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 6051–6100 of 10420 papers

TitleStatusHype
1D-Convolutional Capsule Network for Hyperspectral Image Classification—0
Learn like a Pathologist: Curriculum Learning by Annotator Agreement for Histopathology Image Classification—0
Learning with SASQuaTCh: a Novel Variational Quantum Transformer Architecture with Kernel-Based Self-Attention—0
DFDG: Data-Free Dual-Generator Adversarial Distillation for One-Shot Federated Learning—0
Learning with Recursive Perceptual Representations—0
Learning with Noisy Ground Truth: From 2D Classification to 3D Reconstruction—0
DevNet: A Deep Event Network for Multimedia Event Detection and Evidence Recounting—0
Anatomy-specific classification of medical images using deep convolutional nets—0
Learning with Neighbor Consistency for Noisy Labels—0
Learning with Limited Samples -- Meta-Learning and Applications to Communication Systems—0
Learning with Label Noise for Image Retrieval by Selecting Interactions—0
Development of CNN Architectures using Transfer Learning Methods for Medical Image Classification—0
Learning with Inadequate and Incorrect Supervision—0
Low-Memory Neural Network Training: A Technical Report—0
Learning with Hierarchical Complement Objective—0
Low-rank features based double transformation matrices learning for image classification—0
Learning with Differentiable Algorithms—0
Development Of A Fire Detection System On Satellite Images—0
An Artificial Neural Network for Image Classification Inspired by Aversive Olfactory Learning Circuits in Caenorhabditis Elegans—0
Low Saturation Confidence Distribution-based Test-Time Adaptation for Cross-Domain Remote Sensing Image Classification—0
Learning with convolution and pooling operations in kernel methods—0
Continual Learning with Evolving Class Ontologies—0
Developing Convolutional Neural Networks using a Novel Lamarckian Co-Evolutionary Algorithm—0
Learning What Makes a Difference from Counterfactual Examples and Gradient Supervision—0
Learning What Data to Learn—0
Developing a Recommendation Benchmark for MLPerf Training and Inference—0
Learning Wake-Sleep Recurrent Attention Models—0
Learning Visual Conditioning Tokens to Correct Domain Shift for Fully Test-time Adaptation—0
DetNet: Design Backbone for Object Detection—0
Bias mitigation techniques in image classification: fair machine learning in human heritage collections—0
Learning transformer-based heterogeneously salient graph representation for multimodal remote sensing image classification—0
Learning to Utilize Correlated Auxiliary Noise: A Possible Quantum Advantage—0
An approach based on class activation maps for investigating the effects of data augmentation on neural networks for image classification—0
A Closed-Form Learned Pooling for Deep Classification Networks—0
MAAM: A Lightweight Multi-Agent Aggregation Module for Efficient Image Classification Based on the MindSpore Framework—0
MABViT -- Modified Attention Block Enhances Vision Transformers—0
Learning to Teach with Dynamic Loss Functions—0
Detection of Plant Leaf Disease Directly in the JPEG Compressed Domain using Transfer Learning Technique—0
Machine Learning and Thermography Applied to the Detection and Classification of Cracks in Building—0
Machine Learning-Based Jamun Leaf Disease Detection: A Comprehensive Review—0
Learning to Reweight with Deep Interactions—0
Machine Learning for Brain Disorders: Transformers and Visual Transformers—0
Machine learning for option pricing: an empirical investigation of network architectures—0
Learning to Teach—0
Detection of Non-uniformity in Parameters for Magnetic Domain Pattern Generation by Machine Learning—0
Learning to Specialize with Knowledge Distillation for Visual Question Answering—0
Learning and Sharing: A Multitask Genetic Programming Approach to Image Feature Learning—0
Machine learning with limited data—0
Learning to See Physical Properties with Active Sensing Motor Policies—0
Detection of Degraded Acacia tree species using deep neural networks on uav drone imagery—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