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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/vita-group/freetickets
공식 코드https://github.com/vita-group/longtailcxr
공식 코드Long-Tailed Classification of Thorax Diseases on Chest X-Ray: A New Benchmark Study
https://github.com/vita-group/prunecxr
공식 코드How Does Pruning Impact Long-Tailed Multi-Label Medical Image Classifiers?
https://github.com/vitae-transformer/mtp
공식 코드MTP: Advancing Remote Sensing Foundation Model via Multi-Task Pretraining
https://github.com/vithursant/SPL-ADVisE
공식 코드https://github.com/viv92/structured-attention-graphs
공식 코드One Explanation is Not Enough: Structured Attention Graphs for Image Classification
https://github.com/vkinakh/mv-mr
공식 코드MV-MR: multi-views and multi-representations for self-supervised learning and knowledge distillation
https://github.com/vkinakh/scatsimclr
공식 코드https://github.com/vkola-lab/tmi2022
공식 코드https://github.com/vladan-stojnic/CMC-RSSR
공식 코드Self-Supervised Learning of Remote Sensing Scene Representations Using Contrastive Multiview Coding
https://github.com/vladan-stojnic/zlap
공식 코드Label Propagation for Zero-shot Classification with Vision-Language Models
https://github.com/vlievin/biva-pytorch
공식 코드https://github.com/vmos1/cnn_supernova_b_paper
공식 코드Identifying Transients in the Dark Energy Survey using Convolutional Neural Networks
https://github.com/vojha-code/bneuralt
공식 코드https://github.com/voldemortX/DST-CBC
공식 코드https://github.com/voyazici/visual-transformers-classification
공식 코드Visual Transformers with Primal Object Queries for Multi-Label Image Classification
https://github.com/vrkh1996/Generalization-in-OOD-Detection
공식 코드https://github.com/vt-vl-lab/video-data-aug
공식 코드Learning Representational Invariances for Data-Efficient Action Recognition
https://github.com/vtddggg/Robust-Vision-Transformer
공식 코드https://github.com/vturrisi/disef
공식 코드Diversified in-domain synthesis with efficient fine-tuning for few-shot classification
https://github.com/vturrisi/solo-learn
공식 코드All4One: Symbiotic Neighbour Contrastive Learning via Self-Attention and Redundancy Reduction
https://github.com/vumaasha/atlas
공식 코드Atlas: A Dataset and Benchmark for E-commerce Clothing Product Categorization
https://github.com/vuno/kirby
공식 코드Key Feature Replacement of In-Distribution Samples for Out-of-Distribution Detection
https://github.com/vuoristo/MMAML
공식 코드Multimodal Model-Agnostic Meta-Learning via Task-Aware Modulation
https://github.com/vuptran/sesemi
공식 코드Exploring Self-Supervised Regularization for Supervised and Semi-Supervised Learning
https://github.com/vvoracek/provably-adversarially-robust-nearest-prototype-classifiers
공식 코드https://github.com/vvoracek/sound-randomized-smoothing
공식 코드https://github.com/vyzuer/ALTReco
공식 코드https://github.com/w4k2/sentence-space-stream
공식 코드Employing Sentence Space Embedding for Classification of Data Stream from Fake News Domain
https://github.com/wadiiboulila/weight-initialization
공식 코드https://github.com/wadx2019/homoode
공식 코드https://github.com/wake1021/inceptionmamba
공식 코드InceptionMamba: An Efficient Hybrid Network with Large Band Convolution and Bottleneck Mamba
https://github.com/wala/graph4code
공식 코드https://github.com/walline/doublematch
공식 코드DoubleMatch: Improving Semi-Supervised Learning with Self-Supervision
https://github.com/walline/prohoc
공식 코드ProHOC: Probabilistic Hierarchical Out-of-Distribution Classification via Multi-Depth Networks
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.