https://github.com/MalongTech/CurriculumNet
공식 코드CurriculumNet: Weakly Supervised Learning from Large-Scale Web Images
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/Markin-Wang/FFVT
공식 코드Feature Fusion Vision Transformer for Fine-Grained Visual Categorization
https://github.com/MarziEd/SubSpace-Capsule-Network
공식 코드https://github.com/MatthieuCourbariaux/BinaryConnect
공식 코드BinaryConnect: Training Deep Neural Networks with binary weights during propagations
https://github.com/Mayachitra-Inc/MaleX
공식 코드Malware Detection Using Frequency Domain-Based Image Visualization and Deep Learning
https://github.com/MedMNIST/MedMNIST
공식 코드MedMNIST v2 -- A large-scale lightweight benchmark for 2D and 3D biomedical image classification
https://github.com/Media-Smart/vedastr
공식 코드Revisiting Classification Perspective on Scene Text Recognition
https://github.com/Megvii-BaseDetection/DisAlign
공식 코드Distribution Alignment: A Unified Framework for Long-tail Visual Recognition
https://github.com/Megvii-Nanjing/BBN
공식 코드BBN: Bilateral-Branch Network with Cumulative Learning for Long-Tailed Visual Recognition
https://github.com/Meituan-AutoML/CPVT
공식 코드https://github.com/Meituan-AutoML/Twins
공식 코드Twins: Revisiting the Design of Spatial Attention in Vision Transformers
https://github.com/MenghaoGuo/-EANet
공식 코드Beyond Self-attention: External Attention using Two Linear Layers for Visual Tasks
https://github.com/MenghaoGuo/Awesome-Vision-Attentions
공식 코드https://github.com/Merrical/ILDE
공식 코드Instance-dependent Label Distribution Estimation for Learning with Label Noise
https://github.com/MetaMain/ViTRobust
공식 코드On the Robustness of Vision Transformers to Adversarial Examples
https://github.com/MichaelFan01/STDC-Seg
공식 코드https://github.com/Microsoft/EdgeML
공식 코드RNNPool: Efficient Non-linear Pooling for RAM Constrained Inference
https://github.com/MinkaiXu/RSL-NMT
공식 코드Reciprocal Supervised Learning Improves Neural Machine Translation
https://github.com/MitchellKT/Enhanced-Meta-Label-Correction
공식 코드Enhanced Meta Label Correction for Coping with Label Corruption
https://github.com/MonashAI/HVT
공식 코드https://github.com/MonashAI/LIT
공식 코드https://github.com/MorningStarOvO/ProAPO
공식 코드ProAPO: Progressively Automatic Prompt Optimization for Visual Classification
https://github.com/MrChenFeng/SSR_BMVC2022
공식 코드SSR: An Efficient and Robust Framework for Learning with Unknown Label Noise
https://github.com/MrtnMndt/Rethinking_CNN_Layerwise_Feature_Amounts
공식 코드Rethinking Layer-wise Feature Amounts in Convolutional Neural Network Architectures
https://github.com/MuXutong/FedProc
공식 코드FedProc: Prototypical Contrastive Federated Learning on Non-IID data
https://github.com/Mukaffi28/Explainable-AI-for-Lung-and-Colon-Cancer-Classification
공식 코드https://github.com/MungoMeng/Spiking-Inception
공식 코드High-parallelism Inception-like Spiking Neural Networks for Unsupervised Feature Learning
https://github.com/MyChocer/KGTN
공식 코드https://github.com/NAVER-INTEL-Co-Lab/gaudi-byzantine
공식 코드https://github.com/NJUVISION/MPA
공식 코드All-in-One Image Coding for Joint Human-Machine Vision with Multi-Path Aggregation
https://github.com/NJUVISION/POLC
공식 코드Perception-Oriented Latent Coding for High-Performance Compressed Domain Semantic Inference
https://github.com/NJUyued/MutexMatch4SSL
공식 코드MutexMatch: Semi-Supervised Learning with Mutex-Based Consistency Regularization
https://github.com/NUS-HPC-AI-Lab/R-MeeTo
공식 코드Faster Vision Mamba is Rebuilt in Minutes via Merged Token Re-training
https://github.com/NUST-Machine-Intelligence-Laboratory/dmbfgvr
공식 코드Data-driven Meta-set Based Fine-Grained Visual Classification
https://github.com/NVlabs/FasterViT
공식 코드FasterViT: Fast Vision Transformers with Hierarchical Attention
https://github.com/NVlabs/condensa
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.