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

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Showing 1901–1950 of 10419 papers

TitleStatusHype
InceptionCapsule: Inception-Resnet and CapsuleNet with self-attention for medical image Classification—0
Segment Any Change—0
Deep Continuous NetworksCode0
Faster Inference of Integer SWIN Transformer by Removing the GELU Activation—0
Direct side information learning for zero-shot regressionCode0
Hybrid Quantum Vision Transformers for Event Classification in High Energy Physics—0
CADICA: a new dataset for coronary artery disease detection by using invasive coronary angiography—0
A Single Graph Convolution Is All You Need: Efficient Grayscale Image ClassificationCode1
Dendritic Learning-incorporated Vision Transformer for Image RecognitionCode1
HyperZZW Operator Connects Slow-Fast Networks for Full Context InteractionCode0
Dataset Condensation Driven Machine UnlearningCode0
Towards Image Semantics and Syntax Sequence LearningCode0
Towards Physical Plausibility in Neuroevolution SystemsCode0
Deep Learning-Driven Approach for Handwritten Chinese Character Classification—0
Category-wise Fine-Tuning: Resisting Incorrect Pseudo-Labels in Multi-Label Image Classification with Partial LabelsCode1
GraphViz2Vec: A Structure-aware Feature Generation Model to Improve Classification in GNNs—0
Selection of gamma events from IACT images with deep learning methods—0
SHViT: Single-Head Vision Transformer with Memory Efficient Macro DesignCode2
Generating Multi-Center Classifier via Conditional Gaussian DistributionCode0
Few and Fewer: Learning Better from Few Examples Using Fewer Base ClassesCode0
Exploring the Transferability of a Foundation Model for Fundus Images: Application to Hypertensive Retinopathy—0
MixMobileNet: A Mixed Mobile Network for Edge Vision Applications—0
Additional Look into GAN-based Augmentation for Deep Learning COVID-19 Image Classification—0
Memory-Inspired Temporal Prompt Interaction for Text-Image Classification—0
Revisiting Active Learning in the Era of Vision Foundation ModelsCode1
Exploring the Unexplored: Understanding the Impact of Layer Adjustments on Image Classification—0
An Ultralightweight Hybrid CNN Based on Redundancy Removal for Hyperspectral Image Classification—0
CNN architecture extraction on edge GPU—0
LDCA: Local Descriptors with Contextual Augmentation for Few-Shot Learning—0
DDI-CoCo: A Dataset For Understanding The Effect Of Color Contrast In Machine-Assisted Skin Disease DetectionCode0
Catch-Up Mix: Catch-Up Class for Struggling Filters in CNN—0
Interpreting Equivariant Representations—0
Leveraging Chat-Based Large Vision Language Models for Multimodal Out-Of-Context Detection—0
OnDev-LCT: On-Device Lightweight Convolutional Transformers towards federated learning—0
Rethinking Centered Kernel Alignment in Knowledge DistillationCode1
Medical Image Debiasing by Learning Adaptive Agreement from a Biased CouncilCode0
TIM: An Efficient Temporal Interaction Module for Spiking Transformer—0
Augmenting Prototype Network with TransMix for Few-shot Hyperspectral Image ClassificationCode0
Parametric Matrix Models—0
PlasmoData.jl -- A Julia Framework for Modeling and Analyzing Complex Data as GraphsCode1
Density Adaptive Attention is All You Need: Robust Parameter-Efficient Fine-Tuning Across Multiple ModalitiesCode1
I-SplitEE: Image classification in Split Computing DNNs with Early ExitsCode0
Learned Image resizing with efficient training (LRET) facilitates improved performance of large-scale digital histopathology image classification models—0
One Step Learning, One Step ReviewCode0
Enhancing Small Object Encoding in Deep Neural Networks: Introducing Fast&Focused-Net with Volume-wise Dot Product Layer—0
On-Off Pattern Encoding and Path-Count Encoding as Deep Neural Network Representations—0
Land Cover Image ClassificationCode0
Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space ModelCode2
Scalable Pre-training of Large Autoregressive Image ModelsCode5
Explanations of Classifiers Enhance Medical Image Segmentation via End-to-end Pre-training—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