SOTAVerified

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 AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 8001–8025 of 10420 papers

TitleStatusHype
Black Box Explanation by Learning Image Exemplars in the Latent Feature Space—0
Depthwise-STFT based separable Convolutional Neural Networks—0
¶ILCRO: Making Importance Landscapes Flat Again—0
Point-of-Care Diabetic Retinopathy Diagnosis: A Standalone Mobile Application Approach—0
A Fully Convolutional Normalization Approach of Head and Neck Cancer Outcome Prediction—0
Stochastic Optimization of Plain Convolutional Neural Networks with Simple methodsCode0
Optimized Generic Feature Learning for Few-shot Classification across Domains—0
Depthwise Non-local Module for Fast Salient Object Detection Using a Single Thread—0
AutoFCL: Automatically Tuning Fully Connected Layers for Handling Small DatasetCode0
Block-wise Scrambled Image Recognition Using Adaptation Network—0
GhostImage: Remote Perception Attacks against Camera-based Image Classification SystemsCode0
Spectral Pyramid Graph Attention Network for Hyperspectral Image Classification—0
Multiplication fusion of sparse and collaborative-competitive representation for image classificationCode0
SlideImages: A Dataset for Educational Image Classification—0
Code-Bridged Classifier (CBC): A Low or Negative Overhead Defense for Making a CNN Classifier Robust Against Adversarial Attacks—0
Relevance Prediction from Eye-movements Using Semi-interpretable Convolutional Neural Networks—0
Extending Class Activation Mapping Using Gaussian Receptive Field—0
Towards detection and classification of microscopic foraminifera using transfer learningCode0
Semi-supervised learning method based on predefined evenly-distributed class centroids—0
Multi-Complementary and Unlabeled Learning for Arbitrary Losses and Models—0
Boosting Occluded Image Classification via Subspace Decomposition Based Estimation of Deep FeaturesCode0
Bag of Tricks for Retail Product Image ClassificationCode0
Neural Data Server: A Large-Scale Search Engine for Transfer Learning Data—0
Fast Neural Network Adaptation via Parameter Remapping and Architecture SearchCode0
The Effect of Data Ordering in Image Classification—0
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All datasetsImageNetCIFAR-10CIFAR-100STL-10ObjectNetMNISTSVHNiNaturalist 2018ImageNet ReaLFlowers-102Clothing1Mmini WebVision 1.0

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CoCa (finetuned)Top 1 Accuracy91—Unverified
2Model soups (BASIC-L)Top 1 Accuracy90.98—Unverified
3Model soups (ViT-G/14)Top 1 Accuracy90.94—Unverified
4DaViT-GTop 1 Accuracy90.4—Unverified
5Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2—Unverified
6DaViT-HTop 1 Accuracy90.2—Unverified
7SwinV2-GTop 1 Accuracy90.17—Unverified
8MAWS (ViT-6.5B)Top 1 Accuracy90.1—Unverified
9Florence-CoSwin-HTop 1 Accuracy90.05—Unverified
10RevCol-HTop 1 Accuracy90—Unverified