https://github.com/sophiali06/byteps_thc
공식 코드THC: Accelerating Distributed Deep Learning Using Tensor Homomorphic Compression
Papers with Code 아카이브
Image Classification
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- 33
- 평가표
- 177
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- 2,906
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/sotiraslab/scmil
공식 코드SC-MIL: Sparsely Coded Multiple Instance Learning for Whole Slide Image Classification
https://github.com/soumik-kanad/diffssl
공식 코드Do text-free diffusion models learn discriminative visual representations?
https://github.com/soumyaxyz/abstractAnalysis
공식 코드Automatic Recognition of Learning Resource Category in a Digital Library
https://github.com/soumyaxyz/documentclassify
공식 코드Automatic Recognition of Learning Resource Category in a Digital Library
https://github.com/sourajitcs/tips
공식 코드https://github.com/spalaciob/s2snets-reconstruction
공식 코드https://github.com/spallanzanimatteo/QuantLab
공식 코드Additive Noise Annealing and Approximation Properties of Quantized Neural Networks
https://github.com/sparshgup/QNL-Net
공식 코드A Scalable Quantum Non-local Neural Network for Image Classification
https://github.com/spraise/BSNet
공식 코드BSNet: Bi-Similarity Network for Few-shot Fine-grained Image Classification
https://github.com/spravil/HyenaPixel
공식 코드https://github.com/srebuffi/lsd-clusters
공식 코드https://github.com/sreyan88/aspire
공식 코드ASPIRE: Language-Guided Data Augmentation for Improving Robustness Against Spurious Correlations
https://github.com/ssfootball04/class-balanced-experts
공식 코드https://github.com/ssharoff/robust
공식 코드Know thy corpus! Robust methods for digital curation of Web corpora
https://github.com/stanford-aimi/liere
공식 코드https://github.com/stanford-aimi/ravl
공식 코드RaVL: Discovering and Mitigating Spurious Correlations in Fine-Tuned Vision-Language Models
https://github.com/stanford-futuredata/equivariant-transformers
공식 코드https://github.com/stanfordmlgroup/ManyICL
공식 코드Many-Shot In-Context Learning in Multimodal Foundation Models
https://github.com/stanfordmlgroup/MedSelect
공식 코드https://github.com/stanfordmlgroup/MoCo-CXR
공식 코드MoCo-CXR: MoCo Pretraining Improves Representation and Transferability of Chest X-ray Models
https://github.com/stanislavfort/adversaries_to_ood_detection
공식 코드Adversarial vulnerability of powerful near out-of-distribution detection
https://github.com/starmemda/MlTr
공식 코드https://github.com/state-spaces/s4
공식 코드Efficiently Modeling Long Sequences with Structured State Spaces
https://github.com/steffi7574/LayerParallelLearning
공식 코드https://github.com/stegmuel/ScoreNet
공식 코드https://github.com/steremma/curr-meta-learning
공식 코드https://github.com/stevengrove/vtpack
공식 코드https://github.com/stevinc/TheColorOutOfSpace
공식 코드The color out of space: learning self-supervised representations for Earth Observation imagery
https://github.com/stmstmstm/stm
공식 코드https://github.com/stockeh/canine-embedded-ml
공식 코드Who's a Good Boy? Reinforcing Canine Behavior in Real-Time using Machine Learning
https://github.com/stomach-ache/long-tailed-ood-detection
공식 코드https://github.com/stomachcold/hctransformers
공식 코드Attribute Surrogates Learning and Spectral Tokens Pooling in Transformers for Few-shot Learning
https://github.com/stonemo/cign
공식 코드Class-Incremental Grouping Network for Continual Audio-Visual Learning
https://github.com/stonezwr/TSSL-BP
공식 코드Temporal Spike Sequence Learning via Backpropagation for Deep Spiking Neural Networks
https://github.com/stwisdom/urnn
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.