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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/sudarshanregmi/AdaSCALE
공식 코드https://github.com/sudarshanregmi/T2FNorm
공식 코드T2FNorm: Extremely Simple Scaled Train-time Feature Normalization for OOD Detection
https://github.com/sudarshanregmi/ascood
공식 코드https://github.com/suhyun777/cvpr23-gap
공식 코드https://github.com/sukrutrao/attribution-evaluation
공식 코드https://github.com/sumanthsadhu/mc-optimizer
공식 코드Moment Centralization based Gradient Descent Optimizers for Convolutional Neural Networks
https://github.com/sumanyumuku98/contextual-bias
공식 코드Does Data Repair Lead to Fair Models? Curating Contextually Fair Data To Reduce Model Bias
https://github.com/summitgao/hc_adgan
공식 코드Adaptive DropBlock Enhanced Generative Adversarial Networks for Hyperspectral Image Classification
https://github.com/summitgao/msfmamba
공식 코드https://github.com/summitgao/ss-mae
공식 코드SS-MAE: Spatial-Spectral Masked Auto-Encoder for Multi-Source Remote Sensing Image Classification
https://github.com/sumyeongahn/cuda_ltr
공식 코드CUDA: Curriculum of Data Augmentation for Long-Tailed Recognition
https://github.com/sun-umn/Transfer-Learning-in-Medical-Imaging
공식 코드Rethinking Transfer Learning for Medical Image Classification
https://github.com/sun-umn/ttl
공식 코드Rethinking Transfer Learning for Medical Image Classification
https://github.com/sunarker/lccn
공식 코드https://github.com/sunblaze-ucb/transferability-advdnn-pub
공식 코드Delving into Transferable Adversarial Examples and Black-box Attacks
https://github.com/sundw2014/DKS
공식 코드https://github.com/sungbinlim/GBS
공식 코드https://github.com/sungbinlim/neuboots
공식 코드https://github.com/sungho-coolg/fscl
공식 코드Fair Contrastive Learning for Facial Attribute Classification
https://github.com/sungjinl/icassp2019-ood-dataset
공식 코드Contextual Out-of-Domain Utterance Handling With Counterfeit Data Augmentation
https://github.com/sunnan191/evisec
공식 코드Evidential Spectrum-Aware Contrastive Learning for OOD Detection in Dynamic Graphs
https://github.com/sunnysiqi/combo
공식 코드A Unified Framework for Connecting Noise Modeling to Boost Noise Detection
https://github.com/sunnysiqi/lnl_k
공식 코드LNL+K: Enhancing Learning with Noisy Labels Through Noise Source Knowledge Integration
https://github.com/sunpengfei1122/DMU
공식 코드Delayed Memory Unit: Modelling Temporal Dependency Through Delay Gate
https://github.com/sunsmarterjie/DAAS
공식 코드https://github.com/sunyoung98/Brain_Tumor_Detection_XAI
공식 코드Explainability of Deep Neural Networks for Brain Tumor Detection
https://github.com/super-AND/super-AND
공식 코드A Comprehensive Approach to Unsupervised Embedding Learning based on AND Algorithm
https://github.com/sushizixin/clip4idc
공식 코드https://github.com/sushmitasarker/sgc_for_medical_image_classification
공식 코드Can Score-Based Generative Modeling Effectively Handle Medical Image Classification?
https://github.com/sustainlab-group/geography-aware-ssl
공식 코드https://github.com/sustcsonglin/flash-linear-attention
공식 코드https://github.com/sutd-visual-computing-group/LS-KD-compatibility
공식 코드Revisiting Label Smoothing and Knowledge Distillation Compatibility: What was Missing?
https://github.com/sverneka/ConfidentClassifierICLR19
공식 코드Analysis of Confident-Classifiers for Out-of-distribution Detection
https://github.com/sverneka/OODGen
공식 코드https://github.com/swadesh06/revisting_cropa
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.