Papers with Code 아카이브
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/SophiaYuSophiaYu/ImageCaption
https://github.com/Soumya1612-Rasha/Keras-GAN_rasha
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/SoumyadeepJana/CelebrityFaceGeneration
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/SourangshuGhosh/CGP-CNN-Design
A Genetic Programming Approach to Designing Convolutional Neural Network Architectures
https://github.com/SpaceNetChallenge/utilities
https://github.com/Spain2394/darknet
CSPNet: A New Backbone that can Enhance Learning Capability of CNN
https://github.com/SpanoChristian/darknet
CSPNet: A New Backbone that can Enhance Learning Capability of CNN
https://github.com/Spider-scnu/Instance-Segmentation-For-Cancer
https://github.com/SpikeKing/VQA-v2
https://github.com/SpikeKing/mobilenet_v3
https://github.com/Spoorthy-gunda/Image-Classification
https://github.com/SrinjaySarkar/ViT
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
https://github.com/SsnL/moco
https://github.com/SsnL/moco_align_uniform
https://github.com/StanfordASL/SCOD
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
https://github.com/StefOe/indrnn-pytorch
Independently Recurrent Neural Network (IndRNN): Building A Longer and Deeper RNN
https://github.com/StephKua/Kaggle-Twitter-Sentiment-Extraction
Multi-Sample Dropout for Accelerated Training and Better Generalization
https://github.com/Stephenfang51/Focal_loss_turtorial
https://github.com/Stephenfang51/Grad_CAM
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
https://github.com/StevenGerrad/large-scale-Evolution-Net
https://github.com/Stomper10/CheXpert
https://github.com/SuchismitaSahu1993/Studying-the-Robustness-of-GANs-on-Noisy-Data-using-MNIST-and-EMNIST-Datasets
https://github.com/Suci2609/generate_train_list.py-
https://github.com/Sujith2k/darknet
CSPNet: A New Backbone that can Enhance Learning Capability of CNN
https://github.com/SunDoge/efficientnet-pytorch
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
https://github.com/Sunarker/Safeguarded-Dynamic-Label-Regression-for-Noisy-Supervision
Safeguarded Dynamic Label Regression for Generalized Noisy Supervision
https://github.com/Sunil4423/-cassava_disease_classification
https://github.com/Sunkua/Colorizer
https://github.com/Sunnydreamrain/IndRNN
Independently Recurrent Neural Network (IndRNN): Building A Longer and Deeper RNN
https://github.com/SupratimH/neural-style-transfer
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/SupreethRao99/VisionTransformer
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
https://github.com/Suraj-Panwar/Capsule_Network_based_Deep_Q_learning
https://github.com/Sushma07/dancedarknet
https://github.com/SyBorg91/pose-estimation-detection
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
https://github.com/Syarujianai/deeplab-commented
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.