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/FarzamIHPC/YoloV3_mask
CSPNet: A New Backbone that can Enhance Learning Capability of CNN
https://github.com/FelixAbrahamsson/mixmatch-pytorch
https://github.com/FengHZ/AAAI2021-260
SHOT-VAE: Semi-supervised Deep Generative Models With Label-aware ELBO Approximations
https://github.com/FilLTP89/SeismoALICE
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/FloCF/SSL_pytorch
https://github.com/FlyEgle/MAE-pytorch
https://github.com/FlyingMoon-GitHub/ACNet
Attention Convolutional Binary Neural Tree for Fine-Grained Visual Categorization
https://github.com/FraCorti/Deep_Subnetworks_for_Dynamic_Resource_Constraints
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
https://github.com/Fragjacker/Pointcloud-grad-CAM
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
https://github.com/FrancescoSaverioZuppichini/A-journey-into-Convolutional-Neural-Network-visualization-
Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps
https://github.com/FrancescoSaverioZuppichini/ResNet
https://github.com/FreddeFrallan/Multilingual-CLIP
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/Fsoft-AIC/Neural-Collapse-in-Deep-Linear-Networks
Neural Collapse in Deep Linear Networks: From Balanced to Imbalanced Data
https://github.com/FuxiaoLiu/LRV-Instruction
Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotations
https://github.com/Fw9wef/DetectorGAN
https://github.com/G-4-R-Y/Tweet-Sentiment-Extraction
https://github.com/G-4-R-Y/Tweet-Sentiment-Extraction-roBERTa-5fold
https://github.com/GH920/Improve-Medical-Image-Classification-with-GAN
https://github.com/GH920/improved-bagan-gp
https://github.com/GISH123/Cathay-Holdings-CIP-Projects-for-Interpretable-Machine-Learning
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
https://github.com/GKalliatakis/Keras-VGG16-places365
https://github.com/GPUPhobia/vocal-mask
https://github.com/GSNCodes/Breast_Cancer_Detection_CNN
https://github.com/GT-RIPL/FeatMatch
FeatMatch: Feature-Based Augmentation for Semi-Supervised Learning
https://github.com/GXYM/Focal-loss
https://github.com/GabrieleMonte/CoMBInE
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/Gahyeonkim09/AAPL
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/GangmingZhao/GraphFPN-Graph-Feature-Pyramid-Network-for-Object-Detection
https://github.com/Gauravshahare/ADVERSIAL_AUTOENCODER
https://github.com/Gauravsharma-20/Minor-Project
https://github.com/GeekLiB/caffe-model
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
https://github.com/GenesisDCarmen/C_Reconocimiento_Facial
https://github.com/GeoTrouvetout/Vehicle_ReID
https://github.com/GeorgOhneH/WerbeSkip
Averaging Weights Leads to Wider Optima and Better Generalization
https://github.com/George0828Zhang/simulst
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.