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 5251–5300 of 10420 papers

TitleStatusHype
Enhanced Gradient for Differentiable Architecture Search—0
Enhanced Attacks on Defensively Distilled Deep Neural Networks—0
Classification and Retrieval of Digital Pathology Scans: A New Dataset—0
An Overview on Data Representation Learning: From Traditional Feature Learning to Recent Deep Learning—0
Energy-entropy competition and the effectiveness of stochastic gradient descent in machine learning—0
Classification and reconstruction of spatially overlapping phase images using diffractive optical networks—0
Energy-Efficient Model Compression and Splitting for Collaborative Inference Over Time-Varying Channels—0
Energy Efficient Hardware for On-Device CNN Inference via Transfer Learning—0
Classification Accuracy Improvement for Neuromorphic Computing Systems with One-level Precision Synapses—0
Adversarial attacks to image classification systems using evolutionary algorithms—0
Energy Efficient Hadamard Neural Networks—0
Energy-Efficient Deployment of Machine Learning Workloads on Neuromorphic Hardware—0
Classes Are Not Equal: An Empirical Study on Image Recognition Fairness—0
Energy-Efficient Classification at the Wireless Edge with Reliability Guarantees—0
Energy-Efficient and Federated Meta-Learning via Projected Stochastic Gradient Ascent—0
Class Distance Weighted Cross Entropy Loss for Classification of Disease Severity—0
Energy-efficient Amortized Inference with Cascaded Deep Classifiers—0
Energy-constrained Self-training for Unsupervised Domain Adaptation—0
Energy-Based Spherical Sparse Coding—0
End-to-end training of deep kernel map networks for image classification—0
A Novel Weight-Shared Multi-Stage CNN for Scale Robustness—0
Adversarial Attacks to Direct Data-driven Control for Destabilization—0
A Comprehensive Review of Image Analysis Methods for Microorganism Counting: From Classical Image Processing to Deep Learning Approaches—0
A 1Mb mixed-precision quantized encoder for image classification and patch-based compression—0
End-to-end optimized image compression for multiple machine tasks—0
End-to-End Optimization of JPEG-Based Deep Learning Process for Image Classification—0
End-to-End Kernel Learning with Supervised Convolutional Kernel Networks—0
End-to-End Anti-Backdoor Learning on Images and Time Series—0
Endoscopy Classification Model Using Swin Transformer and Saliency Map—0
A Novel Vision Transformer with Residual in Self-attention for Biomedical Image Classification—0
Encoding High Dimensional Local Features by Sparse Coding Based Fisher Vectors—0
Encoding Hierarchical Information in Neural Networks helps in Subpopulation Shift—0
Encoders and Ensembles for Task-Free Continual Learning—0
Class Attention to Regions of Lesion for Imbalanced Medical Image Recognition—0
A Novel Time Series-to-Image Encoding Approach for Weather Phenomena Classification—0
Encoder Based Lifelong Learning—0
Class-agnostic Object Detection—0
EncodeNet: A Framework for Boosting DNN Accuracy with Entropy-driven Generalized Converting Autoencoder—0
A novel statistical metric learning for hyperspectral image classification—0
Adversarial Attacks on Image Classification Models: Analysis and Defense—0
A Comprehensive Review of Generative AI in Healthcare—0
Enabling Small Models for Zero-Shot Selection and Reuse through Model Label Learning—0
Enabling Efficient Processing of Spiking Neural Networks with On-Chip Learning on Commodity Neuromorphic Processors for Edge AI Systems—0
Enabling Deep Learning on Edge Devices through Filter Pruning and Knowledge Transfer—0
CLAMP: Contrastive LAnguage Model Prompt-tuning—0
A novel spatial-frequency domain network for zero-shot incremental learning—0
Empowering Vision Transformers with Multi-Scale Causal Intervention for Long-Tailed Image Classification—0
CLAF: Contrastive Learning with Augmented Features for Imbalanced Semi-Supervised Learning—0
Empowering Networks With Scale and Rotation Equivariance Using A Similarity Convolution—0
A Novel Solution of an Elastic Net Regularization for Dementia Knowledge Discovery using Deep 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
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