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 4151–4200 of 10420 papers

TitleStatusHype
Déjà Vu Memorization in Vision-Language Models—0
Benchmarks for Image Classification and Other High-dimensional Pattern Recognition Problems—0
Benchmarking the Robustness of Semantic Segmentation Models—0
Analysis of convolutional neural network image classifiers in a rotationally symmetric model—0
Deformation-Invariant Neural Network and Its Applications in Distorted Image Restoration and Analysis—0
Benchmarking Test-Time Unsupervised Deep Neural Network Adaptation on Edge Devices—0
Deformable Gabor Feature Networks for Biomedical Image Classification—0
Analysis of convolutional neural network image classifiers in a hierarchical max-pooling model with additional local pooling—0
Adaptive Sharpness-Aware Pruning for Robust Sparse Networks—0
ACIL: Active Class Incremental Learning for Image Classification—0
High Quality Remote Sensing Image Super-Resolution Using Deep Memory Connected Network—0
DeformableFormer: Classification of Endoscopic Ultrasound Guided Fine Needle Biopsy in Pancreatic Diseases—0
DefMamba: Deformable Visual State Space Model—0
SNR and Resource Adaptive Deep JSCC for Distributed IoT Image Classification—0
Defining Quantum Neural Networks via Quantum Time Evolution—0
Deferred Poisoning: Making the Model More Vulnerable via Hessian Singularization—0
Adaptive Selection of Deep Learning Models on Embedded Systems—0
HIGHLY EFFICIENT 8-BIT LOW PRECISION INFERENCE OF CONVOLUTIONAL NEURAL NETWORKS—0
Defensive Tensorization: Randomized Tensor Parametrization for Robust Neural Networks—0
Defensive Tensorization—0
Benchmarking PathCLIP for Pathology Image Analysis—0
Analysis of Catastrophic Forgetting for Random Orthogonal Transformation Tasks in the Overparameterized Regime—0
Benchmarking Multi-Domain Active Learning on Image Classification—0
Higher Order Transformers: Efficient Attention Mechanism for Tensor Structured Data—0
High Frequency Residual Learning for Multi-Scale Image Classification—0
Highly Efficient Forward and Backward Propagation of Convolutional Neural Networks for Pixelwise Classification—0
Defending Malware Classification Networks Against Adversarial Perturbations with Non-Negative Weight Restrictions—0
Post-train Black-box Defense via Bayesian Boundary Correction—0
Benchmarking MedMNIST dataset on real quantum hardware—0
Defending Against Universal Perturbations With Shared Adversarial Training—0
Analysis Dictionary Learning: An Efficient and Discriminative Solution—0
Adaptive sampling for scanning pixel cameras—0
Benchmarking Inference Performance of Deep Learning Models on Analog Devices—0
Defending Against Image Corruptions Through Adversarial Augmentations—0
Benchmarking FedAvg and FedCurv for Image Classification Tasks—0
Defending Adversaries Using Unsupervised Feature Clustering VAE—0
Exploring Optimal Deep Learning Models for Image-based Malware Variant Classification—0
Image and Point-cloud Classification for Jet Analysis in High-Energy Physics: A survey—0
Highly Efficient Representation and Active Learning Framework and Its Application to Imbalanced Medical Image Classification—0
Hilbert Curve Based Molecular Sequence Analysis—0
How do Convolutional Neural Networks Learn Design?—0
HQViT: Hybrid Quantum Vision Transformer for Image Classification—0
Hyperspectral Images Classification Based on Multi-scale Residual Network—0
DeepVO: A Deep Learning approach for Monocular Visual Odometry—0
Deep Visual Domain Adaptation: A Survey—0
Deep Visual Domain Adaptation—0
Hierarchical ResNeXt Models for Breast Cancer Histology Image Classification—0
Deep View-Sensitive Pedestrian Attribute Inference in an end-to-end Model—0
Hierarchical Recurrent Neural Encoder for Video Representation with Application to Captioning—0
Benchmarking Adversarial Robustness—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