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/etetteh/sota-data-augmentation-and-optimizers
Improved Regularization of Convolutional Neural Networks with Cutout
https://github.com/eth-pbl/tinyissimoyolo
Ultra-Efficient On-Device Object Detection on AI-Integrated Smart Glasses with TinyissimoYOLO
https://github.com/eth-sri/diffai
https://github.com/ethanbar11/ssm_2d
https://github.com/ethancaballero/Restricted_Boltzmann_Machine__RBM
https://github.com/ethanleet/CapsNet
https://github.com/ethanluoyc/transporter-pytorch
Unsupervised Learning of Object Keypoints for Perception and Control
https://github.com/ethz-spylab/rlhf_trojan_competition
Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback
https://github.com/etjoa003/explainable_ai
Improving Deep Neural Network Classification Confidence using Heatmap-based eXplainable AI
https://github.com/etmwb/cvsegmentation
https://github.com/etrommer/dcsr
https://github.com/etrulls/deepdesc-release
https://github.com/eunki7/flask-deeplearning-service-demo
https://github.com/euphoria0-0/Learning-Loss-for-Active-Learning
https://github.com/europa1610/Tensorflow-Shufflenet
ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices
https://github.com/evolvinglmms-lab/lmms-eval
MME-Survey: A Comprehensive Survey on Evaluation of Multimodal LLMs
https://github.com/ewinata/CIFAR-10
https://github.com/ex4sperans/freesound-classification
Improving Pairwise Ranking for Multi-label Image Classification
https://github.com/exekudos/se-resnet
https://github.com/expertailab/spaceqa
https://github.com/explainableml/loft
https://github.com/explainingai-code/VIT-Pytorch
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
https://github.com/exploring-curiosity/CovidPredictionML
Unveiling COVID-19 from Chest X-ray with deep learning: a hurdles race with small data
https://github.com/fL0n9/SKFAC-MindSpore
https://github.com/fabian57fabian/prototypical-networks-few-shot-learning
https://github.com/fabianwinter93/JAX
https://github.com/fabio-sim/Depth-Anything-ONNX
https://github.com/fabioasdias/ubao
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/fabiofumarola/ultrayolo
https://github.com/fabja19/rml
https://github.com/fabxy/accessibilityCV
https://github.com/fac2003/perceiver-multi-modality-pytorch
https://github.com/facebook/fb-caffe-exts
https://github.com/facebook/fb.resnet.torch
Some Improvements on Deep Convolutional Neural Network Based Image Classification
https://github.com/facebookarchive/fb.resnet.torch
Some Improvements on Deep Convolutional Neural Network Based Image Classification
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.