https://github.com/Deci-AI/super-gradients
Very Deep Convolutional Networks for Large-Scale Image Recognition
Papers with Code 아카이브
Domain Generalization
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 3
- 평가표
- 21
- 보존된 평가 기록
- 570
The idea of Domain Generalization is to learn from one or multiple training domains, to extract a domain-agnostic model which can be applied to an unseen domain
Source: Diagram Image Retrieval using Sketch-Based Deep Learning and Transfer Learning
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/DeepBrainsMe/FSnet
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
https://github.com/DeepMark/deepmark
https://github.com/DeepVoltaire/AutoAugment
https://github.com/DequanWang/tent
AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty
https://github.com/DevBruce/CutMixImageDataGenerator_For_Keras
CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features
https://github.com/DiegoArcelli/De-Stylization-Network
Two at Once: Enhancing Learning and Generalization Capacities via IBN-Net
https://github.com/Dmitrsl/Tools
Bag of Tricks for Image Classification with Convolutional Neural Networks
https://github.com/DogeZen/resnet2onnx2tensorrt
https://github.com/DominikBatic/EndoViT
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
https://github.com/DrRyanHuang/VGGNet
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/Duplums/bhb10k-dl-benchmark
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/ENSTA-U2IS-AI/torch-uncertainty
https://github.com/EPFL-VILAB/XDEnsembles
Benchmarking Neural Network Robustness to Common Corruptions and Perturbations
https://github.com/EdenMelaku/Transfer-Learning-Pytorch-Implementation
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/EdenMelaku/Transfer-Learning-Pytorch-Implmentation
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/EiroaMD/final_project_IH_pneumonia
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/Emma0118/domain-generalization
Feature-Critic Networks for Heterogeneous Domain Generalization
https://github.com/EngineeringSapien/NarutoCV
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/Epi-NMT/DADG
Discriminative Adversarial Domain Generalization with Meta-learning based Cross-domain Validation
https://github.com/EricAlcaide/MiniFold
https://github.com/EscVM/RSC-Wrapper
https://github.com/EstherBear/implementation-of-pruning-filters
https://github.com/EverLookNeverSee/diag2model
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/Evgeneus/Graph-Domain-Adaptaion
https://github.com/EvgenyVendrov/DeepLearningCourse
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/FaceOnLive/Face-Liveness-Detection-SDK-Linux
S-Adapter: Generalizing Vision Transformer for Face Anti-Spoofing with Statistical Tokens
https://github.com/FlyEgle/MAE-pytorch
https://github.com/FrancescoSaverioZuppichini/ResNet
https://github.com/GKalliatakis/Keras-VGG16-places365
https://github.com/GabrieleMonte/CoMBInE
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/Glp91/fire-detection
https://github.com/Godot-yry/VGG16_mindspore
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/Gojay001/toolkit-DeepLearning
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/Graylab/deepH3-distances-orientations
https://github.com/HAHA-DL/MLDG
Learning to Generalize: Meta-Learning for Domain Generalization
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.