Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
Great Barrier Reef Model Pipeline: 15th place
Search
Maxwell
February 16, 2022
Science
1
210
Great Barrier Reef Model Pipeline: 15th place
https://www.kaggle.com/c/tensorflow-great-barrier-reef
All I want to use was YOLO-X!
Maxwell
February 16, 2022
Tweet
Share
More Decks by Maxwell
See All by Maxwell
Causal Impact -paper summary-
hoxomaxwell
3
810
Lecture materials at the University of Tokyo School of Medicine
hoxomaxwell
1
140
Kaggle Hungry Geese
hoxomaxwell
1
110
HuBMAP 17th place model pipeline
hoxomaxwell
1
95
LT: Shallow Dive into Bayes Factor
hoxomaxwell
6
1.4k
Kaggle APTOS 2019 @ U-Tokyo Med
hoxomaxwell
1
420
Cornell Birdcall 36th place solution
hoxomaxwell
2
230
Kaggle Bengali.AI 6 th place solution
hoxomaxwell
4
8.5k
Google Colaboratory Shortcuts
hoxomaxwell
2
1k
Other Decks in Science
See All in Science
04_石井クンツ昌子_お茶の水女子大学理事_副学長_D_I社会実現へ向けて.pdf
sip3ristex
0
530
データマイニング - コミュニティ発見
trycycle
PRO
0
110
トラブルがあったコンペに学ぶデータ分析
tereka114
2
1.7k
機械学習 - 授業概要
trycycle
PRO
0
210
ガウス過程回帰とベイズ最適化
nearme_tech
PRO
1
470
眼科AIコンテスト2024_特別賞_6位Solution
pon0matsu
0
420
データベース10: 拡張実体関連モデル
trycycle
PRO
0
790
データベース12: 正規化(2/2) - データ従属性に基づく正規化
trycycle
PRO
0
770
モンテカルロDCF法による事業価値の算出(モンテカルロ法とベイズモデリング) / Business Valuation Using Monte Carlo DCF Method (Monte Carlo Simulation and Bayesian Modeling)
ikuma_w
0
200
実力評価性能を考慮した弓道高校生全国大会の大会制度設計の提案 / (konakalab presentation at MSS 2025.03)
konakalab
2
180
データマイニング - グラフデータと経路
trycycle
PRO
1
180
データベース08: 実体関連モデルとは?
trycycle
PRO
0
780
Featured
See All Featured
Gamification - CAS2011
davidbonilla
81
5.4k
実際に使うSQLの書き方 徹底解説 / pgcon21j-tutorial
soudai
PRO
181
54k
Product Roadmaps are Hard
iamctodd
PRO
54
11k
Build The Right Thing And Hit Your Dates
maggiecrowley
37
2.8k
Save Time (by Creating Custom Rails Generators)
garrettdimon
PRO
31
1.3k
Making the Leap to Tech Lead
cromwellryan
134
9.4k
Improving Core Web Vitals using Speculation Rules API
sergeychernyshev
18
1k
GitHub's CSS Performance
jonrohan
1031
460k
Building Applications with DynamoDB
mza
95
6.5k
ピンチをチャンスに:未来をつくるプロダクトロードマップ #pmconf2020
aki_iinuma
126
53k
Into the Great Unknown - MozCon
thekraken
40
1.9k
個人開発の失敗を避けるイケてる考え方 / tips for indie hackers
panda_program
108
19k
Transcript
Copyright 2022 Maxwell_110 Validation strategy - Sequence-based 4 fold CV
- The number of CoTS is close in each fold - Training data is frames with CoTs - Validation data includes frames w/o CoTs Resize up to 2.75 times using progressive learning 1280 720 Augmentation Increasing probability of applying augmentation as progressive learning progresses. - Default YOLO-X augmentations - random resize: (-5, 5) - mosaic / MixUp / hsv / flip: p = 0.6 -> 0.8 - degrees: Not used - translate: 0.1 - mosaic / MixUp scale: (0.5, 1.5) - RandomGamma - RGBShift - Sharpen - GaussNoise Batch Size: 4 GeForce RTX 3080 (x 2) Solution description in Kaggle discussion https://www.kaggle.com/c/tensorflow-great-barrier-reef/discussion/307691 Learning strategy - Progressive learning - Optimizer: default SGD (decay: 5e-4, momentum: 0.9) - LR: .000625 - Scheduler: yoloxwarmcos - min_lr_ratio: 0.1 - EMA: on - warmup_epochs: 5 - max_epoch: 30 TTA Seq-NMS https://arxiv.org/abs/1602.08465 https://github.com/tmoopenn/seq-nms n_frames: 2 confidence threshold: 0.07 linkage threshold: 0.1 nms th: 0.4 Weighted Box Fusion skip box threshold: 0.05 wbf IoU threshold: 0.45 Final confidence threshold: .08 Public LB : 0.607 Private LB : 0.714