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

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Showing 4251–4275 of 10420 papers

TitleStatusHype
Learning by Self-ExplainingCode0
Biased Attention: Do Vision Transformers Amplify Gender Bias More than Convolutional Neural Networks?Code0
Continual Learning with Deep Streaming Regularized Discriminant AnalysisCode0
Personalized Food Image Classification: Benchmark Datasets and New Baseline—0
Dynamic Spectrum Mixer for Visual Recognition—0
Mitigating Group Bias in Federated Learning for Heterogeneous Devices—0
Deep Nonparametric Convexified Filtering for Computational Photography, Image Synthesis and Adversarial Defense—0
LCReg: Long-Tailed Image Classification with Latent Categories based Recognition—0
Contrastive Deep Encoding Enables Uncertainty-aware Machine-learning-assisted Histopathology—0
OLID I: an open leaf image dataset for plant stress recognition—0
Strong-Weak Integrated Semi-supervision for Unsupervised Single and Multi Target Domain Adaptation—0
Accelerating Deep Neural Networks via Semi-Structured Activation Sparsity—0
Padding-free Convolution based on Preservation of Differential Characteristics of Kernels—0
Computer Vision Pipeline for Automated Antarctic Krill Analysis—0
GlobalDoc: A Cross-Modal Vision-Language Framework for Real-World Document Image Retrieval and Classification—0
Gall Bladder Cancer Detection from US Images with Only Image Level LabelsCode0
SABLE: Secure And Byzantine robust LEarning—0
Distance-Aware eXplanation Based LearningCode0
TMComposites: Plug-and-Play Collaboration Between Specialized Tsetlin MachinesCode0
HAct: Out-of-Distribution Detection with Neural Net Activation Histograms—0
RR-CP: Reliable-Region-Based Conformal Prediction for Trustworthy Medical Image Classification—0
Adversarial attacks on hybrid classical-quantum Deep Learning models for Histopathological Cancer Detection—0
Representation Synthesis by Probabilistic Many-Valued Logic Operation in Self-Supervised Learning—0
Privacy Preserving Federated Learning with Convolutional Variational Bottlenecks—0
Decoding visual brain representations from electroencephalography through Knowledge Distillation and latent diffusion modelsCode0
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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