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 3301–3350 of 10419 papers

TitleStatusHype
An Intelligent Hybrid Model for Identity Document Classification—0
State Classification of Cooking Objects Using a VGG CNN—0
Fast Adaptation with Bradley-Terry Preference Models in Text-To-Image Classification and Generation—0
Dynamic Deep Neural Networks: Optimizing Accuracy-Efficiency Trade-offs by Selective Execution—0
Dynamic Differential-Privacy Preserving SGD—0
Dynamic Early Exiting Predictive Coding Neural Networks—0
Dynamic Facial Analysis: From Bayesian Filtering to Recurrent Neural Network—0
Differential Privacy Mechanisms in Neural Tangent Kernel Regression—0
Dynamic Fusion based Federated Learning for COVID-19 Detection—0
Dynamic Game Theoretic Neural Optimizer—0
A Closer Look at Prototype Classifier for Few-shot Image Classification—0
1D-Convolutional Capsule Network for Hyperspectral Image Classification—0
Differential Privacy Analysis of Decentralized Gossip Averaging under Varying Threat Models—0
Differentially Private Video Activity Recognition—0
Dynamic Group Transformer: A General Vision Transformer Backbone with Dynamic Group Attention—0
Dynamic Inference with Neural Interpreters—0
CapsNet comparative performance evaluation for image classification—0
Dynamic Memory-enhanced Transformer for Hyperspectral Image Classification—0
Fashion and Apparel Classification using Convolutional Neural Networks—0
Fast Adaptation with Linearized Neural Networks—0
Fast and Balanced: Efficient Label Tree Learning for Large Scale Object Recognition—0
Finding Optimal Kernel Size and Dimension in Convolutional Neural Networks An Architecture Optimization Approach—0
Dynamic Neural Network Channel Execution for Efficient Training—0
Dynamic Object Comprehension: A Framework For Evaluating Artificial Visual Perception—0
Differentially Private Meta-Learning—0
Dynamic Perturbation-Adaptive Adversarial Training on Medical Image Classification—0
Ancient Coin Classification Using Graph Transduction Games—0
Differentially Private Federated Learning via Inexact ADMM with Multiple Local Updates—0
3D/2D regularized CNN feature hierarchy for Hyperspectral image classification—0
Fall Leaf Adversarial Attack on Traffic Sign Classification—0
Differentially Private Federated Learning via Inexact ADMM—0
Dynamic Scheduling for Vehicle-to-Vehicle Communications Enhanced Federated Learning—0
Dynamic Shuffle: An Efficient Channel Mixture Method—0
Dynamic Spectrum Mixer for Visual Recognition—0
Topology-aware Differential Privacy for Decentralized Image Classification—0
Differentiable Spike: Rethinking Gradient-Descent for Training Spiking Neural Networks—0
Biologically inspired sleep algorithm for increased generalization and adversarial robustness in deep neural networks—0
Additional Look into GAN-based Augmentation for Deep Learning COVID-19 Image Classification—0
Cascaded Cross-Attention Networks for Data-Efficient Whole-Slide Image Classification Using Transformers—0
Early Detection and Classification of Breast Cancer Using Deep Learning Techniques—0
Cascaded Recurrent Neural Networks for Hyperspectral Image Classification—0
Fine-grained Image Classification by Exploring Bipartite-Graph Labels—0
Fantope Regularization in Metric Learning—0
Differentiable Search for Finding Optimal Quantization Strategy—0
Plug-in, Trainable Gate for Streamlining Arbitrary Neural Networks—0
Biologically inspired deep residual networks for computer vision applications—0
Biologically Inspired Deep Learning Approaches for Fetal Ultrasound Image Classification—0
Eating Habits Discovery in Egocentric Photo-streams—0
Anchor Cascade for Efficient Face Detection—0
Differentiable Deep Clustering with Cluster Size Constraints—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