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 5051–5100 of 10420 papers

TitleStatusHype
A Framework for Generalizing Critical Heat Flux Detection Models Using Unsupervised Image-to-Image Translation—0
Test-time Adaptation in the Dynamic World with Compound Domain Knowledge Management—0
Better May Not Be Fairer: A Study on Subgroup Discrepancy in Image ClassificationCode0
Instance-dependent Label Distribution Estimation for Learning with Label NoiseCode0
Scattering-induced entropy boost for highly-compressed optical sensing and encryption—0
From Xception to NEXcepTion: New Design Decisions and Neural Architecture SearchCode0
Bayesian posterior approximation with stochastic ensemblesCode0
Backdoor Attack Detection in Computer Vision by Applying Matrix Factorization on the Weights of Deep Networks—0
CLIPPO: Image-and-Language Understanding from Pixels Only—0
Learning to Detect Semantic Boundaries with Image-level Class Labels—0
SAIF: Sparse Adversarial and Imperceptible Attack Framework—0
Design-time Fashion Popularity Forecasting in VR Environments—0
Losses over Labels: Weakly Supervised Learning via Direct Loss ConstructionCode0
Adversarial Attacks and Defences for Skin Cancer Classification—0
CAT: Learning to Collaborate Channel and Spatial Attention from Multi-Information Fusion—0
Can a face tell us anything about an NBA prospect? -- A Deep Learning approach—0
Synthetic Image Data for Deep Learning—0
Quantum Phase Recognition using Quantum Tensor Networks—0
A Neural ODE Interpretation of Transformer Layers—0
Using Multiple Instance Learning to Build Multimodal Representations—0
General Adversarial Defense Against Black-box Attacks via Pixel Level and Feature Level Distribution Alignments—0
Analysis of Explainable Artificial Intelligence Methods on Medical Image Classification—0
Algorithmic progress in computer vision—0
Expeditious Saliency-guided Mix-up through Random Gradient ThresholdingCode0
Dual adaptive training of photonic neural networks—0
Reminding Forgetful Organic Neuromorphic Device Networks—0
An AI-Powered VVPAT Counter for Elections in IndiaCode0
Co-training 2^L Submodels for Visual Recognition—0
Frugal Reinforcement-based Active Learning—0
EEG-NeXt: A Modernized ConvNet for The Classification of Cognitive Activity from EEG—0
A New Linear Scaling Rule for Private Adaptive Hyperparameter Optimization—0
Models Developed for Spiking Neural Networks—0
Development Of A Fire Detection System On Satellite Images—0
Improved Deep Neural Network Generalization Using m-Sharpness-Aware Minimization—0
Straggler-Resilient Differentially-Private Decentralized Learning—0
Mixer: DNN Watermarking using Image Mixup—0
Attend Who is Weak: Pruning-assisted Medical Image Localization under Sophisticated and Implicit Imbalances—0
Location-Aware Self-Supervised Transformers for Semantic Segmentation—0
I2MVFormer: Large Language Model Generated Multi-View Document Supervision for Zero-Shot Image Classification—0
Quantum Federated Learning with Entanglement Controlled Circuits and Superposition Coding—0
Kernel Inversed Pyramidal Resizing Network for Efficient Pavement Distress Recognition—0
ConfounderGAN: Protecting Image Data Privacy with Causal Confounder—0
Beyond ADMM: A Unified Client-variance-reduced Adaptive Federated Learning Framework—0
Compound Batch Normalization for Long-tailed Image Classification—0
Faster Adaptive Federated Learning—0
Are Straight-Through gradients and Soft-Thresholding all you need for Sparse Training?Code0
Evaluation of Explanation Methods of AI -- CNNs in Image Classification Tasks with Reference-based and No-reference MetricsCode0
SolarDK: A high-resolution urban solar panel image classification and localization dataset—0
Exploiting Kernel Compression on BNNs—0
Experimental Observations of the Topology of Convolutional Neural Network Activations—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