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 7126–7150 of 10420 papers

TitleStatusHype
Conditional Networks—0
Divergence Regulated Encoder Network for Joint Dimensionality Reduction and ClassificationCode0
MS-GWNN:multi-scale graph wavelet neural network for breast cancer diagnosis—0
Black-box Adversarial Attacks on Monocular Depth Estimation Using Evolutionary Multi-objective Optimization—0
Automatic Detection and Image Recognition of Precision Agriculture for Citrus Diseases—0
Deep Visual Domain Adaptation—0
Screening COVID-19 Based on CT/CXR Images & Building a Publicly Available CT-scan Dataset of COVID-19—0
Playing to distraction: towards a robust training of CNN classifiers through visual explanation techniquesCode0
WHU-Hi: UAV-borne hyperspectral with high spatial resolution (H2) benchmark datasets for hyperspectral image classification—0
Coarse to Fine: Multi-label Image Classification with Global/Local Attention—0
Direct Quantization for Training Highly Accurate Low Bit-width Deep Neural Networks—0
CNNs for JPEGs: A Study in Computational Cost—0
Mixed-Privacy Forgetting in Deep Networks—0
Learning from Crowds by Modeling Common ConfusionsCode0
Coarse-to-Fine Object Tracking Using Deep Features and Correlation FiltersCode0
How Does a Neural Network's Architecture Impact Its Robustness to Noisy Labels?—0
A Survey on Visual Transformer—0
General Domain Adaptation Through Proportional Progressive Pseudo LabelingCode0
A Feasibility study for Deep learning based automated brain tumor segmentation using Magnetic Resonance Images—0
A Review of Artificial Intelligence Technologies for Early Prediction of Alzheimer's Disease—0
LQF: Linear Quadratic Fine-Tuning—0
ResizeMix: Mixing Data with Preserved Object Information and True Labels—0
Color Channel Perturbation Attacks for Fooling Convolutional Neural Networks and A Defense Against Such AttacksCode0
Semi-supervised Hyperspectral Image Classification with Graph Clustering Convolutional Networks—0
DISCO: Dynamic and Invariant Sensitive Channel Obfuscation for deep neural networks—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
5DaViT-HTop 1 Accuracy90.2—Unverified
6Meta Pseudo Labels (EfficientNet-L2)Top 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