Image Classification

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.

Source: Metamorphic Testing for Object Detection Systems

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 881–890 of 10420 papers

Title	Date	Tasks	Status	Hype
Feature Guided Masked Autoencoder for Self-supervised Learning in Remote Sensing	Oct 28, 2023	Image ClassificationMulti-Label Image Classification	CodeCode Available	1
Feature Interaction Interpretability: A Case for Explaining Ad-Recommendation Systems via Neural Interaction Detection	Jun 19, 2020	BIG-bench Machine Learningimage-classification	CodeCode Available	1
FedCV: A Federated Learning Framework for Diverse Computer Vision Tasks	Nov 22, 2021	BenchmarkingFederated Learning	CodeCode Available	1
FedDC: Federated Learning with Non-IID Data via Local Drift Decoupling and Correction	Mar 22, 2022	Federated Learningimage-classification	CodeCode Available	1
Adversarial Attacks on ML Defense Models Competition	Oct 15, 2021	Adversarial AttackAdversarial Robustness	CodeCode Available	1
Federated Learning via Input-Output Collaborative Distillation	Dec 22, 2023	Federated Learningimage-classification	CodeCode Available	1
FedMLP: Federated Multi-Label Medical Image Classification under Task Heterogeneity	Jun 27, 2024	Federated Learningimage-classification	CodeCode Available	1
An Overview of Deep Learning Architectures in Few-Shot Learning Domain	Aug 12, 2020	Deep LearningFew-Shot Learning	CodeCode Available	1
ClusterFormer: Clustering As A Universal Visual Learner	Sep 22, 2023	Clusteringimage-classification	CodeCode Available	1
Clusterability as an Alternative to Anchor Points When Learning with Noisy Labels	Feb 10, 2021	Image ClassificationImage Classification with Human Noise	CodeCode Available	1

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All datasets ImageNet CIFAR-10 CIFAR-100 STL-10 ObjectNet MNIST SVHN iNaturalist 2018 ImageNet ReaL Flowers-102 Clothing1M mini WebVision 1.0

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	CoCa (finetuned)	Top 1 Accuracy	91	—	Unverified
2	Model soups (BASIC-L)	Top 1 Accuracy	90.98	—	Unverified
3	Model soups (ViT-G/14)	Top 1 Accuracy	90.94	—	Unverified
4	DaViT-G	Top 1 Accuracy	90.4	—	Unverified
5	Meta Pseudo Labels (EfficientNet-L2)	Top 1 Accuracy	90.2	—	Unverified
6	DaViT-H	Top 1 Accuracy	90.2	—	Unverified
7	SwinV2-G	Top 1 Accuracy	90.17	—	Unverified
8	MAWS (ViT-6.5B)	Top 1 Accuracy	90.1	—	Unverified
9	Florence-CoSwin-H	Top 1 Accuracy	90.05	—	Unverified
10	RevCol-H	Top 1 Accuracy	90	—	Unverified