先端技術とメディア表現(FTMA2018) 第1回レポートまとめ

Transcript

1. Differentiable Plasticity: A New Method for Learning to Learn- arXiv 2018 Thomas Miconi, Jeff Clune, Kenneth O. Stanley (Uber AI Labs) ͲΜͳ΋ͷʁ ઌߦݚڀͱൺ΂ͯͲ͕͍͜͢͝ʁ ٕज़΍ख๏ͷΩϞ͸Ͳ͜ʁ ٞ࿦͸͋Δʁ ࣍ʹಡΉ΂͖࿦จ͸ʁ CBDLQSPQͱޯ഑߱Լ๏Λ࢖ͬͯՄ઼ੑʢ)FCCJBO ͷ ͭͳ͕ΓΛσβΠϯ͢Δɽ %//ͰϔϒଇΛద༻ͨ͠΋ͷ͸͜Ε·Ͱͳ͔ͬͨɽ Y@K U ͕χϡʔϩϯͷग़ྗɽX@J K͸௨ৗͷ//ͷ܎਺ɽͦΕʹ )FCCଇΛද߲͢ΛՃ͑ͨɽ)FCC͸୯७ʹલޙͷϨΠϠʔͷɼ χϡʔϩϯͷग़ྗͷੵɽ(SBEJFOU
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2. World Models- arXiv 2018 David Ha (Google Brain) Jurgen Schmidhuber (NNAISENSE, Swiss AI Lab, IDSIA (USI & SUPSI)) ͲΜͳ΋ͷʁ ઌߦݚڀͱൺ΂ͯͲ͕͍͜͢͝ʁ ٕज़΍ख๏ͷΩϞ͸Ͳ͜ʁ ٞ࿦͸͋Δʁ ࣍ʹಡΉ΂͖࿦จ͸ʁ ը໘σʔλ͔Β಺෦ϞσϧʹΑͬͯѹॖ৘ใͷ[ͱະདྷ ༧ଌͷ̷Λग़ྗ͠ɼͦͷग़ྗͱใुͷΈ͔ΒࣗΒͷߦ ಈΛֶश͢Δɽ 4DPSFͷ޲্ɽσʔλͷલॲཧ͕͍Βͳ͍ɽ Vision Modelʢߴ࣍ݩ৘ใͷѹॖʣ(VAE)ͱɼMemory RNNʢѹॖ৘ใͷ࣌ܥྻσʔλ ʢهԱʣ͔Βະདྷͷ༧ଌʣ(Mixture Density Network -RNN)ʢ͜ͷ2͕ͭ಺෦Ϟσϧͷ ੜ੒ʣͱɼControlerʢߦಈͷܾఆʣʢ࠷దԽʹCMA-ESΛ࢖༻ʣͷ3ͭΛ૊Έ߹Θͤ ͨɽ Ͳ͏΍ͬͯ༗ޮͩͱݕূͨ͠ʁ ΧʔϨʔεήʔϜͷ4DPSFɽ7J[%PPN ஄Λආ͚ͯੜ͖࢒Δήʔ Ϝ ͷ4DPSFɽ ࠶ֶशͳ͠Ͱ7"&Λ৽͍͠λεΫʹޮՌతʹ࠶ར༻Ͱ͖ͳ͍ɽ
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3. Towards the Automatic Anime Characters Creation with Generative Adversarial Networks (make girls moe) Yanghua Jin School of Computer Science Fudan University Jiakai Zhang School of Computer Science Carnegie Mellon University Minjun Li School of Computer Science Fudan Univerisity Yingtao Tian Department of Computer Science Stony Brook University Huachun Zhu School of Mathematics Fudan Univerisity Zhihao Fang Department of Architecture Tongji Univerisity ͲΜͳ΋ͷʁ ઌߦݚڀͱൺ΂ͯͲ͕͍͜͢͝ʁ ٕज़΍ख๏ͷΩϞ͸Ͳ͜ʁ ٞ࿦͸͋Δʁ ࣍ʹಡΉ΂͖࿦จ͸ʁ Ξχϝإը૾ੜ੒ɽ"$("/Λ༻͍ͯɼ൅ܕ΍ϝΨω ͳͲͷಛ௃ΛදͤΔɽ ΑΓߴղ૾౓Խɽ જࡏม਺Λม͑Δ͜ͱͰࣗࡏʹը૾ੜ੒Ͱ͖Δɽ (FOFSBUPSʹ%FDPOWPMVUJPOͷ୅ΘΓʹ1JYFM
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4. PROGRESSIVE GROWING OF GANS FOR IMPROVED QUALITY, STABILITY, AND VARIATION - ICLR2018 Tero Karras Timo Aila Samuli Laine Jaakko Lehtinen NVIDIA NVIDIA NVIDIA NVIDIA and Aalto University ͲΜͳ΋ͷʁ ઌߦݚڀͱൺ΂ͯͲ͕͍͜͢͝ʁ ٕज़΍ख๏ͷΩϞ͸Ͳ͜ʁ ٞ࿦͸͋Δʁ ࣍ʹಡΉ΂͖࿦จ͸ʁ ௿ղ૾౓͔ΒͩΜͩΜߴղ૾౓ը૾Λ࡞͍ͬͯ͘ख๏ Ͱը૾ΛQYͰੜ੒ɽ ֶशʹࠇຐज़తͳ͜ͱΛ͠ͳͯ͘΋ൺֱత҆ఆֶͯ͠ शͰ͖ɺ׌ͭଟ༷ੑΛ͍࣋ͬͯΔ ੜ੒ͨ͠ը૾͕ຊ෺ͱݟ෼͚͕͔ͭͳ͍΄Ͳ៉ྷ QY
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5. Full-body High-resolution Anime Generation with Progressive Structure-conditional Generative Adversarial Networks – DeNA Blog Tero Karras Timo Aila Samuli Laine Jaakko Lehtinen NVIDIA NVIDIA NVIDIA NVIDIA and Aalto University ͲΜͳ΋ͷʁ ઌߦݚڀͱൺ΂ͯͲ͕͍͜͢͝ʁ ٕज़΍ख๏ͷΩϞ͸Ͳ͜ʁ ٞ࿦͸͋Δʁ ࣍ʹಡΉ΂͖࿦จ͸ʁ QYͷΞχϝը૾ͱϙʔζͷϞʔγϣϯ͔Βɼಈ͖ ͷ͋ΔΞχϝը૾Λੜ੒ɽ إ͚ͩͰͳ͘શ਎ը૾Λੜ੒ɽ ੜ੒ը૾ʹϞʔγϣϯ͕෇͚ΒΕΔɽ Ϟʔγϣϯը૾΋ಉ࣌ʹஈ֊తʹֶशɽ 0QFOQPTFͰϙʔζͷLFZQPJOUΛ఺ੜ੒ɽ Ͳ͏΍ͬͯ༗ޮͩͱݕূͨ͠ʁ ιʔεը૾Λλʔήοτϙʔζͷߏ଄Λ༗͢Δը૾ʹ ม׵͢Δ1(͓Αͼ%1(ͳͲͷख๏ͱൺ΂ͯಉఔ౓ ʹม׵Ͱ͖ͨɽ কདྷσʔληοτΛ࡞ΔΒ͍͠ɽ 1PTF
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12. Super-Fon: Mobile Entertainment to Combat PhonologicalDisorders in Children Rui Neves Madeira, Patrícia Macedo, So a Reis, João Ferreira 
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13. ઎୼ٗढ़ͳϟυΡΠනݳ A Survey of 5G Network: Architecture and Emerging Technologies Authors: A. Gupta, R. K. Jha IEEE Access ਕؔαʖη 201613036_LI ZHENYU ʹΞ͵΍͹ʁ ୊ 5 ੊େʤ5Gʥιϩϧ௪৶໤͹րવͳϤʖδʖ͹གྷٽΝຮͪͤ͹Ͷༀཱིͯ॑གྷ͵ ৿ٗढ़ͶؖͤΖ৆ࡋ͵௒ࠬ݃ՎΝ়ղͤΖ ઎ߨݜڂͳർ΄ͱʹ͗ͤ͟͞͏ʁ ৆ࡋ͵௒ࠬͶΓΕɼD2D ͺक͵঱఼ͳ͢ͱɼҲൢద͵ 5G ιϩϧ௪৶໤Ν఑Ҍͤ Ζɽ ٗढ़Ώघ๑͕ΫϠͺʹ͞ʁ D2DɼঘوໝΠέιηϛ΢ϱφɼέϧΤχɼ͕Γ;Ϡό͹΢ϱνʖϋρφ͗ 5G ι ϩϧ௪৶໤͹Ҳ෨Ͳ͍Ζ͞ͳΝࣖ͢ͱ͏Ζɽ ʹ͑Ώͮͱ༙ްͫͳݗৄͪ͢ʁ 5G ٗढ़Νݜڂ͢ͱ͏Ζҡ͵Ζࠅ͹ήϩʖϕΏؽؖ͵ʹͲɼࣰࢬ͠Ηͱ͏Ζݜڂϕ ϫζΥέφͶͯ͏ͱ͹৆ࡋ͵௒ࠬ͗؜ΉΗͱ͏Ζɽ
14. ٠࿨ͺ͍Ζʃ ༲ྖ͹ଁՅɼυʖνϪʖφ͹րવɼଶͬ࣎ؔ͹୻क़ɼ͕Γ;γʖϑη඾࣯͹޴৏͵ ʹͶༀͶཱིͯͳࢧ͑ɽ ࣏Ͷಣ΋΄͘࿨ชͺʁ Blockchains and Smart Contracts for the Internet of Things
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22. WatchSense: On- and Above-Skin Input Sensing through a Wearable Depth Sensor &+,d Srinath Sridhar1, Anders Markussen2, Antti Oulasvirta3, Christian Theobalt1, Sebastian Boring2 ʹΞ͵΍͹ʃ ઎ߨݜڂͳർ΄ͱʹ͗ͤ͟͞͏ʃ ٗढ़Ώघ๑͹ΫϠͺʹ͞ʃ ʹ͑Ώͮͱ༙ްͫͳݗৄͪ͢ʃ ٠࿨ͺ͍Ζʃ ࣏Ͷಣ΋΄͘࿨ชͺʃ ५ঐشॺक़ज़ॵॳ਱ऐभোৡু১؛ Depth७থ१॑৷ःؚ੐ऋুभൖषඡोॊऒधؚ૬রदभ োৡؚ఺ल੐भ௙શ॑૭ચपघॊ؛ జਟু১म੐ऋুभൖ॑ඡोॊऒधؚ૬রदোৡघॊऒ ध॑৊ৎपੳ௙दऌऩः؛ऽञؚनभ੐दඡोथःॊऊ ॑௙શदऌऩः؛ Depth७থ१॑ॱॵॳએपৌखؚ࿿ीपਝ઼घॊऒध؛ ऽञؚRandomForest॑৷ःथ2஺మद੐॑௙શघॊऒ ध؛ ଺ୡ঻ৰୡपथؚॱॵॳਜ਼઼਄੭भਫનऔؚॱॵॳउे ल঍ংشभੳ௙ಖ২॑௬੼खؚ੔ষଢ଼஢धૻຎघॊऒध दથ஍ਙ॑ਫ਼઒खञ؛ ਠৎਡदDepth७থ१॑५ঐشॺक़ज़ॵॳपඇी੢िऒ धऋदऌऩः؛য୷ख੐ध஡੐खऊ१এشॺदऌथःऩ ः؛ OmniTouch 201713110 ᱎઢၲᆓ #1 (য৑॥ش५)
23. OmniTouch: Wearable Multitouch Interaction Everywhere 8,67b ੅ठઈल૭ચऩdepth७থ१धউট४ख़ॡॱपेॊ३५ॸ঒؛஘رऩुभभ਀ એदॢছইॕढ़ঝदऊणॖথॱছॡॸॕঈऩঐঝॳॱॵॳभ॔উজॣش३ঙথ ॑ਹ৷दऌॊ؛ Chris Harrison, Hrvoje Benko, Andrew D. Willson 201713110 ᱎઢၲᆓ #1 (য৑॥ش५)
24. SkinTrack: Using the Body as an Electrical Waveguide for Continuous Finger Tracking on the Skin &+,b ५ঐشॺक़ज़ॵॳ਱ऐभোৡু১؛५ ঐشॺक़ज़ॵॳप਄ॉહऐैोञਗ਼ாऊ ैৈఢణਯभઐ૴ਦಀ॑৅खؚॱॵॳघ ॊਜ਼઼पૢगथ૗৲घॊਦಀभਜ਼ৼ୷॑ ੦पॱॵॳऔोञৃਚ્॑৒घॊ؛ Yang Zhang, Junhan Zhou, Gierad Laput, Chris Harrison 201713110 ᱎઢၲᆓ #1 (য৑॥ش५)
25. uTrack: 3D Input Using Two Magnetic Sensors 8,67d क़ख़॔ছঈঝഈଜ਱ऐभোৡু১दँॊ؛ ჌ৃ७থ३থॢपेढथؚ஡੐धजभ౎भ ੐॑3Dোৡ३५ॸ঒प૗इॊ؛჌ৃঋॡॺ ঝऊै჌લभx,y,zਜ਼઼धກभ্਱॑ੑ઴घ ॊ؛ঘش२५ॱॹॕपेढथऔऽकऽऩএ ॖথॸॕথॢॱ५ॡप஍ટ৓पઞ৷दऌॊ ऒधऋંऔोञ؛ Ke-Yu Chen, Kent Lyons, Sean White, Shwetak Patel 201713110 ᱎઢၲᆓ #1 (য৑॥ش५)
26. ুฦঋش५भু১दमऩऎؚঁথॻ४ख़ ५ॳকभ७থ३থॢ॑ুभൖ॑৷ःथষ अু১؛ధसञऱङा।ش४७থ१॑ઞ ৷खؚਃ༊৾ಆ॑ిૢघॊऒधद஘رऩ ঁথॻ४ख़५ॳক॑ੳ௙घॊ؛16଻भঁ থॻ४ख़५ॳক॑਴಑95.8%दੳ௙૭ચ؛ BackHand: Sensing Hand Gestures via Back of the Hand 8,67d Jhe-Wei Lin, Chiuan Wang, Yi Yao Huang, Kuan-Ting Chou, Hsuan-Yu Chen, Wei-Luan Tseng, Mike Y. Chen 201713110 ᱎઢၲᆓ #1 (য৑॥ش५)
27. iSkin: Stretchable On-Body Touch Sensors for Mobile Computing &+,d ମ৬भ঱दॱॵॳোৡ॑ষअञीभؚৗख ःျपणऐॊ७থ१दँॊ؛ে৬ి়ਙभ ँॊ੟৬पेढथ੿ैोؚฑໞदಇयघऒ धऋदऌॊ؛੐ؚฏؚປऩनभ஄भୀअ ஘رऩৃਚपँढञ஄द੿ଲदऌॊ؛३থ ॢঝॱॵॳؚঐঝॳॱॵॳपৌૢखथःॊ؛ Martin Weigel, Tong Lu, Gilles Bailly, Antti Oulasvirta, Carmel Majidi, -ÝUJHQSteimle 201713110 ᱎઢၲᆓ #1 (য৑॥ش५)
28. ShareVR: Enabling Co-Located Experiences for Virtual Reality between HMD and Non-HMD Users Jan Gugenheimer, Evgeny Stemasov, Julian Frommel, Enrico Rukzio 
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29. Guessing Objects in Context Karan Sharma , Arun CS Kumar, Suchendra Bhandarkar ୯ޠຒΊࠐΈϕΫτϧΛ༻͍ͯબ୒͞Εͨ14छͷ ը૾ϥϕϧΛֶशͨ͠Ϟσϧ͔Βɺ80छͷϥϕϦ ϯά໰୊Λղ͍ͨɻ ͲΜͳ΋ͷ? ઌߦݚڀͱൺ΂ͯͲ͕͍͜͢͝? ઌߦྫͷθϩγϣοτֶश͸ෳࡶͰεέʔ ϧ͠ʹ͍͕͘ɺͦͷ఺͕վળ͞Ε͍ͯΔɻ ٕज़΍ख๏ͷΩϞ͸Ͳ͜? ୯ޠຒΊࠐΈϕΫτϧ͔Βจ຺Λݟͯಉ࣌ ʹൃੜ͠΍͍͢ϥϕϧΛਪଌ͢Δ఺ɻ Ͳ͏΍ͬͯ༗ޮͩͱݕূͨ͠? microsoftͷCOCOσʔλϕʔεͷϥϕϦϯάΛߦͬͨɻ ٞ࿦͸͋Δ? 80छશͯͷϥϕϧʹֶ͍ͭͯशͨ͠ϞσϧΑΓ͸ਫ਼౓͕௿͍ ͕ɺ͘͝গ਺ͷݕग़ث͔ΒΠϝʔδ಺ͷΦϒδΣΫτΛਪଌՄ ೳͰ͋Δ͜ͱΛࣔͨ͠ɻ ࣍ʹಡΉ΂͖࿦จ͸? ಉ͘͡word2vecΛ෼ྨ໰୊ʹར༻͍ͯ͠Δ Moe Matsuki, and Sozo Inoue, 2016 Recognizing unknown activities using semantic word vectors and twitter timestamps 201813566 ஥ଜ༐അ #1(෹ίʔε) SIGGRAPH '16
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    %JTQMBZ ࢹ఺Ҡಈɼ֎෦ޫݯͷมԽʹରԠͯ͠
 දࣔը૾͕มԽ͢ΔσΟεϓϨΠ ɾর౓ηϯαʔ΍τϥοΩϯάΛ༻͍ͳ͍
 ɾQBTTJWF
    EJTQMBZͷಛ௃ͱͯ͠র໌ͷ
 มԽ΁ͷରԠ͕ૉૣ͍ ɾෳ਺೾௕ʹ͓͍ͯɼ໨తͷ൓ࣹ཰Λಉ࣌ʹ
 ੜ੒͢ΔͨΊͷ࠷దԽܭࢉ ҐஔͷมԽ͢ΔฏߦޫΛ4-.ʹ͋ͯɼ
 ͦΕΛࡱӨͨ͠ ɾ4-.ͷಛੑ্ɼ֯౓෼ղೳ͕௿͍
 ɾදࣔՄೳͳը૾αΠζ͕খ͍͞
 ɾ৭ͷදࣔ͸·ͩͰ͖͍ͯͳ͍ !2 50(`
45. ͲΜͳ΋ͷʁ Ͳ͏΍ͬͯݕূͨ͠ʁ ઌߦݚڀͱൺ΂ͯ ٕज़ͷΩϞ͸ʁ ٞ࿦ ҏ౻ ࣍ʹಡΉ΂͖࿦จ 
 
 )JHIDPOUSBTU
    $PNQVUBUJPOBM
    $BVTUJD
    %FTJHO
    
    ίʔεςΟΫεͱͦΕΛੜ੒͢Δσβ ΠϯͷͨΊͷ࠷దԽΞϧΰϦζϜ ϋΠίϯτϥετɼΑΓ׈Β͔
 ઌߦݚڀʹൺ΂ɼࢹ֮తʹΑΓෳࡶͳ ίʔεςΟΫεΛੜ੒Մೳ ೖࣹද໘͔ΒͷϨΠτϨʔγϯάΛߦ͍ɼ ޫݯ͔Β໨ඪͷը૾Λੜ੒͢Δͷʹޫͷ෼෍ ΛͲ͏มԽͤ͞Ε͹͍͍ͷ͔ͱ͍͏PQUJDBM
    USBOTQPSU
    NBQΛੜ੒͠ܭࢉͨ͠ ࣮ࡍʹΞΫϦϧΛ$/$Ͱ੾࡟ͨ͠΋ͷͰ
 ίʔεςΟΫεΛੜ੒͠ɼࡱӨΛߦͳͬͨ ಺෦൓ࣹͳͲΛߟྀʹೖΕ͍ͯͳ͍
 র໌ͷೖࣹ͕֯ઙ͍ͱ͏·͍͔͘ͳ͍
 ໘ޫݯͩͱDPVTUJDTʹϘέ͕ൃੜ͢Δ !3 50(` 1PJTTPO#BTFE
    $POUJOVPVT
    4VSGBDF
    (FOFSBUJPOGPS
    (PBM#BTFE
    $BVTUJDT
46. ͲΜͳ΋ͷʁ Ͳ͏΍ͬͯݕূͨ͠ʁ ઌߦݚڀͱൺ΂ͯ ٕज़ͷΩϞ͸ʁ ٞ࿦ ҏ౻ ࣍ʹಡΉ΂͖࿦จ 
 
 1PJTTPO#BTFE
    $POUJOVPVT
    4VSGBDF
    (FOFSBUJPO
    GPS
    (PBM#BTFE
    $BVTUJDT
    
    ೚ҙͷίʔεςΟΫεΛੜ੒͢Δಁ໌ ମͷܭࢉख๏ ߴਫ਼ࡉ͔ͭ׈Β͔
 ۶ં໘͕࿈ଓతͳͷͰɼޫͷ෼෍΋ ࿈ଓతʹͳΔɽैདྷ͸཭ࢄత 'JODLI
    FU
    BM<>ͷݚڀʹΑͬͯ
 ੜ੒͞ΕΔίʔεςΟΫεͱൺֱͨ͠ ϝογϡ͕٧·ͬͨ࣌ʹͷ࣮૷Ͱ͸
 ௿ίϯτϥετʹͳΔɽ࠶ϝογϡ
 Խͤ͞ΔͱίʔεςΟΫε͕೾ଧͭɽ !4 50(` ೖࣹޫͱεΫϦʔϯʹরࣹ͞ΕΔޫͷ ؔ܎ͱɼͦΕΛੜ੒͢Δܗঢ়ΛϙΞι ϯํఔࣜʁͰղ͍ͨ
47. ͲΜͳ΋ͷʁ Ͳ͏΍ͬͯݕূͨ͠ʁ ઌߦݚڀͱൺ΂ͯ ٕज़ͷΩϞ͸ʁ ٞ࿦ ҏ౻ ࣍ʹಡΉ΂͖࿦จ 
 
 4IBEPX
    "SU ෳ਺ͷӨֆΛಉ࣌ʹ౤Ө͢ΔͨΊͷ
 ࠷దԽख๏ ೖྗը૾ʹରͯ͠ɼଘࡏ͠ͳ͍%Φϒ
 δΣΫτͷՄೳੑ͕͋Δ͔Βɼগ͠
 มܗ͍ͤͯ͞Δ ೖྗը૾ͷೋ࣍ݩࡾ֯ϝογϡ཭ࢄԽ
 Λ༻͍ͯɼը૾Λ׈Β͔ʹมܗͤͨ͞ ͍͔ͭ͘ͷγϟυ΢ύλʔϯΛ
 ੜ੒͢Δ%ூࠁΛ࡞੒ͨ͠ ɾෳ਺ͷӨΛಉ࣌ʹग़͢ࡍɼͦΕͧΕͷ
 ૊Έ߹Θ͕ͤྑ͘ͳ͍͕࣌͋Δ
 ɾݱࡏͷ࠷దԽ͸ཧ૝తͳ఺ޫݯ͔ฏߦޫͷΈ !5 50(`
    
48. ͲΜͳ΋ͷʁ Ͳ͏΍ͬͯݕূͨ͠ʁ ઌߦݚڀͱൺ΂ͯ ٕज़ͷΩϞ͸ʁ ٞ࿦ ҏ౻ ࣍ʹಡΉ΂͖࿦จ 
 )JHI
    #SJHIUOFTT
    )%3
    1SPKFDUJPO
    6TJOH
    %ZOBNJD
    'SFFGPSN
    -FOTJOH GSFFGPSN
    MFOTΛ༻͍ͨ
 ߴً౓ϓϩδΣΫλʔͷߏ଄ ߴً౓ɼߴίϯτϥετ
 4-.ΛGSFFGPSNMFOTͱͯ͠༻͍ͨ࠷ ॳͷྫ Ґ૬มௐͱGSFFGPSNMFOTͷ࠷దԽܭࢉ ϓϩτλΠϓͷ࡞੒Λߦ͍ɼίϯτϥ ετൺɼϐʔΫً౓ͷήΠϯ஋ͳͲΛ ٻΊͨ ϓϩτλΠϓ͸୯৭͕ͩɼϑϧΧϥʔ΋ Մೳ
 4-.ͱಉظͷࡍʹ஗Ԇ͕ൃੜ͢Δ !6 50(`
49. ͲΜͳ΋ͷʁ Ͳ͏΍ͬͯݕূͨ͠ʁ ઌߦݚڀͱൺ΂ͯ ٕज़ͷΩϞ͸ʁ ٞ࿦ ҏ౻ ࣍ʹಡΉ΂͖࿦จ 
 $PNQVUBUJPOBM
    -JHIU
    3PVUJOH
    %
    1SJOUFE
    0QUJDBM
    'JCFST
    GPS
    4FOTJOH
    BOE
    %JTQMBZ
    ޫϑΝΠόʔ͕ຒΊࠐ·ΕͨΦϒδΣΫτ
 ͷ࡞੒ΞϧΰϦζϜ ैདྷͷGBCSJDBUJPOݚڀͰ͸ද໘ͷ൓ ࣹʹ࡞༻͢Δ΋ͷ͔͠ͳ͔ͬͨ ̎ͭͷද໘ ϑΝΠόʔ͕ೖΔ໘ͱग़Δ ໘ Λೖྗͱͯ͠ઃܭ͢ΔࡍʹϑΝΠόʔ ͷۂ཰Λ࠷খʹ͢ΔΞϧΰϦζϜ ਓͷإ΍൒ٿɼ೴ͳͲͷ͍͔ͭ͘ͷΞϓϦ έʔγϣϯΛ࣮૷ͨ͠
    ·ͨɼλονηϯγϯάͳͲ΋࣮૷ͨ͠ ɹݱࡏͷ%ϓϦϯτͰ࢖༻Մೳͳࡐ ࣭Ͱ͸ϑΝΠόʔ͔Βͷޫ͕࿙Εͯ ίϯτϥετ͕Լ͕Δ !7 50(`
50. ͲΜͳ΋ͷʁ Ͳ͏΍ͬͯݕূͨ͠ʁ ઌߦݚڀͱൺ΂ͯ ٕज़ͷΩϞ͸ʁ ٞ࿦ ҏ౻ ࣍ʹಡΉ΂͖࿦จ 
 
 'PDBM
    4VSGBDF
    %JTQMBZT
    ᫔᫓ௐ੔໰୊Λղܾ͢ΔͨΊͷ
 ଟয఺σΟεϓϨΠ ैདྷͷ઀؟Ϩϯζͱޫݯͱͯ͠ͷ
 σΟεϓϨΠͷߏ੒Ͱ͸য఺໘͸̍Օॴ ඇઢܗ࠷খೋ৐࠷దԽͱઢܗ࠷খೋ৐๏ Λ༻͍ͯը૾͔Βয఺໘Λݟ͚ͭΔ -$04ϕʔεͷ྆؟).%ʹ૊ΈࠐΜͩ 4-. -$04ͷಛੑ্໎ޫ΍
 ৭ऩ͕ࠩൃੜ͢Δ !8 50(`
51. ͲΜͳ΋ͷʁ Ͳ͏΍ͬͯݕূͨ͠ʁ ઌߦݚڀͱൺ΂ͯ ٕज़ͷΩϞ͸ʁ ٞ࿦ ҏ౻ ࣍ʹಡΉ΂͖࿦จ 
 
 'MPBUJOH
    WPMVNFUSJD
    JNBHF
    GPSNBUJPO
    VTJOH
    B
    EJIFESBM
    DPSOFS
    SFqFDUPS
    BSSBZ
    EFWJDF
    ίʔφʔϦϑϨΫλΞϨΠΛ༻͍ͨ
 ϘϦϡʔϝτϦοΫσΟεϓϨΠ Ԝ໘ϛϥʔΛ༻͍ͨϘϦϡʔϝτϦο ΫσΟεϓϨΠͰ͸ऩࠩʹΑͬͯ૾͕ ࿪Ή͕ɼ͜ͷݚڀͰ͸࿪Έ͕গͳ͍ WPMVNFUSJD
    JNBHF͔Β཭Εͨ࣌ʹً౓ ͕ஶ͘͠མͪΔͨΊɼ౤Өը૾ͷσΟ βϦϯάΛߦͬͯɼً౓มௐΛߦͬͨ ̎໘ίʔφʔϦϑϨΫλΞϨΠɼΨϧ όϊɼ%.%Λ༻͍ͨϓϩτλΠϓΛ ੡࡞ ը૾αΠζͱࢹ໺֯͸εΩϟφϛϥʔͱ
 ίʔφʔϦϑϨΫλΞϨΠʹґଘ͢Δ !9 04"`
52. ͲΜͳ΋ͷʁ Ͳ͏΍ͬͯݕূͨ͠ʁ ઌߦݚڀͱൺ΂ͯ ٕज़ͷΩϞ͸ʁ ٞ࿦ ҏ౻ ࣍ʹಡΉ΂͖࿦จ 
 
 5IF
    .BHJD
    -FOT
    3FGSBDUJWF
    4UFHBOPHSBQIZ
    ූ߸Խ͞Εͨ৘ใΛ෮߸Խ͢Δ
 QBTTJWF
    EJTQMBZ HPBM
    CBTFE
    DBVTUJDTͱߟ͑͸ಉ͕ͩ͡ɼ
 ͜ͷݚڀͰ͸൓ࣹޫ΍ࣹग़ޫʹ͍ͭͯߟ͑Δ ম͖ͳ·͠๏Λ༻͍ͯɼྡ઀͢ΔϑΝηοτ ؒͷ'15Λߟྀ͠ͳ͕Βɼ׈Β͔͞ΛߴΊΔ ͜ͱͰɼٻΊΔΠϝʔδͷߴղ૾౓ԽΛͨ͠ %ϓϦϯλʔͱ੾࡟ػΛ༻͍ͯ
 ࣮ࡍʹϓϩτλΠϓΛ࡞੒ͨ͠ Ұൠʹ࢖༻͞ΕΔʹ͸ɼϨϯζ
 ͕େ͖͗͢Δ͠ߴՁ !10 50(` '15ʜGBDFUQBUDI
    USBOTGPSNBUJPO
53. ͲΜͳ΋ͷʁ Ͳ͏΍ͬͯݕূͨ͠ʁ ઌߦݚڀͱൺ΂ͯ ٕज़ͷΩϞ͸ʁ ٞ࿦ ҏ౻ ࣍ʹಡΉ΂͖࿦จ 
 
 1BTTJWF
    .JEBJS
    %JTQMBZ
    র໌Λ౰͚ͯͨ࣌ͩݟ͑ΔΑ͏ʹͳ ΔσΟεϓϨΠ QBTTJWF
    EJTQMBZͱͯ͠ʮϢʔβʔͷߦಈʹ൓Ԡ ͢Δʯʮೖࣹ͢ΔޫʹԠ͡Δʯͱ͍͏छྨ͕͋ Δ͕͜ͷݚڀͰ͸ͲͪΒ΋ߦͬͨ ؀ڥޫʹ൓Ԡ͠ͳ͍Α͏ʹ͢Δޫֶઃܭ ϓϩτλΠϓΛ࡞੒͠ɼ໌Δ͞ͳͲʹ ͍ͭͯඃݧऀ࣮ݧΛߦͬͨ ޫ͸ਖ਼໘͔Β౰ͯΔඞཁ͕͋Δ
 େਓ͸ڻ͕͘ɼࢠڙ͸ڻ͔ͳ͍
 "*1ʹΑΔڸ໘൓ࣹʹΑͬͯάϨΞ͕ੜ͡Δ !11 "$&`
54. ͲΜͳ΋ͷʁ Ͳ͏΍ͬͯݕূͨ͠ʁ ઌߦݚڀͱൺ΂ͯ ٕज़ͷΩϞ͸ʁ ٞ࿦ ҏ౻ ࣍ʹಡΉ΂͖࿦จ 
 
 1JYFM
    "SU
    XJUI
    3FGSBDUFE
    -JHIU
    CZ
    3FBSSBOHFBCMF
    4UJDLT ΞΫϦϧͷεςΟοΫʹ༻͍ͨϐΫη ϧΞʔτʹͯɼ೚ҙͷը૾Λදࣔ͢Δ QBQBTΒͷίʔεςΟΫεΛੜ੒͢Δ ݚڀʹൺ΂ɼੜ࢈ίετ͕௿͍ εςΟοΫΛಁաͨ͠ޫ͕೚ҙͷը૾ Λදࣔ͢ΔΑ͏ʹɼεςΟοΫͷ഑ஔ Λ࠷దԽ໰୊Λղ͍ͯಋ͘ ͍͔ͭ͘ͷύλʔϯΛ੡࡞͠ɼJOQVU
    JNBHFͱಉ༷ͷֆ͕ಘΒΕͨͷΛ֬ೝ ͨ͠ ೖྗύλʔϯͷίϯτϥετൺ͕ߴ͍ ͱ͏·͘දݱͰ͖ͳ͍ !12 &630(3"1)*$4`
    
55. ͲΜͳ΋ͷʁ Ͳ͏΍ͬͯݕূͨ͠ʁ ઌߦݚڀͱൺ΂ͯ ٕज़ͷΩϞ͸ʁ ٞ࿦ ҏ౻ ࣍ʹಡΉ΂͖࿦จ 
 
 4VOOZ
    %BZ
    %JTQMBZ
    .JEBJS
    *NBHF
    'PSNFE
    CZ
    4PMBS
    -JHIU
    "*ϓϨʔτΛ༻͍ͨ೔ޫԼͰ؍࡯Մೳ ͳۭதө૾૷ஔ ΤωϧΪʔফඅ͕গͳ͍
 ैདྷͷݚڀͰ͸԰֎Ͱͷۭதө૾͸ े෼ͳ໌Δ͕͞ग़ͳ͍
 ଠཅޫΛҰ౓֦ࢄͤ͞ΔͨΊͷσΟ ϑϡʔβʔͷબఆ ଠཅޫΛ໛ͨ͠র໌Λઃஔ͠ɼࣨ಺Ͱ࣮ݧΛߦͬͨ
 ϓϩτλΠϓΛ࡞੒͠ɼ԰಺Ͱً౓ɼίϯτϥετ Λܭଌ͠԰֎Ͱ࣮ࡍʹݟ͑Δ͔Λ֬ೝͨ͠ ҉͍৔ॴͰ͸࢖༻Ͱ͖ͳ͍
 ಁաܕʹͰ͖ͳ͍
 "*ϓϨʔτʹΑͬͯղ૾౓͕௿Լ͢Δ !13 *44`
56. ͲΜͳ΋ͷʁ Ͳ͏΍ͬͯݕূͨ͠ʁ ઌߦݚڀͱൺ΂ͯ ٕज़ͷΩϞ͸ʁ ٞ࿦ ҏ౻ ࣍ʹಡΉ΂͖࿦จ 
 
 %
    *OUFSBDUJOH
    XJUI
    B
    3FMJHIUBCMF
    (MBTTFT'SFF
    %
    %JTQMBZ
    ؀ڥޫʹ൓Ԡ͢Δάϥεແ͠Ͱݟ͑Δ %
    EJTQMBZ %
    MJHIUpFMEͷೖग़ྗΛϦΞϧλΠϜ Ͱߦ͏ ؀ڥޫ΍Ϣʔβʔ͕ಈ͔ͯ͠Δޫݯͷ MJHIU
    pFMEΛऔಘ͢Δ
 (16ʹΑΔϨϯμϦϯά .3*ͷσʔλΛ༻͍ͯσΟεϓϨΠͷ ੑೳΛࣔͨ͠ ۭؒ෼ղೳɼ֯౓෼ղೳ͕௿͍
 ݱࡏͷϓϩτλΠϓͰ͸άϨʔεέʔϧ ͷΈ !14 $)*`
57. ͲΜͳ΋ͷʁ Ͳ͏΍ͬͯݕূͨ͠ʁ ઌߦݚڀͱൺ΂ͯ ٕज़ͷΩϞ͸ʁ ٞ࿦ ҏ౻ ࣍ʹಡΉ΂͖࿦จ 
 
 1SJOUJOH
    BOJTPUSPQJD
    BQQFBSBODF
    XJUI
    NBHOFUJD
    qBLFT ࣓ੑϑϨʔΫͱޫߗԽथࢷΛ༻͍ͯɼ
 ҹ࡮͢Δ΋ͷͷ#3%'Λ੍ޚ͢Δ ҆Ձʹߴ෼ղೳͷ#3%'Λ࡞੒͢Δ ͜ͱ͕Մೳ ࣓ثϑϨʔΫ͕ಛఆͷ഑ஔʹͳΔΑ ͏ʹ࣓৔Λ଍͠߹ΘͤΔ ͍͔ͭ͘ͷҟͳΔ࣓৔Λ༻͍ͯɼ TJHHSBQI
    MPHPΛϓϦϯτͨ͠ ࣓ثϑϨʔΫ͕খ͍࣌͞͸͏·͍͔͘ͳ͍
 ϒϥγΛ༻͍ͯɼϑϨʔΫΛՃ͑Δͱϒϥο γϯάͷํ޲ʹ͋Δఔ౓ͷҟํੑ͕ੜ͡Δ !15 50(`
58. ͲΜͳ΋ͷʁ Ͳ͏΍ͬͯݕূͨ͠ʁ ઌߦݚڀͱൺ΂ͯ ٕज़ͷΩϞ͸ʁ ٞ࿦ ҏ౻ ࣍ʹಡΉ΂͖࿦จ 
 
 1SPKFDUJPO
    #BTFE
    3FBMUJNF
    .BUFSJBM
    "QQFBSBODF
    .BOJQVMBUJPO
    ϓϩδΣΫγϣϯϚοϐϯάΛ༻͍ ͯ෺ମͷ֎؍Λม͑Δ ΦϒδΣΫτͷܗঢ়΍ҐஔΛ߹ΘͤΔ͕ͳ͍ɽ ·ͨɼಈతͳΦϒδΣΫτʹ΋ద༻Մೳ
 ೝ஌Պֶʹج࣭ͮ͘ײૢ࡞ ΧϝϥͰऔಘͨ͠ը૾ʹରͯ͠ɼΧϥʔϚον ϯά΍ΨϯϚิਖ਼Λߦͬͯੜ੒ͨ͠ը૾͕ന৭ ޫԼͰͲͷΑ͏ʹݟ͑Δ͔Λਪఆ͢Δ ಁ໌ײ΍ޫ୔ײͷ࠶ݱΛϓϩτλΠϓ Λ੡࡞ͯ͠ߦͬͨ ൒ಁ໌ʹ͠Α͏ͱ͢Δͱɼڸ໘൓ࣹ͕ݱΕͳ ͍
 ΞϧϕυΛࣄલʹ෼཭͓ͯ͘͜͠ͱͰࠇͭͿ ΕΛճආͰ͖Δ !16 $713`
59. ͲΜͳ΋ͷʁ Ͳ͏΍ͬͯݕূͨ͠ʁ ઌߦݚڀͱൺ΂ͯ ٕज़ͷΩϞ͸ʁ ٞ࿦ ҏ౻ ࣍ʹಡΉ΂͖࿦จ 
 
 %
    *NBHJOH
    UISPVHI
    4QSBZ0O
    0QUJDT
    ਫణͷ͍ͭͨ૭ͷࣸਅ͔ΒMJHIU
    pFME ΛಘΒΕΔ ैདྷ͸ϚΠΫϩϨϯζΞϨΠͳͲΛ༻ ͍ͨޫֶܥ΍ɼΧϝϥΞϨΠͳͲ͕ඞ ཁͩͬͨ ೖ೦ʹઃܭ͞ΕͨޫֶܥͰͳ͘ͱ΋ɼ Ͳ͏͍͏ৼΔ෣͍Λ͢Δ΋ͷ͔Θ͔ͬ ͍ͯΕ͹ϨΠτϨՄೳͱ͍͏͜ͱ ͜ͷޫֶܥ͸ఆྔతʹධՁ͠ʹ͍͘
 ਫణͷද໘ͷ%εΩϟϯΛߦ͍͑ͯͳ͍͔Βɼ.JUTVCB
    SFOEFSΛ࢖ͬͯΠϝʔδΛϨϯμϦϯά͠ɼϨΠτϨͷਫ਼౓ ΛධՁͨ͠ ෭࢈෺Ͱ͸͋Δ͕ɼӷణͷεΩϟϯʹ΋໾ཱͭ
 ߴ඼࣭ͳग़ྗΛಘΔʹ͸σϓεਪఆ΍ϑΟϧλ Ϧϯά͕ॏཁ !17 50(`
60. ͲΜͳ΋ͷʁ Ͳ͏΍ͬͯݕূͨ͠ʁ ઌߦݚڀͱൺ΂ͯ ٕज़ͷΩϞ͸ʁ ٞ࿦ ҏ౻ ࣍ʹಡΉ΂͖࿦จ 
 
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    #Y%'
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 ΑΓࣗ༝౓ͷߴ͍#Y%'σΟϓϨΠΛ੡࡞͢Δ͜ ͱ͕Մೳ ଟ૚ͷಁ໌ϑΟϧϜʹΑΔճંΛϞσϧԽ͠ɺ ೚ҙͷ#3%'·ͨ͸#5%'Λ࠶ݱ͢Δҹ࡮ύ λʔϯΛੜ੒͢Δٯ໰୊Λղͨ͘ΊͷҐ૬ۭ ؒϞσϧ ϑΥτϓϩολʔΛ༻͍ͯϓϩτλΠϓΛ࡞ ੒͠ɼͦ͜ʹίώʔϨϯτͳϨʔβʔͱΠ ϯίώʔϨϯτͷর໌Λ౰ͯͨ র໌৚݅Λఆٛ͢Δඞཁ͕͋Δɽ
 ॲཧ࣌ؒΛ͞Βʹૣ͘Ͱ͖Ε͹ɼΑΓߴ඼࣭ͳ #Y%'σΟεϓϨΠΛੜ੒Ͱ͖Δ
 ϑΣϜτඵϨʔβʔՃ޻͍ͨ͠ !18 50(`
61. ͲΜͳ΋ͷʁ Ͳ͏΍ͬͯݕূͨ͠ʁ ઌߦݚڀͱൺ΂ͯ ٕज़ͷΩϞ͸ʁ ٞ࿦ ҏ౻ ࣍ʹಡΉ΂͖࿦จ 
 
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    BOE
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    4FOTJUJWF
    %JTQMBZ
    PG
    %
    $POUFOU র໌ͷมԽʹΑΔϋΠϥΠτ΍ӨɼԞ ߦ͖ࢹࠩΛ࠶ݱ͢ΔσΟεϓϨΠ ैདྷͷ%σΟεϓϨΠ͸֯౓ɼҐஔ ͕มಈ͢Δর໌Λߟྀ͍ͯ͠ͳ͔ͬͨ ૚ͷϨΠϠʔͷ͏ͪɼલ໘ΛGPDVTJOH
    PQUJDTͱͯ͠࢖༻͠ɼϨϦʔϑͷΑ͏ͳޙ ໘Λ൓ࣹͱͯ͠࢖༻͢Δ ݱࡏͷ4-.ͷੑೳʹدΒͣɼఏҊख๏ͷγϛϡ ϨʔγϣϯΛߦͬͨ
 ·ͨɼϓϩτλΠϓΛ࡞੒͠ը૾ΛࡱӨͨ͠ ࠓճͷϓϩτλΠϓ͸ߴղ૾౓͕ͩɼ4-.ͷα Πζతʹখ͘͞ɼ൓Ԡ͢Δ֯౓΋ඇৗʹڱ͍
 άϨʔεέʔϧ !19 *$$1`
62. ͲΜͳ΋ͷʁ Ͳ͏΍ͬͯݕূͨ͠ʁ ઌߦݚڀͱൺ΂ͯ ٕज़ͷΩϞ͸ʁ ٞ࿦ ҏ౻ ࣍ʹಡΉ΂͖࿦จ 
 
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 ෺ମΛಈ͔ͨ͠ࡍͷ஗ԆΛ֬ೝͨ͠ ϓϩδΣΫλʔ͕ҰͭͰ͸ෆՄೳ
 τϥοΩϯάʹΑͬͯ͸౤Өʹ஗Ԇ͕ൃੜ͢Δ ͕ɼ͜Ε͸࠷దԽܭࢉʹΑΔ΋ͷͰ͸ͳ͍ !20 50(`
63. ͲΜͳ΋ͷʁ Ͳ͏΍ͬͯݕূͨ͠ʁ ઌߦݚڀͱൺ΂ͯ ٕज़ͷΩϞ͸ʁ ٞ࿦ ҏ౻ ࣍ʹಡΉ΂͖࿦จ 
 
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 ϥδΦϝτϦοΫิਖ਼Λ͢Δ͜ͱͰɼ͞Βʹվળͦ͠͏
 EZOBqBTI࢖͑͹ಈతͳΦϒδΣΫτʹ΋ద༻Ͱ͖ͦ͏ !21 5"1`
64. ͲΜͳ΋ͷʁ Ͳ͏΍ͬͯݕূͨ͠ʁ ઌߦݚڀͱൺ΂ͯ ٕज़ͷΩϞ͸ʁ ٞ࿦ ҏ౻ ࣍ʹಡΉ΂͖࿦จ 
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65. ͲΜͳ΋ͷʁ Ͳ͏΍ͬͯݕূͨ͠ʁ ઌߦݚڀͱൺ΂ͯ ٕज़ͷΩϞ͸ʁ ٞ࿦ ҏ౻ ࣍ʹಡΉ΂͖࿦จ 
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 ͢Έ·ͤΜɼ͜͜΋͏গͪ͠ΌΜͱಡΈ·͢ ޫֶૉࢠ΍ճંૉࢠɼϓϩτλΠϓͷΧϝϥ ͷઃఆͱγϛϡϨʔγϣϯ݁Ռ͕Ұக͢Δ͜ ͱΛ֬ೝͨ͠ ·ͩΞϧΰϦζϜ͕؆୯ͳͨΊɼ)%3Πϝʔ δϯάͳͲͷߴ౓ͳλεΫʹ͸దͯ͠ͳ͍
 ΦϒδΣΫτؒͷΦΫϧʔδϣϯͷڥք͕ద ੾ʹॲཧͰ͖ͯͳ͍ !23 4*((3"1)`
66. ͲΜͳ΋ͷʁ Ͳ͏΍ͬͯݕূͨ͠ʁ ઌߦݚڀͱൺ΂ͯ ٕज़ͷΩϞ͸ʁ ٞ࿦ ҏ౻ ࣍ʹಡΉ΂͖࿦จ 
 
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 ԁਲ਼ͷܗঢ়ΛσΟεϓϨΠαΠζͱϏϡʔ ΞʔͷҐஔͱ͍͏ؔ਺ʹͯ͠ղ͍ͨ J
    QBE
    ͱϓϥενοΫγʔτΛ༻͍ͨϓϩτλΠϓ Λ੡࡞
 ୯؟ɼ྆؟ͷ྆ํͷγεςϜΛ༻͍ͯɼඃݧऀ࣮ݧ Λߦͬͨ ໌Δ͍԰֎ʹ͸ద͞ͳ͍͕ɼனͷΦϑΟεͰ࢖ ͑Δ͘Β͍ʹ͸े෼ͳً౓
 Z [࣠ͷҠಈʹରͯ͠͸มԽ͕Θ͔ΓͣΒ͍
 কདྷతʹ͸಄෦ΛτϥοΩϯά͍ͨ͠ !24 6*45`
67. ͲΜͳ΋ͷʁ Ͳ͏΍ͬͯݕূͨ͠ʁ ઌߦݚڀͱൺ΂ͯ ٕज़ͷΩϞ͸ʁ ٞ࿦ ҏ౻ ࣍ʹಡΉ΂͖࿦จ 
 
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 ࠓޙɼ࿥ԻʹΞϯϏιχοΫΛ༻͍Δ༧ఆ !25 4"`
68. 
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73. DeepWear: a Case Study of Collaborative Design between Human and Artificial Intelligence ˌ'5." Natsumi Kato* University of Tsukuba Hiroyuki Osone* University of Tsukuba Daitetsu Sato University of Tsukuba Naoya Muramatsu University of Tsukuba Yoichi Ochiai University of Tsukuba University of Tsukuba Hiroyuki Osone* University of Tsukuba Daitetsu Sato University of Tsukuba Naoya Muramatsu University of Tsukuba Yoichi Ochiai University of Tsukuba ͲΜͳ΋ͷʁ %$("/Λ༻ֶ͍ͯशͤͨ͞ϒϥϯυͷ༸෰ͷը ૾σʔλ͔Βಛ௃Λֶश͠෰ͷΠϝʔδΛੜ੒ɺ ύλʔφʔ͕ͦΕΛ΋ͱʹ෰ΛσβΠϯ͢Δਓؒ ͱਓ޻஌ೳͷ༥߹తΫϦΤΠςΟϒ ٞ࿦͸͋Δʁ Ͳ͏΍ͬͯ༗ޮͩͱূ໌ͨ͠ʁ "NB[POͷϓϩδΣΫτΈ͍ͨʹػց͚ͩͰ΍Ζ ͏ͱ͢Δͱͩͱ·ͩணΒΕΔ෰ʹͳΒͳ͍
    ϚςϦΞϧʢૉࡐʣ΋ಛ௃ͷ࠶ݱʹͱͬͯେ੾
    ݩͷ෰ΑΓ๭ϒϥϯυͬΆ͍ͱ͍͏ධՁग़ͨ
    աڈʹϚʔέοτʹग़ͨ๭ϒϥϯυͷ෰ͱଞͷϒ ϥϯυͷ෰ͱ͜ͷݚڀͰੜ੒ͨ͠෰Λൺ΂ͯͲΕ ͕๭ϒϥϯυͩͱࢥ͏͔ϢʔβʔελσΟ Alec Radford, Luke Metz, and Soumith Chintala. 2015. Unsupervised representation learning with deep convolutional generative adversarial networks. 
 ٕज़΍ख๏ͷΩϞ ("/ͷߏ଄ʹ%//Λద༻ͨ͠%$("/Λ༻͍ͯ ੜ੒ͨ͠෰ͷΠϝʔδը૾ʹج͖ͮύλʔφʔʢਓ ؒʣ͕෰ͷύλʔϯΛੜ੒͢Δ ઌߦݚڀͱൺ΂ͯԿ͕͍͢͝ʁ ਓؒΛੜ੒ͷաఔʹಥͬࠐΉ͜ͱͰ࣮ࡍʹணΒΕ Δ෰Λ࡞ΕΔ ࣍ʹಡΉ΂͖࿦จ͸ʁ 
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74. UNSUPERVISED REPRESENTATION LEARNING WITH DEEP CONVOLUTIONAL
 GENERATIVE ADVERSARIAL NETWORKS ͲΜͳ΋ͷʁ $//Λ࢖ͬͨݚڀʹ͓͍ͯ͋·Γ஫໨͞Ε͍ͯ ͳ͍ڭࢣͳֶ͠शΛ༻͍ͨݚڀ
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    நग़ͨ͠ಛ௃Λ࢖ͬͯੜ੒Λߦ͏͜ͱ͕Ͱ͖Δ ٕज़΍ख๏ͷΩϞ ࠷ۙൃද͞Εͨ$//ߏ଄ͷมԽܥΛ༻͍Δ͜ͱ ʹΑͬͯ%//ͷ("/΁ͷಋೖΛՄೳʹ ઌߦݚڀͱൺ΂ͯԿ͕͍͢͝ʁ %//ͷߏ଄Λ༻͍ͯ("/ͷߏ଄ΛΞοϓσʔτ ͢Δ͜ͱʹ੒ޭˠڭࢣͳֶ͠शʹ࢖͑Δ ٞ࿦͸͋Δʁ ·ͩϞσϧͷෆ҆ఆ͕͞࢒ΓɺϞσϧͷ܇࿅͕௕ ͘ͳΔͱϑΟϧλʔͷαϒηοτ͕୯ҰͷৼಈϞʔ υʹ่ΕΔ
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    Ͳ͏΍ͬͯ༗ޮͩͱূ໌ͨ͠ʁ ܇࿅͞Εͨ%$("/ͱಛ௃நग़ͱը૾ੜ੒Λߦ͏ ྨࣅͷωοτϫʔΫͱͷΤϥʔ஋ͷى͖͞Λൺֱ ࣍ʹಡΉ΂͖࿦จ͸ʁ LAPGAN(Denton et al., 2015) ͔ͳ ˌ'5." 
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106. Hybrid Practice in the Kalahari: Design Collaboration through Digital Tools and Hunter-Gatherer Craft - CHI15 Jennifer Jacobs, Amit Zoran (MIT Media Lab, The Hebrew Univ.) "CTU *OUSPEVDUJPO $PODMVTJPO ඇσδλϧͳ޻ܳͱσδλϧϑΝϒϦέʔγϣϯͷ૊Έ߹Θͤɻඇσδλϧͷ׳श΍Ձ஋؍Λಎ࡯͢ΔͨΊͷڞಉ ੍࡞ɻ ఻౷తͳઌॅຽจԽͷ࣮ફΛཧղ͢Δ͜ͱͰɼٕज़తʹࢧ࣋͞ΕͯΔ੡࡞ʹؔ͢Δର࿩͕ڧԽ͞ΕΔɻڞಉ੍࡞ ͷ࢓૊ΈΛ௨ͨ͡ඇσδλϧͳจԽͱͷؔΘΓʹΑͬͯɼίϛϡχέʔγϣϯͷҧ͍ΛຒΊΔ͜ͱ͕Ͱ͖ɼจԽʹ ͓͚Δ੡࡞Λཧղ͢Δ͜ͱ͕Ͱ͖Δɻඇσδλϧ࢈ۀจԽʹσδλϧπʔϧΛ૊ΈࠐΉ͜ͱͰɼٕज़ͷΞϑΥʔμ ϯεͷݶքʹ͍ͭͯͷ৽ͨͳಎ࡯ΛಘΔɻ ίϛϡχέʔγϣϯ্ͷݫ͍͠՝୊ʹ௚໘ͭͭ͠ɼڞಉ੍࡞͸ࣗ෼ͷ໨తΛΞϓϩʔνΛ఻͑Δ͜ͱ͕Ͱ͖Δɻڞ ಉ੍࡞ͷ؀ڥͷՁ஋ΛաখධՁ͢΂͖Ͱ͸ͳ͍ɻ 
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107. Cooking with Robots: Designing a Household System Working in Open Enviroments - CHI10 Yuta Sugiura, Daisuke Sakamoto, Anusha Withana, Masahiko Inami , Takeo Igarashi (KMD, Univ. of TokyoɼJST, ERATO, IGARASHI Design UI Projectɹ) "CTU *OUSPEVDUJPO $PODMVTJPO Φʔϓϯͳ؀ڥͰಈ࡞͢ΔௐཧγεςϜͷఏҊɻ༠ಋՃ೤ௐཧثͷϙοτʹ༷ʑͳࡐྉΛೖΕͯௐཧ͢Δɻࢦࣔॻ ʹैͬͯՃ೤ڧ౓Λௐ੔͢ΔɻγεςϜ͕ͲͷΑ͏ʹͯ͠ϩϘοτٴͼਓؒݻ༗ͷཁૉΛڞ༗ϫʔΫεϖʔεʹ૊ ΈࠐΉ͔ɻ ΄ͱΜͲͷՈి͸ϘοΫεͱ͍͏ด࠯͞Εͨ؀ڥͰಈ࡞͍ͯ͠ΔɻΦʔϓϯͳ؀ڥͰΑΓߴ౓ͳλεΫΛ࣮ߦ͢Δ Ոి͕ඞཁɻϩϘοτ͸ϢʔβʔͱۭؒΛڞ༗͢ΔͨΊɼ؀ڥͷಈతมԽʹ҆શͰରԠͰ͖Δඞཁ͕͋Δɻෳࡶ ͳݱ࣮ͷλεΫΛ੍ޚ͢ΔͨΊͷద੾ͳϢʔβʔΠϯλʔϑΣʔε΋ఏڙ͢Δඞཁ͕͋Δɻ Ϣʔβͱͷڞ༗ௐཧ؀ڥΛ࣋ͭௐཧγεςϜ$PPLZΛ։ൃͨ͠ɻ୯७ͳௐཧλεΫʹ͢ΔͨΊʹɼௐཧࢦࣔͱϰΟ δϡΞϧϚʔΧʔؚ͕·ΕͨϨγϐΛ࢖༻͢ΔɻϢʔβ͸ɼࡐྉఴՃͷλΠϛϯάɼುͷ֧፩ɼిؾௐཧثͷ੍ޚ ͳͲͷࢦࣔΛγεςϜʹग़͢ɻϩϘοτ͸ͦͷࢦࣔʹैͬͯλεΫΛ࣮ߦɻ࣮ݧͰ͜ͷख๏Ͱ͏·͘ௐཧͰ͖Δ͜ ͱΛ֬ೝͨ͠ 
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108. The Hybrid Artisans: A Case Study in Smart Tools - ToCHI2014 AMIT ZORAN, ROY SHILKROT, SURANGA NANYAKKARA, JOSEPH PARADISO(MIT Media Lab, Singapore Univ. of Tech. and Design) "CTU *OUSPEVDUJPO $PODMVTJPO ਓؒͱػց͕૬৐ޮՌͰಈ࡞͢ΔϋΠϒϦου૬ޓ࡞༻ͷύϥμΠϜΛ࣮ূ͢ΔΑ͏ͳσδλϧϑΝϒϦέʔγϣ ϯͱ޻ܳΛ૊Έ߹ΘͤΔΞϓϩʔνͷఏҊɻ'SFF%͸ख࣋ͪͷσδλϧூࠁσόΠεͰɼίϯϐϡʔλͰ؂ࢹ͞Εɼ ੡࡞ऀ͸ࣗ༝ʹૢ࡞Ͱ͖Δɻ͋Β͔͡Ίઃܭ͞Εͨ%Ϟσϧʹج͍ͯɼΦϒδΣΫτͷଛইͷϦεΫ͕௿͍ͱ͖ ʹͷΈಈ࡞͢Δ ਓؒͱίϯϐϡʔλͷ྆ํʹΑͬͯੜΈग़͞Εͨ৽͍͠ϋΠϒϦουྖҬΛཱ֬͠ɼ੡଄ϓϩηεʹ͓͚Δओ؍ తҙࢥܾఆΛऔΓೖΕɼσβΠϯͱϑΝϒϦέʔγϣϯͷؒͷઢΛ͍͋·͍ʹ͢Δɻ޻ܳ඼ΛσδλϧྖҬʹಋೖ ͢Δ 'SFF%͸ɼσβΠφʔ͕৽͍͠ํ๏Ͱݪࡐྉʹ;ΕΔͱಉ࣌ʹɼ૑଄ͷաఔͷҰ؀ͱͯ͠ݮࢉతϑΝϒϦέʔγϣ ϯΛ౷߹͢Δ͜ͱ͕Ͱ͖Δɻख࣋ͪͷூࠁπʔϧͱ౷߹͞Εͨσδλϧػೳ͕ɼෳࡶͳ%ΦϒδΣΫτΛூࠁ͢ Δࡍʹɼܦݧͷઙ͍$"%σβΠφʔΛࢧԉ͢Δ৽ٕज़ͷఏҊɻਓؒͷओ؍ੑͱػցͷࣗಈੜ࢈Λ༥߹ͨ͠ɻ 
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109. Laser Cooking: a Novel Culinary Technique for Dry Heating using a Laser Cutter and Vision Technology - CEA’12 Kentaro Fukuchi, Kazuhiro Jo, Akifumi Tomiyama, Shunsuke Takao (Meiji Univ., Institute of Advanced Media Arts and Sciences, Tokyo Univ. of the Arts) "CTU *OUSPEVDUJPO $PODMVTJPO ס೤ௐཧػثͱͯ͠ϨʔβʔΧολʔΛ༻͍ͨ৽͍͠ௐཧٕज़ɻίϯϐϡʔλ੍ޚͷϨʔβʔΧολʔͱը૾ॲཧ ٕज़Λ࢖༻ͯ͠ɼܗঢ়΍૊੒ʹԠͯ͡ࡐྉΛௐཧ͠ɼ৽͍͠ຯ΍ςΫενϟʔɼ૷০ɼ*%ΛூࠁՄೳɻค຤࠭౶ Λ༻͍ͨ৯༻ூࠁΛ࡞੒͢Δଟ૚%ϓϦϯτٕज़ͷఏҊɻ ݱ୅ͷྉཧͰ͸ɼߴ౓ͳՊֶٕज़Λ࢖ͬͯ৽͍͠ຯΛ࣮ݱ͍ͯ͠Δɻۙ୅తͳྉཧ΁ͷΞϓϩʔν͸ɼ৘ใٕज़ ͱϝΧτϩχΫεΛ׆༻͍ͯ͠Δɻ୹࣌ؒͰہॴతʹ੒෼ΛՃ೤͢Δ͜ͱ͕Ͱ͖Δ-BTFS
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110. Hybrid Basketry: Interweaving Digital Practice within Contemporary Craft - SIGGRAPH’13 Art Gallery AMIT ZORAN (MIT Media Lab) "CTU *OUSPEVDUJPO $PODMVTJPO ݱ୅ͷ%ҹ࡮ͱ఻౷޻ܳΛ༥߹ɻ̏%ϓϦϯτߏ଄͕ख৫Γύλʔϯͷ৳௕΍ൃలΛՄೳʹ͢ΔΑ͏ͳܗΛͯ͠ ͍ΔϋΠϒϦουόεέοτϦʔΛ։ൃͨ͠ɻ%ϓϦϯτ͞ΕͨϓϥενοΫͷཁૉ͸σδλϧۂ཰ͱϚχϗʔ ϧυͷඒֶʹߩݙ͠ɼख৫Γͷѵɼδϡʔυ౳͸ಠಛͷ༗ػతັྗͰόεέοτΛຬͨ͢ɻݱ୅తͳσβΠϯͱ੡ ࡞ͷΞϓϩʔνʹ͓͚Δ޻ܳͱ఻౷ͷࡏΓํʹ͍ͭͯͷਂ͍ٞ࿦ σδλϧ੡࡞͸޻ܳ඼ͷ෺ཧతՁ஋ʹେ͖ͳӨڹΛ༩͑ΔɻσδλϧͰઃܭ͞Εͨ޻ܳ඼͸ຊ࣭తʹ࠶ݱՄೳͰ͋ Δ͕ɼରরతʹɼ఻౷తͳ޻ܳ඼͸શ͘ಉ͡σβΠϯͷ܁Γฦ͠͸΄ͱΜͲෆՄೳɻഁյ͞Εͨ΋ͷΛ෮ݩ͢Δ ϓϩηεͰɼσδλϧ޻ܳΛ૊ΈࠐΉ͜ͱͰ৽͍͠΋ͷ͕ੜ੒͞ΕΔɻ ৽͍͠σδλϧٕज़ͱ఻౷తͳख࡞ۀͷٕज़Λ୳ٻͨ͠ɻػց͸੍ޚͱΠϊϕʔγϣϯͷੜ੒ثɼਓؒͷख࡞ۀɼ ܳज़తੜ࢈ͱจԽͷอޢͱͯ͠ɼσδλϧͱ఻౷ͷۃੑʹ͍ͭͯͷ৽͍͠ߟ͑ํΛ։ൃ͢ΔɻσδλϧจԽɼσβ Πϯͱ੡଄ͷαΠόʔεϖʔεͰࣦΘΕͨ෺࣭తΞΠσϯςΟςΟΛ࠶ར༻͢ΔՄೳੑ͕͋Δɻ 
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111. HeartChat: Heart Rate Augmented Mobile Messaging to Support Empathy and Awareness ƒ”‹ƒ ƒ••‹„ǡƒ‹‡Ž—•…Š‡ǡƒ™‡ÏǤ‘œƴniak, Florian Alt ˑThe ACM CHI Conference on Human Factors in Computing Systems HeartChat ͮͱʃ ϟριʖζͳͳ΍Ͷৼധ਼Νૻ৶ͤΖ͞ͳ͗Ͳ͘ΖϠώ΢ϩοϡρφΠϕϨίʖεϥϱɽ ՁͲ HeartChat? ॊཔ͹τΫηφͫ͜͹αϝϣωίʖεϥϱΠϕϨͲͺ૮घ͹ৼ৚Νཀྵմ͢ͰΔ͏͹Ͳɼ اช࣊ΏηνϱϕΏժ଀Νૻ৶ͤΖେΚΕͶਫ਼ରυʖνͲ״৚ΝනݳͤΖɽ ʹ͑Ώͮͱʃ
112. 1)ϟριʖζૻ৶࣎͹ৼധ਼ͶΓͮͱϟριʖζΝ৯෉ͤ͜Ζ HeartBubbles 2)͕ޕ͏͗Ψϱϧ΢ϱ͹࣎ͶϨΠϩν΢ϞͲৼധ਼ΝනࣖͤΖ HeartLight 3)ϚνϱΝԣͪ࣎͢Ͷৼധ਼Νૻ৶ͤΖ HeartButton ͹ࢀझྪΝࢾ͢ͱΊΖɽ ࣰݩͺ 7 ૌ 14 ໌Ͷ 69 ೖؔ࢘༽͢ͱ΍Δ͏ɼͨ͹״૟ΝΠϱίʖφͪ͢ɽ ݃Վ:ؽ೵ڠ௪ ʀৼധ਼Νૻ৶ͤΖ͞ͳͺ״৚Ώชຼ೟ࣟͶༀཱིͬɼֺ͢͠͹໚Ͳ΍ॊཔ͹ΠϕϨίʖε ϥϱΓΕ΍৏յͮͱ͏Ζͳ͏͑υʖν͗ಚΔΗͪɽ ʀৼധ਼ͶΓͮͱϏʖφψʖ͗ʹ͞ͲՁΝ͢ͱ͏Ζ͹͖͗ਬ଎Ͳͪ͘ɽ ʀ޹͘͵ৱ΄෼Ώ෼ࣆͶͯ͏ͱ࿫ͤ࣎Ͷৼധ਼͗৏ত͢ͱ͏ͪɽ ʀΉͪࣙ෾ࣙਐ͹ৼധয়ڱΝஎΖ͞ͳͲࣙހ؏ࡱΏηφϪη͹ݬҾΝಝఈͤΖ͞ͳͶ΍ༀ ཱིͮͪɽ ʀύʖφοϡρφͺՊଔΏ਎ື͵༓ਕͳ͹ཤ༽͗๮Ή͢͏ɽ ݃Վ:֦ؽ೵พ ʀHeatrBubbles ͗࠹΍ֺ͚͢ɼϏʖφψʖ͹ৼ৚Νཀྵմ͢Ώͤ͏ͳ͏͑Πϱίʖφ݃Վɽ ʀHeartBubbles ͺ৯ͶΓΖනࣖ͵͹Ͳɼ਼࣊ͳർ΄ͱඏຽ͵ৼധรԿ͗෾͖ΕͶ͚͏ɽ ʀHeartButton ͗࠹΍໎ྐͲմए͹༲ҝ੓͍͗ͮͪͳ͏͑Πϱίʖφ݃Վ͍͗Εɼ෾ੵ͹ ݃ՎͲ΍ଲ࿫ं͹য়ସͶଲͤΖқࣟ͹༙қ͵ଁՅ͗೟ΌΔΗͪɽ ʀHeartButton ͺࣙਐ͗໎ࣖదͶৼധ਼Νૻ৶ͤΖͪΌɼͨ͹਼࣊͹қັ͗ଠ͹̐ؽ೵Γ Ε΍༙қٝͶ״ͣΔΗͪɽ ʀHertsLight ͺϏʖφψʖ͗ϟριʖζΝಣΞͲ͏Ζ࣎͹ৼധ਼ΝஎΖ͹Ͷༀཱིͮͪɽ
113. ࢂߡชݛ͹ sur vey Daniel Buschek, Alexander De Luca, and Florian Alt. 2015. There is More to Typing Than Speed: Expressive Mobile Touch Keyboards via Dynamic Font Personalisation. In Proceedings of the 17th International Conference on Human- &RPSXWHU,QWHUDFWLRQZLWK0RELOH'HYLFHVDQG6HUYLFHV 0RELOH+&,b . ACM, New York, NY, USA, 125Ȃ130. DOI: http://dx.doi.org/10.1145/2785830.2785844 ν΢ϒϱήͺΦϧʖིΏଐౕ͵ʹ͹ఈྖద͵གྷҾͶؖ͢ͱݜڂ͠Ηͱ͏Ζ͗ɼTapScript Νཤ༽͢ͱɼν΢ϒϱή࣎͹Ϥʖδʖ͹ߨಊΏชຼɼࢨ͹ഓ஖Ώυώ΢η͹޴͘Ώಊ͘͵ ʹ͖Δɼν΢ϒϱήͶݺ੓దಝ௅Ν࣍ͪͦΖघॽ͘͹Γ͑͵ϓΧϱφ͹ਫ਼੔Νߨ͵ͮͪɽ ν΢ϒηφͳͨ͹ν΢ϒϱήͶΓΕਫ਼੔͠ΗͪϓΧϱφ͹ૌ͹ಝఈིͺ 84.5%Ͳɼν΢ϒ ϱή࣎Ͷิͮͱ͏͖ͪ࠴ͮͱ͏͖ͪ͹ਜ਼մིͺ 94.8%ͫͮͪɽ͞ΗͲɼݺਕ͹ν΢ϒϱή ͹ಝ௅ͶΓΕਫ਼੔͠ΗͪϓΧϱφͶͺݺ੓ద͵ಝ௅͍͗Ζͳ೟ࣟ͠Ηͪɽ Franco Curmi, Maria Angela Ferrario, Jen Southern, and Jon Whittle. 2013. HeartLink: Open Broadcast of Live Biometric Data to Social Networks. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems &+,b . ACM, New York, NY, USA, 1749Ȃ1758. DOI: http://dx.doi.org/10.1145/2470654.2466231 ώ΢ΨϟφϨρέυʖνΝࣙਐ͹݊߃؇ཀྵΏφϪʖωϱή͹ͪΌͶཤ༽ͤΖҐ֐Ͷɼλʖ εϡϩϋρφϭʖέͶ͕͏ͱڠ༙ͤΖͳ͏͑Ն೵੓Ͷͯ͏ͱɼৼധ਼͵ʹ͹ώ΢ΨϟφϨ ρέυʖνΝϨΠϩν΢ϞͲफॄ͢ɼΨϱϧ΢ϱͲϔϫʖχΫϡηφͤΖ HeartLink Ν֋ ൅ͪ͢ɽ ਫ਼ରυʖν͹ࢻְԿͺυʖν͹఑ڛंͳࢻ௎ं͹ؖܐͶӪڻΝ༫͓ɼ ఑ڛंͺࢻ௎ ंͶۛͰ͏ͪ໪ત͹৚ๅ൅৶Νߨ͏ɼࢻ௎ंͺಋҲ͹αϝϣωτΡͶ଒͢ͱ͏Ζͳ͏͑қ ࣟ͗کΉͮͪɽώ΢ΨϟφϨρέυʖν͹ڠ༙ͺਕؔؖܐͶӪڻΝ༫͓Ζ͞ͳ͗Κ͖ͮͪ ͪΌɼ৿͢͏ϑζϋηϠυϩΏαϝϣωτΡ͹ߑ஛ͶనԢͲ͘ΖՆ೵੓͍͗Ζɼ Joan Morris DiMicco, Vidya Lakshmipathy, and Andrew Tresolini Fiore. 2002. Conductive Chat: Instant messaging with a skin conductivity channel. In Proceedings of Conference on Computer Supported Cooperative Work. Citeseer. Conductive Chat ͺϤʖδʖ͹รಊͤΖϨΠϩν΢Ϟ͹ൿේ͹ఽ಍ౕΝξ΢Πϫή΢ϱν ʖϓΥ΢ηͶૌΊࠒ΋΢ϱηνϱφϟριʖζϱή΢ϱνʖϓΥ΢ηͲ͍ΖɽτΫηφο ϡρφ͹ଲ࿫͹஦ͶϤʖδʖ͹ڷฅౕɼְ੩ౕΝ؜ΌΖ͞ͳͶΓͮͱ״৚ద͵αϱτϱς
114. Νึͮͱ͏Ζɽ ͞͹ݜڂ྘Үͺɼ ৚ॻద৚ๅ͗αϱϒϣʖνഖղ؂ڧͶ͕͜Ζཋٽͳқਦ͹ ڠ༙Ν͏͖Ͷ๝͖ͶͤΖ͖ΝཀྵմͤΖ͞ͳΝ໪దͳ͢ͱ͏Ζɽ Rana El Kaliouby and Peter Robinson. 2004. FAIM: Integrating Automated Facial Affect Analysis in Instant Messaging. In Proceedings of the 9th International Conference on –‡ŽŽ‹‰‡–•‡” –‡”ˆƒ…‡•ȋ  ǯͶͺȌ. ACM, New York, NY, USA, 244Ȃ246. DOI: http://dx.doi.org/10.1145/964442.964493 ఽ౹ద͵΢ϱηνϱφϟριʖζϱήϕϧρφϓΧʖϞͺɼනݳ͹कགྷ͵ܙࣞͳ͢ͱτΫ ηφϟριʖζͶғଚ͢ͱ͏Ζɽ FAIM ͺϨΠϩν΢ϞͲਕ͹اΝ෾ੵ͢ɼ ͨΗΝනݳͤΖ ״৚ద͵ΫϡϧένʖΝౌ৖ͦ͠Ζ͞ͳͲଲ࿫ΝکԿͤΖɽ͞͹࿨ชͲͺاΝ෾ੵ͢Πϕ ϨͶ౹߻ͤΖࡏ͹અܯ৏͹՟ୌͳͨ͹ଲॴͶͯ͏ͱफ़΄ͱ͏Ζɽا͹න৚ͺೖ৙ద͵αϝ ϣωίʖεϥϱͶ͕͏ͱ΍॑གྷ͵ༀׄΝՎͪ͢ͱ͏Ζɽ FAIM ͹ӪڻΝ਼஍Կ͢ɼ ΓΕྒྷ͏ ΍͹΃ͳրવ͢ͱ͏͚͞ͳ͗๮ΉΗΖɽ Ke-Chen Pong, Chi-An Wang, and Shuo Hsiu Hsu. 2014. GamIM: Affecting Chatting Behavior by Visualizing Atmosphere of Conversation. In  ǯͷͺš–‡†‡†„•–”ƒ…–•‘ —ƒ ƒ…–‘”•‹‘’—–‹‰›•–‡•ȋ ǯͷ4). ACM, New York, NY, USA, 2497Ȃ2502. DOI: http://dx.doi.org/10.1145/2559206.2581168 Ϡώ΢ϩυώ΢ηΝղͪ͢΢ϱηνϱφϟριʖζ͹ި׷Ͷ͕͏ͱɼτΫηφ͖Δ״৚ద ͵घ͖͗ΕΝଁکͤΖاช࣊͵ʹ͹ॊཔ͹శ෉෼ͺɼ್ਕ͹ଲ࿫ं͹ؔ͹ճ࿫͹ฉҕـΝ ࢻְԿͤΖ͞ͳ͗Ͳ͘͵͏ɽ GamIM ͺૻ৶͠ΗͪϟριʖζΝφϪʖωϱή͠Ηͪ෾ྪح ͶΓͮͱ෾ੵ͢ͱਜ਼ɼ ෝɼ ஦ཱིͶ෾ྪͨ͢͹״৚Ͷ߻Κͦͱ৯෉͘͹๒Νਫ਼੔͢ͱճ࿫͹ฉ ҕـΝࢻְԿͤΖɽ ๒ͺϟριʖζ͹बว͖Δ൅ਫ਼͢ɼ ͨ͹ޛժ໚৏๏͹୉ـ྘ҮͲࢯΉΖ ͪΌعଚ͹๒ͳ૮ޕࡠ༽ͤΖɽ͞͹Γ͑͵ΰʖϞదΠϕϫʖοͲ͍Ζ״৚͹๒͹࢔ཻͳ૮ ޕࡠ༽ͺɼ ϤʖδʖͶճ࿫஦Ͷ൅ਫ਼ͪ͢״৚͹ྖΝࢧ͏ड़ͦ͠ɼ ઞࡑదͶϤʖδʖ͹οϡρ φಊࡠͶӪڻΝٶ·͢ɼΓΕ੷ۅద͵ճ࿫ΝଇͤͳՀఈ͠ΗΖɽ 201611460 ኏ੋܔ৑ (ਕؔαʖη)
117. Learning to be a Depth Camera for Close-Range Human Capture and Interaction Sean Ryan Fanello Cem Keskin Shhram Izadi Pushmeet Kohli David Kim David Sweeney Antonio Criminisi Jamie Shotton Sing Bing Kang Tim Paek Microsoft Research iCub Facility - Institute Italiano di Tecnologia %ͷ8FCΧϝϥʹ੺֎ઢϥΠτΛ͚ͭػցֶशͰख΍ إͷೝࣝΛ͢Δ͜ͱͰ҆ՁͰߴੑೳͳ%ਂ౓ΧϝϥΛ ࡞੒ͨ͠ɻ
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118. Category-Specific Object Reconstruction from a Single Image Abhishek Kar∗ , Shubham Tulsiani∗ , Joao Carreira and Jitendra Malik ˜ University of California, Berkeley - Berkeley, CA 94720 ̍ຕͷը૾͔Β͍ࣸͬͯΔΦϒδΣΫτͷ̏࣌ݱঢ়ͷ ܗΛࣗಈੜ੒͢Δٕज़ɻػցֶशͰ͋ΔΦϒδΣΫτ ͷࣸਅΛ͋ΒΏΔ֯౓͔ΒͱΓɺͦͷσʔληοτΛ ݩʹ̎࣍ݩը૾͔Β̏࣍ݩϞσϧΛੜ੒͢Δɻ
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119. Real Time Hand Pose Estimation using Depth Sensors Cem Keskin, Furkan Kırac¸, Yunus Emre Kara and Lale Akarun Bogazic¸i University ˘ Computer Engineering Department, 34342, Istanbul, Turkey
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120. Multiview Face Capture using Polarized Spherical Gradient Illumination Abhijeet Ghosh Graham Fyffe Borom Tunwattanapong Jay Busch Xueming Yu Paul Debevec USC Institute for Creative Technologies ภޫٿ໘ޯ഑র໌Λ༻͍ͯෳ਺ͷࢹ఺͔Βղੳ͢Δ͜ ͱͰߴղ૾౓͔ͭڸ໘ޫ౓৘ใΛ࣋ͬͨإͷزԿֶత ܗঢ়Λऔಘ͢ΔɻΧϝϥͱޫݯͷ྆ํʹ௿ίετͷੑ తภޫࢠΛ࢖༻ͯͨ͠ࢹ఺Λऔಘ͢Δɻ 201813567 দӬঘ೭ #FTMA18 (ਓؒ)
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129. ؖ࿊ݜڂ Flexible Registration of Human Motion Data with Parameterized Motion Models - ਕؔ͹ࣙಊϠʖεϥϱౌ࿧͹ͪΌ͹ްིద͵Ϡυϩϗʖη͹ΠϕϫʖοΝ఑ࣖ - ิߨɼૺߨɼζϡϱϕ͵ʹ͹ϠʖεϥϱͲࣰݩ - ߶඾࣯͹ϠʖεϥϱυʖνΝಚΖͪΌͶɼ υʖνϗʖη͹ྭΝൔࣙಊదͶࣆ઴ౌ࿧͢͵ ͜Ηͻ͵Δ͵͏ˢ͖͖࣎ؔ͗Ζ ¾ Ն೵͵մ݀ࡨʁυʖνϗʖη಼͹ঙ਼͹ྭΝൔࣙಊϕϫιηͲ༩Όౌ࿧͢ͱ͖Δɼ Ϡυϩϗʖη͹ౌ࿧ϟλρχΝ࢘༽͢ͱϏϧϟʖνԿ͠ΗͪϠυϩΝஊ֌దͶߍ ৿ͤΖ͞ͳ - গཔదͶͺΓΕଡ͚͹අݩंɼ ߶ྺं͖Δࢢʹ΍͵ʹ͹ΓΕଡ͚͹ಊ͘͹ώϨΦʖεϥ ϱΝφϪʖωϱήυʖνϗʖηͶ௧Յ - Ϡʖεϥϱ߻੔ɼѻक़ɼαʖυΡϱήɼ೟ࣟɼ͕Γ;ϓΡϩνϨϱήͶ͕͜ΖΠϕϨί ʖεϥϱ͹௒ࠬΝࠕޛΏΖ Style Translation for Human Motion - αϱτϱςΝฯଚ͢͵͗Δɼ ਕؔ͹ಊ͘Ν͠Ή͡Ή͵ην΢ϩͶો૥͚ร׷Ͳ͘ΖΓ͑ ͶͤΖ͞ͳ ¾ ๴୉͵υʖνιρφΝߑ஛ͤΖෝ୴͗୉͘͏໲ୌΝմ݀Ͳ͘Ζ - ؖઇΝಢཱི͢ͱϠυϩԿͪ͢ ¾ ೘ྙͳड़ྙ͹ࠐ֪͗ڠ௪Ͳ͵͚ͱͺ͵Δ͵͏ ¾ Shin et al ͹ retargeting Πϕϫʖο͹Γ͑͵घ๑ͳૌΊ߻ΚͦΗͻմ݀ͤΖՆ೵੓ ͍͗Ζ ¾ ੏ޜཀྵ࿨Ώͨ͹ଠ͹ؖ࿊෾໼͹෾ੵٗढ़ΝԢ༽ͤΖ͞ͳͲɼਕؔ͹ಊ͘Ͷ͕͜Ζ ην΢ϩ͹ຌ࣯Ͷͯ͏ͱ͹৿͢͏ಐࡱΝݡͯͪ͜͏ Generalizing Motion Edits with Gaussian Processes - ָ͞सεητϞ͹ҲൢԿϕϫϏτΡΝ࢘༽͢ͱɼ ୻͏φϪʖωϱήεʖίϱηͲࡠ੔͠ ΗͪรߍΝϓϩΠωϟʖεϥϱͶఽ೽ͤΖεητϞ - গཔదͶͺɼ ͞͹ٗढ़͗ϓρφϕϧϱφ͵ʹ͹؂ڧ੏༁ΝॴཀྵͲ͘Ζ͖ʹ͖͑Ν୵ڂ͢ ͱɼޛॴཀྵ͗෈གྷͶ͵ΖΓ͑Ͷͪ͢͏ Modeling Spatial and Temporal Variation in Motion Data - ӣಊυʖν͹รԿΝϠυϩԿ͢ɼ߻੔ͤΖͪΌ͹৿͢͏๏๑͹఑ࣖ ¾ ΨϨζψϩ͹ิߨγ΢έϩ͹Κ͖ͥ͵ࠫΝਫ਼੔ͤΖ͞ͳ͗Ͳ͘ΖώϨΦʖεϥϱ Ϡυϩɼड़ྙಊࡠ͹ࣙષ͠Ν୉෱ͶրવͤΖՆ೵੓͍͗Ζ - ॑གྷ͵͹ͺɼ ঙྖ͹υʖνͲཱࣙదͶϠυϩԿ͢ͱώϨΦʖεϥϱΝ߻੔ͤΖਜ਼ࣞ͵๏ ๑
130. - ό΢θΝ௧ՅͤΖ๏๑ͺචͥ͢΍ࣙષͶ͵Δ͵͏ - ਼஍దͶͺҩͮͱ΍ݡͪ໪ͺΚ͖ͥͶҡ͵Ζ͖ͫͫ͜Δրવ͹༪ஏ͍Ε - future workˢϠʖεϥϱυʖνΝѻक़ͤΖͪΌͶώϨΦʖεϥϱ͹Π΢υΠΝ࢘༽ͤ Ζ͞ͳ Efficient Content-Based Retrieval of Motion Capture Data - ϛʖθ͹ࢨఈ͠ΗͪϚυΡϛ΢ϱφؔ͹شՁָదؖܐΝىफ़ͤΖ༹ʓ͵झྪ͹ఈ੓ద ಝ௅Ν಍೘͢ɼ ͞ΗΔ͹ಝ௅͗ϠʖεϥϱΫϡϕοϡυʖνηφϨʖϞ͹࣎ؔ෾ׄΝʹ ͹Γ͑Ͷ༢಍ͤΖ͖Νࣖͤ - έΦϨεψϨΨ͹ 1 ͯ͹୉͘͵఼ܿͺɼ֦έΦϨͶଲ͢ͱɼϤʖδͺɼ߶඾࣯͹ݗࡩ݃ ՎΝಚΖͪΌͶన઀͵ಝ௅Νમ୔͢͵͜Ηͻ͵Δ͵͏͞ͳ - େනద͵ྭୌ͹Ϡʖεϥϱ͖Δනݳద͵شՁָదಝ௅ΝࣙಊదͶಝఈͤΖͪΌͶɼ ౹ܯ ద๏๑Νࡀ༽ͤΖ༩ఈ
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     ͜ͷϞσϧ͔Βɼ੺৭ߏ଄৭Λग़ͨ͢Ίʹ͸ɼίΞγΣϧߏ଄ʹ͓͍ͯɼONͷۭؾΛ DPSFͱ͠ɼONͷγΣϧΛTJMJDBͰܗ੒͢Δͷ͕͍͍ͱσβΠϯͨ͠ɽ Ͳ͏΍ͬͯ༗ޮͩͱݕূͨ͠ʁ ϞσϧͰܭࢉͨ͠਺஋ͱɼ࣮ࡍͷϚςϦΞϧͷ਺஋Λൺֱ ٞ࿦͸͋Δʁ ੺৭ߏ଄৭͸σβΠϯ௨Γʹ࡞ͬͨΒຊ౰ʹ࣮ݱ͢Δͷʁ
     Ϟσϧͱσʔλͷࠩ෼͸ͲΕ͘Β͍͍͍΋ͷͳͷʁ ࣍ʹಡΉ΂͖࿦จ͸ʁ %FTJHO
     BOE
     TJNVMBUJPO
     PG
     PNOJEJSFDUJPOBM
     SFqFDUJWF
     DPMPS
     pMUFST
     CBTFE
     PO
     NFUBMEJFMFDUSJDNFUBM
     TUSVDUVSF
     
     Absence of Red Structural Color in Photonics Glasses, Bird Feathers and Certain Beetles (arXiv 2014, Magkiriadou, S., Park, J. G., Kim, Y. S., & Manoharan, V. N. )
137. NFUBMEJFMFDUSJDNFUBMͱ͍͏αϯυ΢Οονߏ଄Λ༻͍ͨ֨ࢠঢ়ͷ൓ࣹܕ $PMPS
     'JMUFSͷ࡞੒
     ද໘ϓϥζϞϯڞ໐ͷݪཧʹج͍ͮͯ൓ࣹ͍ͯ͠Δ ͲΜͳ΋ͷʁ ઌߦݚڀͱൺ΂ͯͲ͕͍͜͢͝ʁ ޫͷೖࣹ֯ʹରͯ͠ɼ൓ࣹ͢Δ৭ͷมԽ͕΋ͷ͘͢͝খ͍͞ ٕज़΍ख๏ͷΩϞ͸Ͳ͜ʁ Ξϧϛχ΢ϜͱγϦΧ ೋࢎԽέΠૉ ͷαϯυ΢Οονߏ଄ ʹΑΔ൓ࣹϑΟϧλʔͷੜ੒ Ͳ͏΍ͬͯ༗ޮͩͱݕূͨ͠ʁ ࣮ࡍʹ࡞੒ͨ͠:FMMPX
     .BHFOUB
     $ZBOͷΧϥʔϑΟϧλʔʹ ೖࣹ֯Λม͑ͳ͕ΒޫΛ౰ͯɼݟ͑Δ৭ͷมԽΛ͔֬Ίͨ ٞ࿦͸͋Δʁ ଞͷ৭ͷΧϥʔϑΟϧλʔ͸ʁ ࣍ʹಡΉ΂͖࿦จ͸ʁ 0QUJNJ[BUJPO
     PG
     TIBSQ
     BOE
     WJFXJOHBOHMFJOEFQFOEFOU
     TUSVDUVSBM
     DPMPS Design and simulation of omnidirectional reflective color filters based on metal-dielectricmetal structure (Optics express 2014, Yang, Chenying and Shen, Weidong and Zhang, Yueguang and Peng, Hao and Zhang, Xing and Liu, Xu)
138. ڱ͍೾௕ҬͰ͔ͭݟΔ֯౓ʹґଘ͠ͳ͍ߏ଄৭Λग़ͨ͢Ίͷ ߏ଄ͷ࠷దԽΛϞσϧΛ૊ΜͰߦͬͨ ͲΜͳ΋ͷʁ ઌߦݚڀͱൺ΂ͯͲ͕͍͜͢͝ʁ ೾௕ҬΛڱ͘͢Δ͜ͱͱݟΔ֯౓ʹґଘ͠ͳ͍͜ͱΛཱ྆͢Δ͜ͱ͸೉͔ͬ͠ ͕ͨɼຊ࿦จͰ͸༷ʑͳߏ଄Λݕ౼͠࠷దԽΛߦͬͨ݁Ռɼཱ྆Λ࣮ݱͨ͠
     ೖࣹ֯ʹରͯ͠΋ ٕज़΍ख๏ͷΩϞ͸Ͳ͜ʁ τʔϥεܕͷϦϯάঢ়ͷߏ଄ʹͨ͜͠ͱ Ͳ͏΍ͬͯ༗ޮͩͱݕূͨ͠ʁ ੑೳࢦ਺ΛࣗΒఆٛ͠ɼͦͷ޲্ʹద͏Α͏ͳϞσϧ࡞੒
     ٴͼϞσϧ্ͷܭࢉ஋ͰɼTDBUUFSJOH
     SFTQPOTF͕طଘख๏Α Γվળ͍ͯ͠Δ͜ͱͷূ໌ ٞ࿦͸͋Δʁ ۭؾΛഔ࣭ͱͯ͠ܭࢉ͍ͯ͠Δ͕ɼۭؾҎ֎ͷഔ࣭ FY
     QPMZNFS
     HMBTT ͷ৔߹ʹݟΔ֯౓΁ͷ໌͕֬͞ݮΔ͔΋ ࣍ʹಡΉ΂͖࿦จ͸ʁ "OHVMBS
     BOE
     QPMBSJ[BUJPOJOEFQFOEFOU
     TUSVDUVSBM
     DPMPSTCBTFE
     PO
     %
     QIPUPOJD
     DSZTUBMT Optimization of sharp and viewing-angle-independent structural color (Optics express 2015, Hsu, Chia Wei and Miller, Owen D and Johnson, Steven G and Solja{\v{c}}i{\'c}, Marin)
139. ୯෼ࢄQPMZTUZSFOFٿͱDVUUMFpTI ί΢ΠΧ
     JOLͷཻࢠΛࣗݾ૊৫Խͤ͞ ͨΞϞϧϑΝεϑΥτχοΫߏ଄ΛఴՃࡎͱͯ͠࢖͑ΔΑ͏ʹ͠ɼඇ೒ ৭ͷ৭ͷ͸͖ͬΓͨ͠ߏ଄৭Λ࣮ݱͨ͠ ͲΜͳ΋ͷʁ ઌߦݚڀͱൺ΂ͯͲ͕͍͜͢͝ʁ DVUUMFpTI
     JOLͱQPMZTUZSFOFΛࠞͥɼQPMZTUZSFOFͷ௚ܘΛมԽͤ͞ Δ͜ͱͰ৭Λม͑ΒΕΔΑ͏ʹͨ͠
     ·ͨɼDVUUMFpTI
     JOLͱQPMZTUZSFOFͷ഑߹཰ʹΑͬͯ΋৭͸มԽ͢Δ ٕज़΍ख๏ͷΩϞ͸Ͳ͜ʁ DVUUMFpTI
     JOLͱQPMZTUZSFOFͷ഑߹ Ͳ͏΍ͬͯ༗ޮͩͱݕূͨ͠ʁ ࣮ࡍʹ࡞੒ͨ͠΋ͷͷ৭΍൓ࣹ཰ͷܭଌ ٞ࿦͸͋Δʁ ࣍ʹಡΉ΂͖࿦จ͸ʁ "OHVMBS
     BOE
     QPMBSJ[BUJPOJOEFQFOEFOU
     TUSVDUVSBM
     DPMPSTCBTFE
     PO
     %
     QIPUPOJD
     DSZTUBMT Using Cuttlefi sh Ink as an Additive to Produce Non-iridescent Structural Colors of High Color Visibility (Advanced Materials 2015, Zhang, Yafeng and Dong, Biqin and Chen, Ang and Liu, Xiaohan and Shi, Lei and Zi, Jian)
140. ེԽѥԖ ;O4 ͱࢎԽγϦίϯ 4J0 ͷࠞ߹ࡐྉͷφϊٿΛύ΢μʔԽ ͠ɼDBSCPOͱͱ΋ʹম݁ͨ͠ࡐྉΛ༻͍Δ͜ͱͰɼ֯౓ґଘੑ͕௿ ͘ɼ࠼౓͸ߴ͘ɼ҆ఆੑ΋ߴ͍ߏ଄৭Λ࡞੒ͨ͠ ͲΜͳ΋ͷʁ ઌߦݚڀͱൺ΂ͯͲ͕͍͜͢͝ʁ ;O4ͱ4J0ͷίΞγΣϧߏ଄Λੜ੒͠ɼγΣϧͷް͞΋Լลʹͨ͠
     ·ͨDBSCPOͱͱ΋ʹম݁ͯ͠ύ΢μʔԽ͍ͯ͠Δ ٕज़΍ख๏ͷΩϞ͸Ͳ͜ʁ ;O4ͱ4J0ͷίΞγΣϧߏ଄ͷੜ੒ɾDBSCPOΛ༻͍ͨম݁
     ίΞγΣϧͷγΣϧͷް͞Λม͑ΔͱDBSCPOম݁ޙͷ৭΋มΘΔ
     ·ͨম݁Թ౓Ͱ΋৭͕গ͠มԽ͢Δ Ͳ͏΍ͬͯ༗ޮͩͱݕূͨ͠ʁ ࣮ࡍʹ࡞੒͠ɼ৭΍൓ࣹ཰Λܭଌͨ͠ ٞ࿦͸͋Δʁ ৭͸ͲΕ͘Β͍ͷύλʔϯग़ͤΔͷ͔ ࣍ʹಡΉ΂͖࿦จ͸ʁ Structural coloration pigments based on carbon modified ZnS@ SiO2 nanospheres with low-angle dependence, high color saturation, and enhanced stability (ACS applied materials & interfaces 2016, Wang, Fen and Zhang, Xin and Lin, Ying and Wang, Lei and Zhu, Jianfeng)
141. ௒ૄਫੑͷߏ଄৭ΛɼεϓϨʔίʔςΟϯάͰ࣮૷ͨ͠ ͲΜͳ΋ͷʁ ઌߦݚڀͱൺ΂ͯͲ͕͍͜͢͝ʁ طଘͷߏ଄৭͸ೞΕͨΓ͢Δͱͦͷ઱΍͔͞Λࣦ͍͕ͪ
     ຊݚڀͰ͸ɼεϓϨʔίʔςΟϯάʹΑͬͯੜ੒ͨ͠௒ૄਫੑͷಛੑʹΑΓɼ֯౓ґଘΛ͠ͳ͍ ߏ଄৭ϑΟϧϜͷߴ଎ͳ੡଄Λ࣮ݱͨ͠ ٕज़΍ख๏ͷΩϞ͸Ͳ͜ʁ 4J0ϑΟϧϜʹ௒ૄਫੑͷ1%.4ΛεϓϨʔίʔςΟϯά
     γϦΧͷαΠζΛม͑Δ͜ͱͰ৭Λม͑Δ͜ͱ͕Ͱ͖Δ Ͳ͏΍ͬͯ༗ޮͩͱݕূͨ͠ʁ ࣮ࡍʹ࡞੒͠ɼਫʹ͚ͭΔͳͲͯ͠ੑೳΛ͔֬Ίͨ ٞ࿦͸͋Δʁ ࣍ʹಡΉ΂͖࿦จ͸ʁ 4FMFDUJWF
     $PMPSBUJPO
     PG
     .FMBOJO
     /BOPTQIFSFT
     UISPVHI
     3FTPOBOU
     .JF
     4DBUUFSJOH Rapid fabrication of angle-independent structurally colored films with a superhydrophobic property (Dyes and Pigments 2016, Wang, Fen and Zhang, Xin and Zhang, Lei and Cao, Min and Lin, Ying and Zhu, Jianfeng)
142. ਓؒͷ൅ͷໟ͸؀ڥޫͷ༷ࢠʹΑͬͯ৭͕ҧͬͨΑ͏ʹݟ͑Δɽ͜Ε͸ϝ ϥχϯͷӨڹ͕͋ΔΘ͚͕ͩɼ͜ͷݱ৅Λར༻ͨ͠ਓ޻ߏ଄৭Λ࡞੒ͨ͠
     ϝϥχϯͷ୅ΘΓʹɼQPMZEPQBNJOFΛ༻͍ɼͦͷαΠζ΍ີू౓Λύϥ ϝʔλͱͯ͠؀ڥޫԼͱεϙοτϥΠτԼͰݟ͑ํ͕ҟͳΔΑ͏ͳ෺࣭Λ ࡞੒ͨ͠ɽ ͲΜͳ΋ͷʁ ઌߦݚڀͱൺ΂ͯͲ͕͍͜͢͝ʁ ਓؒͷ൅ͷໟͷݱ৅ΛԠ༻ͨ͠఺ ٕज़΍ख๏ͷΩϞ͸Ͳ͜ʁ φϊٿମঢ়ͷQPMZEPQBNJOFͷϛʔࢄཚͷڞ໐Ͱ৭Λ൓ࣹ͢Δ
     φϊٿମঢ়ͷQPMZEPQBNJOFΛϥϯμϜ෼ࢄͰɼαΠζͱີू౓Λม͑Δ͜ͱͰ৭Λม͑Δ͜ ͱ࣮ݱͨ͠఺
     ·ͨQPMZEPQBNJOFΛೖΕΔ৔ॴΛਫ΍1&(%"ͷ̎ύλʔϯͰࢼ͍ͯ͠Δ Ͳ͏΍ͬͯ༗ޮͩͱݕূͨ͠ʁ QPMZEPQBNJOFͷ௚ܘ΍ີू౓Λม͑ͯɼ࣮ࡍʹޫΛ౰ͯͯ ৭ͷมԽΛ͔֬Ίͨ ٞ࿦͸͋Δʁ ؀ڥޫͱڧ͍ޫͷҧ͍ͬͯͲΕ͘Β͍γϏΞͳͷ͔ ࣍ʹಡΉ΂͖࿦จ͸ʁ 1IPUPOJD
     HMBTT
     GPS
     IJHI
     DPOUSBTU
     TUSVDUVSBM
     DPMPS Selective Coloration of Melanin Nanospheres through Resonant Mie Scattering (Advanced Materials 2017, Cho, Soojeong and Shim, Tae Soup and Kim, Ju Hyeon and Kim, Dong-Hyun and Kim, Shin-Hyun)
143. 1IPUPOJDT
     (MBTTͷߏ଄ͷ൓ࣹ཰ͷબ୒ੑ͸ɼٿঢ়ͷγΣϧܕͷ༠ి཰෼෍ͷϑʔϦΤม׵ͷ ܗঢ়ʹؔ܎͍ͯ͠Δɽ
     ϑΥτχΫεΨϥεΛ༻͍ͯɼద੾ʹύʔςΟΫϧͷδΦϝτϦΛબΜͰ૊Έ߹ΘͤΔ͜ͱ Ͱ૬৐తͳޮՌ͕ಘΒΕΔ
     DPSFTIFMMύʔςΟΫϧ͕ɼ࠼౓ͷߴ͍ϑΥτχΫεΨϥεͷ൓ࣹεϖΫτϧΛಘΔͨΊʹͲ ͷΑ͏ʹ࢖ΘΕΔ͔Λࣔͨ͠
     DPSFTIFMMͷ۶ં཰ͷҧ͍΍ɼCBDLHSPVOEͷ۶ં཰ͷҧ͍ͳͲʹΑͬͯมԽ͢Δɽ ͲΜͳ΋ͷʁ ઌߦݚڀͱൺ΂ͯͲ͕͍͜͢͝ʁ 1IPUPOJD
     (MBTTߏ଄ʹ͓͍ͯɼ൓ࣹ཰ͷબ୒ੑ͕ٿঢ়ͷγΣϧܕͷ ༠ి཰෼෍ͷϑʔϦΤม׵ͷܗঢ়ʹؔ܎͍ͯ͠Δ͜ͱΛࣔͨ͠఺ ٕज़΍ख๏ͷΩϞ͸Ͳ͜ʁ DPSF΍TIFMMͷ૊Έ߹Θͤͷ࢓ํͰBNQMJUVEF͕มԽ͢Δ Ͳ͏΍ͬͯ༗ޮͩͱݕূͨ͠ʁ ٞ࿦͸͋Δʁ ࣍ʹಡΉ΂͖࿦จ͸ʁ Photonic glass for high contrast structural color (arXiv 2018, Shang, Guoliang and Maiwald, Lukas and Renner, Hagen and Jalas, Dirk and Dosta, Maksym and Heinrich, Stefan and Petrov, Alexander Yu and Eich, Manfred)
144. ϑΣϜτඵϨʔβʔΛ༻͍ͨNJDSPOBOPߏ଄Ճ޻ͷ3FWJFX࿦จ
     ֤ߏ଄ΛՃ޻͢ΔࡍͷϨʔβʔͷύϥϝʔλͳͲ͕ɼ࣮ݧΛ௨ ͯ͠ಘΒΕͨσʔλͱͯ͠ৄड़͞Ε͍ͯΔ
     
     φϊߏ଄
     
     ϥϯμϜφϊߏ଄ɿχοέϧද໘΁ͷՃ޻ͳͲ
     
     पظతφϊߏ଄ɿνλϯද໘΁ͷՃ޻ͳͲ
     
     φϊͷಛ௃Λ࣋ͬͨϚΠΫϩߏ଄
     
     ೾ଧͭߔ΍NJDSP3JQQMFɿνλϯද໘΁ͷՃ޻ͳͲ
     
     ԁபߏ଄ɿ
     
     ͦͷଞߏ଄ɿϗʔϧߏ଄ ͲΜͳ΋ͷʁ ࣍ʹಡΉ΂͖࿦จ͸ʁ #JP*OTQJSFE
     'VODUJPOBM
     4VSGBDFT
     #BTFE
     PO
     -BTFS *OEVDFE
     1FSJPEJD
     4VSGBDF
     4USVDUVSFT Fabrication of micro/nano structures on metals by femtosecond laser micromachining (Micromachines 2014: Ahmmed, KM and Grambow, Colin and Kietzig, Anne-Marie) ઌߦݚڀͱൺ΂ͯͲ͕͍͜͢͝ʁ ٕज़΍ख๏ͷΩϞ͸Ͳ͜ʁ Ͳ͏΍ͬͯ༗ޮͩͱݕূͨ͠ʁ ٞ࿦͸͋Δʁ
145. ੜ෺ʹ*OTQJSFE͞ΕͨϨʔβʔ༠ಋʹΑΔपظతද໘ߏ଄ʹ͍ͭ ͯͷ3FWJFX࿦จ
     
     ࣪५ੑ
     
     ੜ෺ͷதʹ͸ߏ଄ͱͯ͠Ꭲਫੑͷߴ͍ߏ଄Λ࣋ͭ΋ͷ͕͋Δ
     
     ௒ૄਫੑͷද໘Ճ޻Λਓ޻తʹϨʔβʔՃ޻Ͱ࣮ݱ
     
     ൓ࣹ
     
     શવ൓ࣹΛ͠ͳ͍ද໘ߏ଄Λ࣋ͭੜ෺͕͍Δ
     
     ϞϧϑΥ௏΍λϚϜγͷΑ͏ʹߏ଄৭Λ࣋ͭੜ෺΋͍Δ
     
     ൓ࣹ཰ͷ௿͍ߏ଄Λਓ޻తʹੜ੒ͨ͠
     
     ͲΜͳ΋ͷʁ ࣍ʹಡΉ΂͖࿦จ͸ʁ #JP*OTQJSFE
     'VODUJPOBM
     4VSGBDFT
     #BTFE
     PO
     -BTFS *OEVDFE
     1FSJPEJD
     4VSGBDF
     4USVDUVSFT Bio-inspired functional surfaces based on laser-induced periodic surface structures (Materials 2016: M{\"u}ller, Frank A and Kunz, Clemens and Gr{\"a}f, Stephan) ઌߦݚڀͱൺ΂ͯͲ͕͍͜͢͝ʁ ٕज़΍ख๏ͷΩϞ͸Ͳ͜ʁ Ͳ͏΍ͬͯ༗ޮͩͱݕূͨ͠ʁ ٞ࿦͸͋Δʁ
146. ֯౓ґଘͷपظతͳද໘ߏ଄Λ૊Έ߹ΘͤͯɼޫΛ͋ͯΔํ ޲ʹԠͯ͡ݟ͑Δ಺༰͕มΘΔΑ͏ͳද໘Ճ޻Λ࣮ݱͨ͠ ͲΜͳ΋ͷʁ ઌߦݚڀͱൺ΂ͯͲ͕͍͜͢͝ʁ ଟํ޲͔ΒޫΛরࣹͯ͠΋ಉ͡Α͏ʹޫΔΑ͏ͳՃ޻ํ๏ ٕज़΍ख๏ͷΩϞ͸Ͳ͜ʁ ७ਮͳSJQQMFΛ࡞ͬͯߏ଄৭Λग़ͤΔ͜ͱ͸Θ͔͍ͬͯͨ
     ͜ͷSJQQMFΛ௚ߦͤͯ͞Ճ޻ͤͨ࣌͞ʹɼ̎ಛ௃Λอ࣋͢Δ Α͏ͳՃ޻Λͨ͠ͷ͕ΩϞ Ͳ͏΍ͬͯ༗ޮͩͱݕূͨ͠ʁ ࣮ࡍʹ࡞੒͠ɼ̎ํ޲͔ΒޫΛ౰ͯͨ݁ՌΛࡱ૾ͨ͠ ٞ࿦͸͋Δʁ ന৭Ҏ֎ͷޫΛೖΕͨΓ͢ΔͱͲ͏ͳΔͷ͔
     ·ͨํ޲ʹରͯ͠ͲΕ΄Ͳϩόετͳͷ͔ ࣍ʹಡΉ΂͖࿦จ͸ʁ %JSFDU
     WJTVBMJ[BUJPO
     PG
     UIF
     DPNQMFUF
     FWPMVUJPO
     PG
     GFNUPTFDPOE
     MBTFSJOEVDFE
     TVSGBDF
     TUSVDUVSBM
     EZOBNJDT
     PG
     NFUBMT Selective appearance of several laser-induced periodic surface structure patterns on a metal surface using structural colors produced by femtosecond laser pulses (Applied Surface Science 2012, Yao, Jianwu and Zhang, Chengyun and Liu, Haiying and Dai, Qiaofeng and Wu, Lijun and Lan, Sheng and Gopal, Achanta Venu and Trofimov, Vyacheslav A and Lysak, Tatiana M)
147. 'MFY4UZMVT
     -FWFSBHJOH
     #FOE
     *OQVU
     GPS
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     *OUFSBDUJPO
      
         
         
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     VXR^V' m¢ 5D[a}ŒD˜?DcŽ™1ADK.C B=>-ND0E—0LB-' yCgP–3yCf™VXR^V1b¡~KMžt 0A.0E„œ6O>-B-' žtˆD„œ ”r€C&b¡~VXR^V@f™VXR^VD š ?‘8†oPB:L9;' p‹7;Ÿ›C/->&b¡~VXR^VKMf™V XR^VDš1‰hCB:LO;'  
     
148. Unsupervised Image-to-Image Translation Networks Ming-Yu Liu Thomas Breuel Jan Kautz 
 ڭࢣͳ͠JNBHFUPJNBHFม׵ϑϨʔϜϫʔΫΛఏҊ͢Δ
     طଘͷڝ߹͢Δख๏ͱൺֱ͠
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     201813558 ஑ాҏ৫ #1 (ਓؒίʔε) ͲΜͳ΋ͷʁ Ͳ͏΍ͬͯ༗ޮͩͱݕূͨ͠ʁ ઌߦݚڀͱൺ΂ͯͲ͕͍͜͢͝ʁ ٞ࿦͸͋Δʁ ٕज़΍ख๏ͷΩϞ͸Ͳ͜ʁ ࣍ʹಡΉ΂͖࿦จ͸ʁ
149. ؔ࿈ݚڀ ɾAttribute2Image: Conditional Image Generation from Visual Attributes (Xinchen Yan, Jimei Yang, Kihyuk Sohn, Honglak Lee)
     
     
     
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     ɾConditional Image Generation with PixelCNN Decoders (Aaron van den Oord, Nal Kalchbrenner, Oriol Vinyals, Lasse Espeholt, Alex Graves, Koray Kavukcuoglu)
     
     
     
     1JYFM$//ΞʔΩςΫνϟʹجͮ͘৽͍͠ը૾ີ౓ϞσϧΛ༻͍ͯ৚݅෇͖ը૾ੜ੒ΛఏҊ͢Δɽઆ໌ϥϕϧ΍λ άɼ·ͨ͸ଞͷωοτϫʔΫʹΑͬͯ࡞੒͞Εͨ೚ҙͷϕΫτϧ্Ͱ৚݅෇͚͢Δ͜ͱ͕Ͱ͖Δɽ·ͨɼ৚݅෇͖ 1JYFM$//͕ը૾"VUP&ODPEFSͷڧྗͳσίʔμͱͯ͠ಇ͘͜ͱΛࣔ͢ɽఏҊͨ͠Ϟσϧ͸ɼ1JYFM$//ͷ࠷ߴਫ४ͷ ੑೳͱҰக͢ΔΑ͏ʹର਺໬౓Λվળ͠ɼܭࢉྔΛେ෯ʹ࡟ݮͨ͠ɽ
     ɾUnsupervised representation learning with deep convolutional generative adversarial networks (Alec Radford, Luke Metz, Soumith Chintala)
     
     
     
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     201813558 ஑ాҏ৫ #1 (ਓؒίʔε)
150. ɾCoupled Generative Adversarial Networks (Ming-Yu Liu, Oncel Tuzel)
     
     
     
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     ɾPhoto-Realistic Single Image Super-Resolution Using a Generative Adversarial Network (Christian Ledig, Lucas Theis, Ferenc Huszar, Jose Caballero, Andrew Cunningham, Alejandro Acosta, Andrew Aitken, Alykhan Tejani, Johannes Totz, Zehan Wang, Wenzhe Shi)
     
     
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     201813558 ஑ాҏ৫ #1 (ਓؒίʔε)
151. Silicone Devices: A Scalable DIY Approach for Fabricating Self-Contained Multi-Layered Soft Circuits using Microfluidics Steven Nagels1* , Raf Ramakers2* , Kris Luyten3 , Wim Deferme1 ͲΜͳ΋ͷʁ
     γϦίϯͱΨϦ΢ϜΛ࢖ͬͨ΢ΣΞϥϒϧσόΠεͷ࡞ ੒ͷͨΊͷϓϥοτϑΥʔϜͷ࡞੒ɺධՁΛߦͬͨɻ ઌߦݚڀͱൺ΂ͯͲ͕͍͜͢͝ʁ
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152. PrintScreen: Fabricating Highly Customizable Thin-film Touch-Displays TFELΛ࢖ͬͯҹ࡮͢Δ͜ͱʹΑͬͯɺ༷ʑͳ΋ͷͷΛޫΔσΟεϓϨΠʹ͢Δ͝ͱ͕Ͱ͖Δɻ Instant Inkjet Circuits: Lab-based Inkjet Printing to Support Rapid Prototyping of UbiComp Devices ಋిੑΠϯΫΛ࢖ͬͯࢴͷ্ʹҹ࡮͢Δ͜ͱͰ؆୯ʹૣ͘ճ࿏ͷ࡞੒͕Ͱ͖Δɻ SkinMarks: Enabling Interactions on Body Landmarks Using Conformal Skin Electron ഽͷ্ʹ௚઀ϚʔΧʔΛ͚ͭΔ͜ͱʹΑͬͯɺϘλϯͱͯ͠ͷೖྗ͕Ͱ͖Δɻ Sketching in Circuits: Designing and building electronics on paper ಋిੑͷςʔϓΛ࢖͏͜ͱʹΑͬͯɺϊʔτͷ্Ͱ΋ిࢠճ࿏͕࡞ΕΔΑ͏ͳϓϥοτϑΥʔϜ ͷ࡞੒ɺධՁΛߦͬͨɻ iSkin: Stretchable On-Body Touch Sensors for Mobile Computing ഽͷ্ʹۂ͕Δ͜ͱ͕Ͱ͖ΔηϯαʔΛ͓͚Δɻ ͜ͷ͜ͱʹΑͬͯɺ༷ʑͳσόΠεʹೖྗΛ͢Δ͜ͱ͕Ͱ͖Δɻ 
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