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 5351–5400 of 10420 papers

TitleStatusHype
A Novel Explainable Artificial Intelligence Model in Image Classification problem—0
Adversarial Attacks for Tabular Data: Application to Fraud Detection and Imbalanced Data—0
Efficient Super Resolution Using Binarized Neural Network—0
Efficient Sparse Artificial Neural Networks—0
A Novel Deep ML Architecture by Integrating Visual Simultaneous Localization and Mapping (vSLAM) into Mask R-CNN for Real-time Surgical Video Analysis—0
Efficient Scale-Permuted Backbone with Learned Resource Distribution—0
Check Your Other Door! Creating Backdoor Attacks in the Frequency Domain—0
A Novel Deep Learning Architecture for Testis Histology Image Classification—0
Adversarial Attacks for Optical Flow-Based Action Recognition Classifiers—0
Efficient Quantum Convolutional Neural Networks for Image Classification: Overcoming Hardware Constraints—0
Efficient Progressive Neural Architecture Search—0
Efficient, probabilistic analysis of combinatorial neural codes—0
Efficient Privacy-Preserving KAN Inference Using Homomorphic Encryption—0
Deep Learning-Driven Approach for Handwritten Chinese Character Classification—0
Efficient Privacy Preserving Edge Computing Framework for Image Classification—0
Efficient Post-Training Augmentation for Adaptive Inference in Heterogeneous and Distributed IoT Environments—0
Channel Pruning via Multi-Criteria based on Weight Dependency—0
A Novel BGCapsule Network for Text Classification—0
Efficient non-uniform quantizer for quantized neural network targeting reconfigurable hardware—0
Efficient Neural Vision Systems Based on Convolutional Image Acquisition—0
Efficient Neural Network Training via Subset Pretraining—0
Channel Compression: Rethinking Information Redundancy among Channels in CNN Architecture—0
Efficient Neural Architecture Transformation Search in Channel-Level for Object Detection—0
Efficient Neural Architecture Transformation Searchin Channel-Level for Object Detection—0
Breast Cancer Histopathology Classification using CBAM-EfficientNetV2 with Transfer Learning—0
Chain of Thought Prompt Tuning in Vision Language Models—0
A Novel Automated Classification and Segmentation for COVID-19 using 3D CT Scans—0
A Novel Approach using CapsNet and Deep Belief Network for Detection and Identification of Oral Leukopenia—0
Adversarial Attacks and Defences for Skin Cancer Classification—0
A Stable, Fast, and Fully Automatic Learning Algorithm for Predictive Coding Networks—0
An Efficient Pre-processing Method to Eliminate Adversarial Effects—0
Factorized Higher-Order CNNs with an Application to Spatio-Temporal Emotion Estimation—0
Efficient multivariate sequence classification—0
A Novel Approach to Breast Cancer Histopathological Image Classification Using Cross-Colour Space Feature Fusion and Quantum-Classical Stack Ensemble Method—0
Efficient Multi-Model Fusion with Adversarial Complementary Representation Learning—0
Efficient Multilingual Multi-modal Pre-training through Triple Contrastive Loss—0
Cervical Cancer Detection Using Multi-Branch Deep Learning Model—0
Adversarial Attack Against Images Classification based on Generative Adversarial Networks—0
Efficient Model Performance Estimation via Feature Histories—0
Certified robustness against physically-realizable patch attack via randomized cropping—0
Efficient Model-Agnostic Multi-Group Equivariant Networks—0
Efficient Maximal Coding Rate Reduction by Variational Forms—0
Certified robustness against adversarial patch attacks via randomized cropping—0
A Novel Approach for Classification and Forecasting of Time Series in Particle Accelerators—0
Efficient Masked Autoencoders with Self-Consistency—0
Efficiently utilizing complex-valued PolSAR image data via a multi-task deep learning framework—0
Efficient Lung Cancer Image Classification and Segmentation Algorithm Based on Improved Swin Transformer—0
Efficient Large Scale Video Classification—0
Certified Defences Against Adversarial Patch Attacks on Semantic Segmentation—0
A Novel ANN Structure for Image Recognition—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
10Meta Pseudo Labels (EfficientNet-B6-Wide)Top 1 Accuracy90—Unverified