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/yuxinwenrick/thinking-two-moves-ahead
공식 코드Thinking Two Moves Ahead: Anticipating Other Users Improves Backdoor Attacks in Federated Learning
https://github.com/yuyijiong/remote_sense_image_quality_inspection
공식 코드An Intelligent Remote Sensing Image Quality Inspection System
https://github.com/yuyinzhou/l2b
공식 코드L2B: Learning to Bootstrap Robust Models for Combating Label Noise
https://github.com/yuyongcan/benchmark-tta
공식 코드Benchmarking Test-Time Adaptation against Distribution Shifts in Image Classification
https://github.com/yws-wxs/vminet
공식 코드A Separable Self-attention Inspired by the State Space Model for Computer Vision
https://github.com/ywwynm/smr
공식 코드Perceptual Video Coding for Machines via Satisfied Machine Ratio Modeling
https://github.com/yyliu01/rpl
공식 코드Residual Pattern Learning for Pixel-wise Out-of-Distribution Detection in Semantic Segmentation
https://github.com/yyt0718/Intri_Attack
공식 코드Data-Free Universal Attack by Exploiting the Intrinsic Vulnerability of Deep Models
https://github.com/yzd-v/FGD
공식 코드https://github.com/yzd-v/MGD
공식 코드https://github.com/yzd-v/cls_KD
공식 코드ViTKD: Practical Guidelines for ViT feature knowledge distillation
https://github.com/yzou2/CRST
공식 코드https://github.com/yzqinjacob/distill-mlc
공식 코드Knowledge Distillation from Single to Multi Labels: an Empirical Study
https://github.com/z-sherkat/baytta
공식 코드https://github.com/z-x-yang/GCT
공식 코드https://github.com/z3n0e/MFRW
공식 코드https://github.com/zachgolden/geoai
공식 코드High Definition image classification in Geoscience using Machine Learning
https://github.com/zaharah/ood_audio
공식 코드On Out-of-Distribution Detection for Audio with Deep Nearest Neighbors
https://github.com/zaiweizhang/Joint-Learning-of-NN
공식 코드Joint Learning of Neural Networks via Iterative Reweighted Least Squares
https://github.com/zakariasenousy/mcua-model
공식 코드https://github.com/zamaex96/Spoof-Detect-Using-ViT
공식 코드https://github.com/zanedurante/vlm_benchmark
공식 코드Few-Shot Classification of Interactive Activities of Daily Living (InteractADL)
https://github.com/zangzelin/code_ECCV2022_DLME
공식 코드https://github.com/zangzelin/code_diffaug
공식 코드https://github.com/zanyarz/zodiac
공식 코드https://github.com/zavalab/plasmodata.jl
공식 코드PlasmoData.jl -- A Julia Framework for Modeling and Analyzing Complex Data as Graphs
https://github.com/zbf1991/RRM
공식 코드Reliability Does Matter: An End-to-End Weakly Supervised Semantic Segmentation Approach
https://github.com/zczcwh/PoseFormer
공식 코드3D Human Pose Estimation with Spatial and Temporal Transformers
https://github.com/zdy93/colafier
공식 코드CoLafier: Collaborative Noisy Label Purifier With Local Intrinsic Dimensionality Guidance
https://github.com/zeeshannisar/cx_gan
공식 코드https://github.com/zehui-lin/uniusnet
공식 코드UniUSNet: A Promptable Framework for Universal Ultrasound Disease Prediction and Tissue Segmentation
https://github.com/zeiss-microscopy/BSConv
공식 코드https://github.com/zengsn/research
공식 코드https://github.com/zengwang430521/tcformer
공식 코드TCFormer: Visual Recognition via Token Clustering Transformer
https://github.com/zengxyyu/PMI-TR
공식 코드A Framework for Inference Inspired by Human Memory Mechanisms
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.