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 4901–4950 of 10420 papers

TitleStatusHype
Deep Learning and Medical Imaging for COVID-19 Diagnosis: A Comprehensive Survey—0
A Unified View of Long-Sequence Models towards Modeling Million-Scale Dependencies—0
How to Use Dropout Correctly on Residual Networks with Batch NormalizationCode0
Scientific Computing with Diffractive Optical Neural Networks—0
LiT Tuned Models for Efficient Species DetectionCode0
NephroNet: A Novel Program for Identifying Renal Cell Carcinoma and Generating Synthetic Training Images with Convolutional Neural Networks and Diffusion Models—0
Scaling Vision Transformers to 22 Billion ParametersCode0
Text recognition on images using pre-trained CNN—0
Context Understanding in Computer Vision: A Survey—0
GMConv: Modulating Effective Receptive Fields for Convolutional Kernels—0
On Function-Coupled Watermarks for Deep Neural NetworksCode0
On the Ideal Number of Groups for Isometric Gradient Propagation—0
Multipath agents for modular multitask ML systems—0
CECT: Controllable Ensemble CNN and Transformer for COVID-19 Image ClassificationCode0
Rethinking Robust Contrastive Learning from the Adversarial PerspectiveCode0
Semantic-Guided Generative Image Augmentation Method with Diffusion Models for Image Classification—0
Knowledge Distillation in Vision Transformers: A Critical Review—0
Cluster-CAM: Cluster-Weighted Visual Interpretation of CNNs' Decision in Image Classification—0
Example-Based Explainable AI and its Application for Remote Sensing Image Classification—0
Revisiting Long-tailed Image Classification: Survey and Benchmarks with New Evaluation Metrics—0
Learning a Fourier Transform for Linear Relative Positional Encodings in Transformers—0
Spiking Synaptic Penalty: Appropriate Penalty Term for Energy-Efficient Spiking Neural Networks—0
SoK: A Systematic Evaluation of Backdoor Trigger Characteristics in Image Classification—0
On the Efficacy of Differentially Private Few-shot Image ClassificationCode0
On Suppressing Range of Adaptive Stepsizes of Adam to Improve Generalisation Performance—0
FV-MgNet: Fully Connected V-cycle MgNet for Interpretable Time Series Forecasting—0
Structured mutation inspired by evolutionary theory enriches population performance and diversity—0
Weight Prediction Boosts the Convergence of AdamW—0
Deep Dependency Networks for Multi-Label Classification—0
Image-Based Vehicle Classification by Synergizing Features from Supervised and Self-Supervised Learning Paradigms—0
Reverse engineering adversarial attacks with fingerprints from adversarial examples—0
NASiam: Efficient Representation Learning using Neural Architecture Search for Siamese NetworksCode0
Does Deep Active Learning Work in the Wild?—0
Rethinking Soft Label in Label Distribution Learning Perspective—0
Inference Time Evidences of Adversarial Attacks for Forensic on Transformers—0
Transfer Learning and Class Decomposition for Detecting the Cognitive Decline of Alzheimer Disease—0
Training with Mixed-Precision Floating-Point Assignments—0
Equivariant Differentially Private Deep Learning: Why DP-SGD Needs Sparser ModelsCode0
NeSyFOLD: Neurosymbolic Framework for Interpretable Image ClassificationCode0
Language-Driven Anchors for Zero-Shot Adversarial RobustnessCode0
Identifying Adversarially Attackable and Robust SamplesCode0
Lateralized Learning for Multi-Class Visual Classification Tasks—0
DAFD: Domain Adaptation via Feature Disentanglement for Image Classification—0
Massively Scaling Heteroscedastic Classifiers—0
The Influences of Color and Shape Features in Visual Contrastive Learning—0
Anticipate, Ensemble and Prune: Improving Convolutional Neural Networks via Aggregated Early Exits—0
Supervision Complexity and its Role in Knowledge Distillation—0
MetaNO: How to Transfer Your Knowledge on Learning Hidden Physics—0
PECAN: A Deterministic Certified Defense Against Backdoor Attacks—0
Explore the Power of Dropout on Few-shot Learning—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