Image Classification
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Image Classification is a fundamental task in vision recognition that aims to understand and categorize an image as a whole under a specific label. Unlike object detection, which involves classification and location of multiple objects within an image, image classification typically pertains to single-object images. When the classification becomes highly detailed or reaches instance-level, it is often referred to as image retrieval, which also involves finding similar images in a large database.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/2023-MindSpore-1/ms-code-213/tree/main/FaceAttribute
https://github.com/2023-MindSpore-1/ms-code-214/blob/main/glore_res/README_CN.md
https://github.com/2023-MindSpore-1/ms-code-214/tree/main/HireMLP
https://github.com/2023-MindSpore-1/ms-code-214/tree/main/Inception-v2
Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning
https://github.com/2023-MindSpore-1/ms-code-214/tree/main/ghostnet_d
https://github.com/2023-MindSpore-1/ms-code-214/tree/main/ghostnet_quant
GhostShiftAddNet: More Features from Energy-Efficient Operations
https://github.com/2023-MindSpore-1/ms-code-214/tree/main/googlenet
https://github.com/2023-MindSpore-1/ms-code-214/tree/main/inception_resnet_v2
Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning
https://github.com/2023-MindSpore-1/ms-code-215/tree/main/PSPNet
https://github.com/2023-MindSpore-1/ms-code-215/tree/main/ProtoNet
Improving ProtoNet for Few-Shot Video Object Recognition: Winner of ORBIT Challenge 2022
https://github.com/2023-MindSpore-1/ms-code-215/tree/main/ntsnet
https://github.com/2023-MindSpore-1/ms-code-215/tree/main/pnasnet
https://github.com/2023-MindSpore-1/ms-code-215/tree/main/pointtransformer
https://github.com/2023-MindSpore-1/ms-code-215/tree/main/proxylessnas
ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware
https://github.com/2023-MindSpore-1/ms-code-216/tree/main/ReIDStrongBaseline
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/2023-MindSpore-1/ms-code-216/tree/main/ResNeSt50
https://github.com/2023-MindSpore-1/ms-code-216/tree/main/ResidualAttentionNet
https://github.com/2023-MindSpore-1/ms-code-216/tree/main/S-GhostNet
https://github.com/2023-MindSpore-1/ms-code-216/tree/main/SE-Net
https://github.com/2023-MindSpore-1/ms-code-216/tree/main/SE_ResNeXt50
https://github.com/2023-MindSpore-1/ms-code-216/tree/main/relationnet
https://github.com/2023-MindSpore-1/ms-code-216/tree/main/repvgg
https://github.com/2023-MindSpore-1/ms-code-216/tree/main/res2net
https://github.com/2023-MindSpore-1/ms-code-216/tree/main/resnet50_adv_pruning
https://github.com/2023-MindSpore-1/ms-code-216/tree/main/resnetv2_50_frn
https://github.com/2023-MindSpore-1/ms-code-216/tree/main/resnext152_64x4d
Aggregated Residual Transformations for Deep Neural Networks
https://github.com/2023-MindSpore-1/ms-code-216/tree/main/retinanet_resnet101
https://github.com/2023-MindSpore-1/ms-code-216/tree/main/retinanet_resnet152
https://github.com/2023-MindSpore-1/ms-code-216/tree/main/simclr
A Simple Framework for Contrastive Learning of Visual Representations
https://github.com/2023-MindSpore-1/ms-code-217/tree/main/ViG
https://github.com/2023-MindSpore-1/ms-code-217/tree/main/squeezenet
SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size
https://github.com/2023-MindSpore-1/ms-code-217/tree/main/sr_ea
Multi-Objective Reinforced Evolution in Mobile Neural Architecture Search
https://github.com/2023-MindSpore-1/ms-code-217/tree/main/ssc_resnet50
https://github.com/2023-MindSpore-1/ms-code-217/tree/main/ssd_inceptionv2
Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning
https://github.com/2023-MindSpore-1/ms-code-217/tree/main/ssd_mobilenetV2
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.