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 5401–5450 of 10420 papers

TitleStatusHype
Adversarial Attack across Datasets—0
Efficient Key-Based Adversarial Defense for ImageNet by Using Pre-trained Model—0
Efficient Hyperparameter Importance Assessment for CNNs—0
Agnostic Multi-Robust Learning Using ERM—0
A novel adversarial learning strategy for medical image classification—0
Centroid Transformers: Learning to Abstract with Attention—0
Centroid-based deep metric learning for speaker recognition—0
An Out-of-the-box Full-network Embedding for Convolutional Neural Networks—0
Adversarial Alignment of Class Prediction Uncertainties for Domain Adaptation—0
Efficient Fully Distributed Federated Learning with Adaptive Local Links—0
Efficient Fine-Tuning with Domain Adaptation for Privacy-Preserving Vision Transformer—0
Efficient Few-Shot Medical Image Analysis via Hierarchical Contrastive Vision-Language Learning—0
TransMed: Large Language Models Enhance Vision Transformer for Biomedical Image Classification—0
On the Implicit Bias Towards Minimal Depth of Deep Neural Networks—0
Efficient feature embedding of 3D brain MRI images for content-based image retrieval with deep metric learning—0
Efficient Document Image Classification Using Region-Based Graph Neural Network—0
CELNet: Evidence Localization for Pathology Images using Weakly Supervised Learning—0
Adversarial Doodles: Interpretable and Human-drawable Attacks Provide Describable Insights—0
A Comparison of Self-Supervised Pretraining Approaches for Predicting Disease Risk from Chest Radiograph Images—0
4Weed Dataset: Annotated Imagery Weeds Dataset—0
Efficient detection of adversarial images—0
Efficient Deep Representation Learning by Adaptive Latent Space Sampling—0
An OpenCL(TM) Deep Learning Accelerator on Arria 10—0
Efficient Deep Learning Infrastructures for Embedded Computing Systems: A Comprehensive Survey and Future Envision—0
A Non-Technical Survey on Deep Convolutional Neural Network Architectures—0
Efficient Converted Spiking Neural Network for 3D and 2D Classification—0
Efficient Computation of Quantized Neural Networks by −1, +1 Encoding Decomposition—0
CE-Dedup: Cost-Effective Convolutional Neural Nets Training based on Image Deduplication—0
Efficient CNNs via Passive Filter Pruning—0
A Non-monotonic Smooth Activation Function—0
CEC-CNN: A Consecutive Expansion-Contraction Convolutional Network for Very Small Resolution Medical Image Classification—0
A non-discriminatory approach to ethical deep learning—0
Adv-Bot: Realistic Adversarial Botnet Attacks against Network Intrusion Detection Systems—0
A Comparison of Few-Shot Learning Methods for Underwater Optical and Sonar Image Classification—0
Efficient Annotation for Medical Image Analysis: A One-Pass Selective Annotation Approach—0
Test-time Adaptation in the Dynamic World with Compound Domain Knowledge Management—0
Efficient and Reliable Overlay Networks for Decentralized Federated Learning—0
An Once-for-All Budgeted Pruning Framework for ConvNets Considering Input Resolution—0
Efficient and Flexible Method for Reducing Moderate-size Deep Neural Networks with Condensation—0
CC-Loss: Channel Correlation Loss For Image Classification—0
Efficient Adaptive Ensembling for Image Classification—0
Efficient Adaptation of Pre-trained Vision Transformer underpinned by Approximately Orthogonal Fine-Tuning Strategy—0
CCESAR: Coastline Classification-Extraction From SAR Images Using CNN-U-Net Combination—0
Anomaly Unveiled: Securing Image Classification against Adversarial Patch Attacks—0
Efficient Active Learning for Image Classification and Segmentation using a Sample Selection and Conditional Generative Adversarial Network—0
Efficacy of Pixel-Level OOD Detection for Semantic Segmentation—0
CBVLM: Training-free Explainable Concept-based Large Vision Language Models for Medical Image Classification—0
Effects of Image Degradations to CNN-based Image Classification—0
Effects of Auxiliary Knowledge on Continual Learning—0
Anomaly Detection in Image Datasets Using Convolutional Neural Networks, Center Loss, and Mahalanobis Distance—0
Show:102550
← PrevPage 109 of 209Next →
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