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/ARM-software/DeepFreeze
공식 코드FixyNN: Efficient Hardware for Mobile Computer Vision via Transfer Learning
https://github.com/ARiSE-Lab/DeepInspect
공식 코드https://github.com/ASU-ESIC-FAN-Lab/DEEPDUPA
공식 코드https://github.com/AamirRaihan/SWAT
공식 코드https://github.com/Abanoub-G/DIRA
공식 코드https://github.com/Abdullah-88/NiNformer
공식 코드NiNformer: A Network in Network Transformer with Token Mixing Generated Gating Function
https://github.com/AceChuse/TaskLevelAug
공식 코드https://github.com/AdamByerly/BMCNNwHFCs
공식 코드https://github.com/Adamdad/kat
공식 코드https://github.com/Adnan-Sadi/LMFLOSS
공식 코드LMFLOSS: A Hybrid Loss For Imbalanced Medical Image Classification
https://github.com/AdriBento/Greybox-
공식 코드https://github.com/Advanced-Vision-and-Learning-Lab/NEHD_UATR
공식 코드Neural Edge Histogram Descriptors for Underwater Acoustic Target Recognition
https://github.com/Aegsteh-T/FedLuck_Euro_Par
공식 코드https://github.com/AfifaKhaled/Batch-Channel-Normalization
공식 코드https://github.com/AhmadSajedii/ProbMCL
공식 코드ProbMCL: Simple Probabilistic Contrastive Learning for Multi-label Visual Classification
https://github.com/AhmedZgaren/Coarse-to-fine-Tracker
공식 코드Coarse-to-Fine Object Tracking Using Deep Features and Correlation Filters
https://github.com/Aiolus-X/RefConv
공식 코드RefConv: Re-parameterized Refocusing Convolution for Powerful ConvNets
https://github.com/Akshayjain97/Non-Uniform_Illumination
공식 코드Non-Uniform Illumination Attack for Fooling Convolutional Neural Networks
https://github.com/AlexColagrande/MANO
공식 코드Linear Attention with Global Context: A Multipole Attention Mechanism for Vision and Physics
https://github.com/AlexImmer/marglik
공식 코드Scalable Marginal Likelihood Estimation for Model Selection in Deep Learning
https://github.com/AlexMeinke/Provable-OOD-Detection
공식 코드Provably Robust Detection of Out-of-distribution Data (almost) for free
https://github.com/AlexanderBartler/MT3
공식 코드MT3: Meta Test-Time Training for Self-Supervised Test-Time Adaption
https://github.com/AlexandraVolokhova/stochasticity_in_neural_ode
공식 코드https://github.com/Alexei95/FasTrCaps
공식 코드FasTrCaps: An Integrated Framework for Fast yet Accurate Training of Capsule Networks
https://github.com/AlexeyAB/darknet
공식 코드CSPNet: A New Backbone that can Enhance Learning Capability of CNN
https://github.com/Alibaba-AAIG/SSL-FEW-SHOT
공식 코드https://github.com/Alibaba-MIIL/ASL
공식 코드https://github.com/Alibaba-MIIL/ImageNet21K
공식 코드https://github.com/AllanSCosta/occam-net
공식 코드OccamNet: A Fast Neural Model for Symbolic Regression at Scale
https://github.com/AlonZolfi/YolOOD
공식 코드YolOOD: Utilizing Object Detection Concepts for Multi-Label Out-of-Distribution Detection
https://github.com/AmalRT/DNN_Reg
공식 코드https://github.com/Amshaker/GroupMamba
공식 코드https://github.com/AngeloFang/MIPR_UAAN
공식 코드Uncertainty-Guided Appearance-Motion Association Network for Out-of-Distribution Action Detection
https://github.com/AnirudhMaiya/Tom
공식 코드Tom: Leveraging trend of the observed gradients for faster convergence
https://github.com/Annbless/ViTAE
공식 코드ViTAE: Vision Transformer Advanced by Exploring Intrinsic Inductive Bias
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.