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/bclwan/MRI_Brain_Segmentation
https://github.com/bcmi220/esc4nmt
https://github.com/bcv-uniandes/job-vs
https://github.com/bdeng99/Error-free-Training-Code
https://github.com/bdsaglam/CapsNet
https://github.com/bdy9527/SDCN
Deep Clustering for Unsupervised Learning of Visual Features
https://github.com/becauseofAI/DetNet-Keras
https://github.com/beeps82/SVHN_CNN
Multi-digit Number Recognition from Street View Imagery using Deep Convolutional Neural Networks
https://github.com/befallenStar/molecularAtt
Swin Transformer: Hierarchical Vision Transformer using Shifted Windows
https://github.com/beierzhu/xerm
Long-Tailed Classification by Keeping the Good and Removing the Bad Momentum Causal Effect
https://github.com/belqiliass/Music-Classifier
Convolutional Neural Network Achieves Human-level Accuracy in Music Genre Classification
https://github.com/ben-davidson-6/fixup
https://github.com/ben-ix/ConvGP
Genetic Programming and Gradient Descent: A Memetic Approach to Binary Image Classification
https://github.com/beneroth13/dinov2
https://github.com/benihime91/pytorch_retinanet
https://github.com/benjaminbeilharz/Generative-Algorithms-on-CNNs
Automatically designing CNN architectures using genetic algorithm for image classification
https://github.com/benjaminjellis/Objax-RepVGG
https://github.com/benjamintli/darknet-gun-detector
CSPNet: A New Backbone that can Enhance Learning Capability of CNN
https://github.com/benjamintli/training-results-azure
CSPNet: A New Backbone that can Enhance Learning Capability of CNN
https://github.com/benjs/nfnets_pytorch
High-Performance Large-Scale Image Recognition Without Normalization
https://github.com/bennyqp/artificial-inspiration
https://github.com/benolmbrt/MedicOOD
https://github.com/bentrevett/pytorch-image-classification
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/benywon/ReCO
https://github.com/bepierre/SpeechVGG
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/beresandras/contrastive-classification-keras
Momentum Contrast for Unsupervised Visual Representation Learning
https://github.com/beresandras/semisupervised-classification-keras
https://github.com/berniwal/swin-transformer-pytorch
Swin Transformer: Hierarchical Vision Transformer using Shifted Windows
https://github.com/bertrandlalo/deep_dog_breeds
https://github.com/bespontaneous/ffn
UniFormer: Unifying Convolution and Self-attention for Visual Recognition
https://github.com/bespontaneous/mca-pytorch
UniFormer: Unifying Convolution and Self-attention for Visual Recognition
https://github.com/bespontaneous/proteus-pytorch
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/betashort/ClassActivationMappings
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
https://github.com/betashort/DeepClusterings
Deep Clustering for Unsupervised Learning of Visual Features
https://github.com/bethgelab/InDomainGeneralizationBenchmark
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.