https://github.com/bollossom/GAC
공식 코드Gated Attention Coding for Training High-performance and Efficient Spiking Neural Networks
Papers with Code 아카이브
Image Classification
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- 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/boone891214/gap
공식 코드Effective Model Sparsification by Scheduled Grow-and-Prune Methods
https://github.com/borchero/natural-posterior-network
공식 코드Natural Posterior Network: Deep Bayesian Uncertainty for Exponential Family Distributions
https://github.com/borisshirokikh/mood_submission_sample-level_airi
공식 코드Solving Sample-Level Out-of-Distribution Detection on 3D Medical Images
https://github.com/boschresearch/GridSaliency-ToyDatasetGen
공식 코드Grid Saliency for Context Explanations of Semantic Segmentation
https://github.com/boschresearch/autoclip
공식 코드AutoCLIP: Auto-tuning Zero-Shot Classifiers for Vision-Language Models
https://github.com/boschresearch/diagvib-6
공식 코드https://github.com/boschresearch/meta-adversarial-training
공식 코드https://github.com/boschresearch/multiosr
공식 코드https://github.com/botong516/conformal_structured_prediction
공식 코드https://github.com/boyiliee/sitta
공식 코드SITTA: Single Image Texture Translation for Data Augmentation
https://github.com/boyuanjackchen/miniproject2_vistrans
공식 코드Understanding Why ViT Trains Badly on Small Datasets: An Intuitive Perspective
https://github.com/boyuh/aucseg
공식 코드AUCSeg: AUC-oriented Pixel-level Long-tail Semantic Segmentation
https://github.com/bradyfu/awesome-multimodal-large-language-models
공식 코드MME-Survey: A Comprehensive Survey on Evaluation of Multimodal LLMs
https://github.com/braincog-x/brain-cog
공식 코드TIM: An Efficient Temporal Interaction Module for Spiking Transformer
https://github.com/brandontrabucco/da-fusion
공식 코드https://github.com/brcsomnath/Advanced-GAP
공식 코드SIMILARnet: Simultaneous Intelligent Localization and Recognition Network
https://github.com/brian-moser/dartsrenet
공식 코드https://github.com/brjathu/SKD
공식 코드Self-supervised Knowledge Distillation for Few-shot Learning
https://github.com/brown-palm/syntheory
공식 코드https://github.com/bruceyo/V-PETL
공식 코드Towards a Unified View on Visual Parameter-Efficient Transfer Learning
https://github.com/bryanplummer/ssn
공식 코드https://github.com/bryanwong17/mil-feature-extractor-selection
공식 코드https://github.com/brycexu/BNN_Kernel
공식 코드https://github.com/btekgit/AdaptiveCNN
공식 코드https://github.com/btsmart/bootstrapping-label-noise
공식 코드Bootstrapping the Relationship Between Images and Their Clean and Noisy Labels
https://github.com/bupt-ai-cz/HSA-NRL
공식 코드Hard Sample Aware Noise Robust Learning for Histopathology Image Classification
https://github.com/bupt-ai-cz/PGDF
공식 코드Sample Prior Guided Robust Model Learning to Suppress Noisy Labels
https://github.com/buttomnutstoast/Multigrid-Neural-Architectures
공식 코드https://github.com/by-liu/cals
공식 코드https://github.com/by-liu/mbls
공식 코드The Devil is in the Margin: Margin-based Label Smoothing for Network Calibration
https://github.com/bychao100/towards-image-compression-and-analysis-with-transformers
공식 코드Towards End-to-End Image Compression and Analysis with Transformers
https://github.com/bychen515/glit
공식 코드GLiT: Neural Architecture Search for Global and Local Image Transformer
https://github.com/byeongjokim/VIPriors-Image-Classification-Challenge
공식 코드https://github.com/bytedance/TWIST
공식 코드Self-Supervised Learning by Estimating Twin Class Distributions
https://github.com/bytedance/ibot
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.