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/daniilidis-group/swscnn
공식 코드https://github.com/danjacobellis/LCCL
공식 코드https://github.com/danjacobellis/mpq
공식 코드https://github.com/danjacobellis/walloc
공식 코드https://github.com/danmcduff/characterizingBias
공식 코드https://github.com/danushv07/n2gem
공식 코드Detecting Adversarial Examples in Batches -- a geometrical approach
https://github.com/dao-ailab/flash-attention
공식 코드FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness
https://github.com/darija-open-dataset/dataset
공식 코드https://github.com/darrenzhang01/excon
공식 코드ExCon: Explanation-driven Supervised Contrastive Learning for Image Classification
https://github.com/darthsimpus/RQNN
공식 코드Random Quantum Neural Networks (RQNN) for Noisy Image Recognition
https://github.com/dashenzi721/csp
공식 코드Towards Better Multi-head Attention via Channel-wise Sample Permutation
https://github.com/data-science-in-mechanical-engineering/space
공식 코드https://github.com/davidbau/dissect
공식 코드Understanding the Role of Individual Units in a Deep Neural Network
https://github.com/davidyanande/arc
공식 코드Efficient Adaptation of Large Vision Transformer via Adapter Re-Composing
https://github.com/davidyyd/alpha-svrg
공식 코드https://github.com/davidzhangyuanhan/bamboo
공식 코드Bamboo: Building Mega-Scale Vision Dataset Continually with Human-Machine Synergy
https://github.com/davor10105/relative-absolute-magnitude-propagation
공식 코드https://github.com/davydovalexander/non-euclidean_mon_op_net
공식 코드https://github.com/dazhangyu123/acmil
공식 코드Attention-Challenging Multiple Instance Learning for Whole Slide Image Classification
https://github.com/dazhangyu123/adr
공식 코드https://github.com/dazhangyu123/aem
공식 코드https://github.com/dazhangyu123/ocl
공식 코드Test-Time Training for Semantic Segmentation with Output Contrastive Loss
https://github.com/dbp1994/bare-wacv-2023
공식 코드Adaptive Sample Selection for Robust Learning under Label Noise
https://github.com/dcorradetti/redai_id_pattern
공식 코드Identification of Stone Deterioration Patterns with Large Multimodal Models
https://github.com/dddavid4real/focus
공식 코드FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification
https://github.com/ddv-lab/Verifiably_Robust_CP
공식 코드https://github.com/dealicious-inc/dtop
공식 코드https://github.com/dearcaat/mhim-mil
공식 코드https://github.com/dearcaat/pict
공식 코드PicT: A Slim Weakly Supervised Vision Transformer for Pavement Distress Classification
https://github.com/dearcaat/wsplin
공식 코드https://github.com/debcaldarola/fedsam
공식 코드Improving Generalization in Federated Learning by Seeking Flat Minima
https://github.com/decile-team/distil
공식 코드SIMILAR: Submodular Information Measures Based Active Learning In Realistic Scenarios
https://github.com/decile-team/trust
공식 코드PRISM: A Rich Class of Parameterized Submodular Information Measures for Guided Subset Selection
https://github.com/declanmcintosh/legallcuda
공식 코드Preservation of High Frequency Content for Deep Learning-Based Medical Image Classification
https://github.com/decodepfl/contractive-hamiltonian-neural-odes
공식 코드Robust Classification using Contractive Hamiltonian Neural ODEs
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.