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

Showing 60766100 of 10420 papers

TitleStatusHype
Developing a Recommendation Benchmark for MLPerf Training and Inference0
Learning Wake-Sleep Recurrent Attention Models0
Learning Visual Conditioning Tokens to Correct Domain Shift for Fully Test-time Adaptation0
DetNet: Design Backbone for Object Detection0
Bias mitigation techniques in image classification: fair machine learning in human heritage collections0
Learning transformer-based heterogeneously salient graph representation for multimodal remote sensing image classification0
Learning to Utilize Correlated Auxiliary Noise: A Possible Quantum Advantage0
An approach based on class activation maps for investigating the effects of data augmentation on neural networks for image classification0
A Closed-Form Learned Pooling for Deep Classification Networks0
MAAM: A Lightweight Multi-Agent Aggregation Module for Efficient Image Classification Based on the MindSpore Framework0
MABViT -- Modified Attention Block Enhances Vision Transformers0
Learning to Teach with Dynamic Loss Functions0
Detection of Plant Leaf Disease Directly in the JPEG Compressed Domain using Transfer Learning Technique0
Machine Learning and Thermography Applied to the Detection and Classification of Cracks in Building0
Machine Learning-Based Jamun Leaf Disease Detection: A Comprehensive Review0
Learning to Reweight with Deep Interactions0
Machine Learning for Brain Disorders: Transformers and Visual Transformers0
Machine learning for option pricing: an empirical investigation of network architectures0
Learning to Teach0
Detection of Non-uniformity in Parameters for Magnetic Domain Pattern Generation by Machine Learning0
Learning to Specialize with Knowledge Distillation for Visual Question Answering0
Learning and Sharing: A Multitask Genetic Programming Approach to Image Feature Learning0
Machine learning with limited data0
Learning to See Physical Properties with Active Sensing Motor Policies0
Detection of Degraded Acacia tree species using deep neural networks on uav drone imagery0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CoCa (finetuned)Top 1 Accuracy91Unverified
2Model soups (BASIC-L)Top 1 Accuracy90.98Unverified
3Model soups (ViT-G/14)Top 1 Accuracy90.94Unverified
4DaViT-GTop 1 Accuracy90.4Unverified
5Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2Unverified
6DaViT-HTop 1 Accuracy90.2Unverified
7SwinV2-GTop 1 Accuracy90.17Unverified
8MAWS (ViT-6.5B)Top 1 Accuracy90.1Unverified
9Florence-CoSwin-HTop 1 Accuracy90.05Unverified
10RevCol-HTop 1 Accuracy90Unverified