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 69767000 of 10420 papers

TitleStatusHype
Features based Mammogram Image Classification using Weighted Feature Support Vector Machine0
Multi-Level Graph Convolutional Network with Automatic Graph Learning for Hyperspectral Image Classification0
Adversarial Rain Attack and Defensive Deraining for DNN Perception0
Hyperspectral Image Classification Method Based on 2D–3D CNN and Multibranch Feature Fusion0
AdderSR: Towards Energy Efficient Image Super-Resolution0
Searching for Low-Bit Weights in Quantized Neural NetworksCode1
Generating Efficient DNN-Ensembles with Evolutionary Computation0
Noisy Concurrent Training for Efficient Learning under Label NoiseCode0
MoPro: Webly Supervised Learning with Momentum PrototypesCode1
MEAL V2: Boosting Vanilla ResNet-50 to 80%+ Top-1 Accuracy on ImageNet without TricksCode1
An Algorithm for Out-Of-Distribution Attack to Neural Network EncoderCode0
Deep Collective Learning: Learning Optimal Inputs and Weights Jointly in Deep Neural Networks0
Unsupervised Image Classification Through Time-Multiplexed Photonic Multi-Layer Spiking Convolutional Neural Network0
Eating Habits Discovery in Egocentric Photo-streams0
Feature Fusion via Multiresolution Compressive Measurement Matrix Analysis For Spectral Image ClassificationCode0
Classifying the Equation of State from Rotating Core Collapse Gravitational Waves with Deep Learning0
Constrained Labeling for Weakly Supervised LearningCode0
Ensemble learning of diffractive optical networks0
Puzzle Mix: Exploiting Saliency and Local Statistics for Optimal MixupCode1
A Visual Analytics Framework for Explaining and Diagnosing Transfer Learning ProcessesCode1
ResNet-like Architecture with Low Hardware RequirementsCode0
One-bit Supervision for Image ClassificationCode0
Adaptive Convolution Kernel for Artificial Neural NetworksCode0
Semi-supervised dictionary learning with graph regularization and active pointsCode0
Margin-Based Regularization and Selective Sampling in Deep Neural Networks0
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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