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 96519675 of 10420 papers

TitleStatusHype
Adversarial Training for Relation Extraction0
Multi-task Dictionary Learning based Convolutional Neural Network for Computer aided Diagnosis with Longitudinal Images0
Boosting with Lexicographic Programming: Addressing Class Imbalance without Cost TuningCode0
Learning Invariant Riemannian Geometric Representations Using Deep Nets0
Explainable Artificial Intelligence: Understanding, Visualizing and Interpreting Deep Learning Models0
Imbalanced Malware Images Classification: a CNN based Approach0
Evaluation of Deep Learning on an Abstract Image Classification Dataset0
Ease.ml: Towards Multi-tenant Resource Sharing for Machine Learning Workloads0
Non-linear Convolution Filters for CNN-based Learning0
Application of a Convolutional Neural Network for image classification to the analysis of collisions in High Energy PhysicsCode0
Learning Efficient Convolutional Networks through Network SlimmingCode2
Towards Automatic Construction of Diverse, High-quality Image Dataset0
Dilated Deep Residual Network for Image Denoising0
Practical Block-wise Neural Network Architecture GenerationCode0
Power Optimizations in MTJ-based Neural Networks through Stochastic Computing0
Random Erasing Data AugmentationCode2
Improved Regularization of Convolutional Neural Networks with CutoutCode1
Style2Vec: Representation Learning for Fashion Items from Style SetsCode0
ZOO: Zeroth Order Optimization based Black-box Attacks to Deep Neural Networks without Training Substitute ModelsCode0
Image Quality Assessment Guided Deep Neural Networks TrainingCode0
Modality-bridge Transfer Learning for Medical Image Classification0
Analysis of Convolutional Neural Networks for Document Image Classification0
Regularizing and Optimizing LSTM Language ModelsCode1
Unsupervised Representation Learning by Sorting SequencesCode0
ProjectionNet: Learning Efficient On-Device Deep Networks Using Neural Projections0
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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
5DaViT-HTop 1 Accuracy90.2Unverified
6Meta Pseudo Labels (EfficientNet-L2)Top 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