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/Deepak3994/Grad-Cam
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
https://github.com/Deepak3994/grad-cam-editted
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
https://github.com/Deepayan137/DeepClustering
https://github.com/Demonhesusheng/darknet_v2
CSPNet: A New Backbone that can Enhance Learning Capability of CNN
https://github.com/DenseAI/awesome-biomedical-machine-learning
https://github.com/DenseAI/awesome-medical-machine-learning
https://github.com/DerrickGXD/unsupervised-keypoints
Unsupervised Learning of Object Keypoints for Perception and Control
https://github.com/DetectionTeamUCAS/RetinaNet_Tensorflow_Rotation
https://github.com/DevBruce/CutMixImageDataGenerator_For_Keras
CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features
https://github.com/DevD1092/face_emotion_recog
https://github.com/Dhruvpatel2112/Dhruv-Patel
Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning
https://github.com/Di-Is/stylegan2-ada-pytorch
https://github.com/DiKorsch/l1_parts
Classification-Specific Parts for Improving Fine-Grained Visual Categorization
https://github.com/DiMarzioRock7/Aerial-Semantic-Segmentation-Drone
https://github.com/DiMarzioRock7/PSPNet
https://github.com/Dichao-Liu/CMAL
https://github.com/Dichao-Liu/CRA-CNN
https://github.com/DiegoOrtego/LabelNoiseMOIT
Multi-Objective Interpolation Training for Robustness to Label Noise
https://github.com/Diganta13/Image-segmentation-by-UNet-Algorithm
Fully Convolutional Architectures for Multi-Class Segmentation in Chest Radiographs
https://github.com/Digiratory/fuzzy-rank-ensemble-torch
https://github.com/Diksha942/Visual-Transformers
Visual Transformers: Token-based Image Representation and Processing for Computer Vision
https://github.com/Ding1119/CGMCL
Enhancing Multimodal Medical Image Classification using Cross-Graph Modal Contrastive Learning
https://github.com/DingXiaoH/GSM-SGD
RepMLP: Re-parameterizing Convolutions into Fully-connected Layers for Image Recognition
https://github.com/DingXiaoH/ResRep
RepMLP: Re-parameterizing Convolutions into Fully-connected Layers for Image Recognition
https://github.com/DivyanshRoy/Learning-Activation-Function-Using-Tensorflow
Learning Activation Functions to Improve Deep Neural Networks
https://github.com/Dmitrsl/Tools
Bag of Tricks for Image Classification with Convolutional Neural Networks
https://github.com/DoTung-bkhn/multiclass-segmentation
https://github.com/DoctorLiQ/AutoML
https://github.com/DogeZen/resnet2onnx2tensorrt
https://github.com/DominickZhang/Distillation-Swin-Transformer
Swin Transformer: Hierarchical Vision Transformer using Shifted Windows
https://github.com/DominikBatic/EndoViT
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
https://github.com/DonCorle0ne/damage_detection
https://github.com/DonghwanKIM0101/CS492I_CV
https://github.com/Doyosae/Deep-Complex-Networks
https://github.com/Doyosae/Deep_Complex_Networks
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.