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/JIA-HONG-CHU/Swin-Transformer-add-EncNet-DaNet-DraNet-for-semantic-segmentation-on-Statelite-Dataset
Swin Transformer: Hierarchical Vision Transformer using Shifted Windows
https://github.com/JIHOO97/Image-Classification-Competition
Bag of Tricks for Image Classification with Convolutional Neural Networks
https://github.com/JKozerawski/BLT
https://github.com/JONGSKY/paper
https://github.com/JPDaly/MultilayerPerceptron
https://github.com/JPlin/MSGAN
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/JQub/QuantumFlow_Tutorial
https://github.com/JRC1995/DemonRangerOptimizer
https://github.com/JSerowik/Masters_Thesis
https://github.com/JTan2231/DenseNet
https://github.com/JWMON/yolo
CSPNet: A New Backbone that can Enhance Learning Capability of CNN
https://github.com/JWSoh/MZSR
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
https://github.com/JacobM184/EfficientNet-for-Gun-detection
https://github.com/JacobPfau/PENCIL
Probabilistic End-to-end Noise Correction for Learning with Noisy Labels
https://github.com/JacopoDapueto/disentangled_microscopy
https://github.com/Jaehoon-Cha-Data/HD-CNN-Hierarchical-Deep-Convolutional-Neural-Network
HD-CNN: Hierarchical Deep Convolutional Neural Network for Large Scale Visual Recognition
https://github.com/JagadishSivakumar/Image-Classifier-ml5.js
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
https://github.com/JaidedAI/EasyOCR
https://github.com/JakobCode/UncertaintyInNeuralNetworks_Resources
https://github.com/JakobHavtorn/nn
https://github.com/JakobKallestad/InceptionV3-on-plankton-images
https://github.com/James-Gilbert-/medical-deep-learning
https://github.com/James-Gilbert-/pneumonia-detection
https://github.com/JanMarcelKezmann/Residual-Network-Architectures
https://github.com/JanMarcelKezmann/TensorFlow-Advanced-Segmentation-Models
https://github.com/Janghyeonwoong/Random-Erasing-Tensorflow2
https://github.com/Jannoshh/simple-sam
Sharpness-Aware Minimization for Efficiently Improving Generalization
https://github.com/Janus-Shiau/SAM-tf2
Sharpness-Aware Minimization for Efficiently Improving Generalization
https://github.com/Janus-Shiau/awd-lstm-tensorflow
https://github.com/Jara555/CNN-for-AD-classification
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
https://github.com/JarveeLee/HybridSupervisionLearning_Pathology
Hybrid Supervision Learning for Pathology Whole Slide Image Classification
https://github.com/JaryHuang/awesome_SSD_FPN_GIoU
https://github.com/Jason-CKY/pokeGAN_fusion
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/JasonLiTW/simple-railway-captcha-solver
https://github.com/Jasonlee1995/AutoAugment_Detection
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.