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 5851–5900 of 10420 papers

TitleStatusHype
Directing DNNs Attention for Facial Attribution Classification using Gradient-weighted Class Activation Mapping—0
Direct Image Classification from Fourier Ptychographic Microscopy Measurements without Reconstruction—0
An Efficient and Small Convolutional Neural Network for Pest Recognition -- ExquisiteNet—0
DiRaC-I: Identifying Diverse and Rare Training Classes for Zero-Shot Learning—0
Blackbox Trojanising of Deep Learning Models : Using non-intrusive network structure and binary alterations—0
DINO-CXR: A self supervised method based on vision transformer for chest X-ray classification—0
Black Box to White Box: Discover Model Characteristics Based on Strategic Probing—0
DIME-FM : DIstilling Multimodal and Efficient Foundation Models—0
DIME-FM: DIstilling Multimodal and Efficient Foundation Models—0
An efficient and flexible inference system for serving heterogeneous ensembles of deep neural networks—0
Black Box Explanation by Learning Image Exemplars in the Latent Feature Space—0
Dilated Deep Residual Network for Image Denoising—0
Black-box adversarial attacks using Evolution Strategies—0
Black-box Adversarial Attacks on Monocular Depth Estimation Using Evolutionary Multi-objective Optimization—0
An Effective Label Noise Model for DNN Text Classification—0
An Effective Gram Matrix Characterizes Generalization in Deep Networks—0
Addressing Discrepancies in Semantic and Visual Alignment in Neural Networks—0
ACLS: Adaptive and Conditional Label Smoothing for Network Calibration—0
Diffusion models applied to skin and oral cancer classification—0
An Effective Fusion Method to Enhance the Robustness of CNN—0
Diff-SySC: An Approach Using Diffusion Models for Semi-Supervised Image Classification—0
DiffSpectralNet : Unveiling the Potential of Diffusion Models for Hyperspectral Image Classification—0
Bit-aware Randomized Response for Local Differential Privacy in Federated Learning—0
BiSSL: Enhancing the Alignment Between Self-Supervised Pretraining and Downstream Fine-Tuning via Bilevel Optimization—0
An Effective Anti-Aliasing Approach for Residual Networks—0
Additive Quantization for Extreme Vector Compression—0
Difficulty in estimating visual information from randomly sampled images—0
BIRD: Behavior Induction via Representation-structure Distillation—0
Differential Privacy Mechanisms in Neural Tangent Kernel Regression—0
Differential Privacy Analysis of Decentralized Gossip Averaging under Varying Threat Models—0
Differentially Private Video Activity Recognition—0
Android Malware Detection Based on RGB Images and Multi-feature Fusion—0
A Closer Look at Prototype Classifier for Few-shot Image Classification—0
Differentially Private Meta-Learning—0
Differentially Private Federated Learning via Inexact ADMM with Multiple Local Updates—0
Ancient Coin Classification Using Graph Transduction Games—0
Differentially Private Federated Learning via Inexact ADMM—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
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
Anchor Cascade for Efficient Face Detection—0
Differentiable Deep Clustering with Cluster Size Constraints—0
Differentiable Channel Sparsity Search via Weight Sharing within Filters—0
Differentiable Architecture Compression—0
L_2BN: Enhancing Batch Normalization by Equalizing the L_2 Norms of Features—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