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 8551–8600 of 10420 papers

TitleStatusHype
Development Of A Fire Detection System On Satellite Images—0
Development of CNN Architectures using Transfer Learning Methods for Medical Image Classification—0
DevNet: A Deep Event Network for Multimedia Event Detection and Evidence Recounting—0
DFDG: Data-Free Dual-Generator Adversarial Distillation for One-Shot Federated Learning—0
DFDL: Discriminative Feature-oriented Dictionary Learning for Histopathological Image Classification—0
DFRD: Data-Free Robustness Distillation for Heterogeneous Federated Learning—0
Diabetic retinopathy image classification method based on GreenBen data augmentation—0
Diagnosing Convolutional Neural Networks using their Spectral Response—0
Diagnosis and Analysis of Celiac Disease and Environmental Enteropathy on Biopsy Images using Deep Learning Approaches—0
Diagnosis of Alzheimer's Disease via Multi-modality 3D Convolutional Neural Network—0
Diagnosis of Autism in Children using Facial Analysis and Deep Learning—0
Diagnosis of Skin Cancer Using VGG16 and VGG19 Based Transfer Learning Models—0
Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases in Women With Breast Cancer—0
Diagnostic Text-guided Representation Learning in Hierarchical Classification for Pathological Whole Slide Image—0
Diagram Image Retrieval using Sketch-Based Deep Learning and Transfer Learning—0
DIET-SNN: A Low-Latency Spiking Neural Network with Direct Input Encoding & Leakage and Threshold Optimization—0
DIET-SNN: Direct Input Encoding With Leakage and Threshold Optimization in Deep Spiking Neural Networks—0
Diff3Dformer: Leveraging Slice Sequence Diffusion for Enhanced 3D CT Classification with Transformer Networks—0
DiffCLIP: Leveraging Stable Diffusion for Language Grounded 3D Classification—0
L_2BN: Enhancing Batch Normalization by Equalizing the L_2 Norms of Features—0
Differentiable Architecture Compression—0
Differentiable Channel Sparsity Search via Weight Sharing within Filters—0
Differentiable Deep Clustering with Cluster Size Constraints—0
Plug-in, Trainable Gate for Streamlining Arbitrary Neural Networks—0
Differentiable Search for Finding Optimal Quantization Strategy—0
Differentiable Spike: Rethinking Gradient-Descent for Training Spiking Neural Networks—0
Topology-aware Differential Privacy for Decentralized Image Classification—0
Differentially Private Federated Learning via Inexact ADMM—0
Differentially Private Federated Learning via Inexact ADMM with Multiple Local Updates—0
Differentially Private Meta-Learning—0
Differentially Private Video Activity Recognition—0
Differential Privacy Analysis of Decentralized Gossip Averaging under Varying Threat Models—0
Differential Privacy Mechanisms in Neural Tangent Kernel Regression—0
Difficulty in estimating visual information from randomly sampled images—0
DiffSpectralNet : Unveiling the Potential of Diffusion Models for Hyperspectral Image Classification—0
Diff-SySC: An Approach Using Diffusion Models for Semi-Supervised Image Classification—0
Diffusion models applied to skin and oral cancer classification—0
Dilated Deep Residual Network for Image Denoising—0
DIME-FM: DIstilling Multimodal and Efficient Foundation Models—0
DIME-FM : DIstilling Multimodal and Efficient Foundation Models—0
DINO-CXR: A self supervised method based on vision transformer for chest X-ray classification—0
DiRaC-I: Identifying Diverse and Rare Training Classes for Zero-Shot Learning—0
Direct Image Classification from Fourier Ptychographic Microscopy Measurements without Reconstruction—0
Directing DNNs Attention for Facial Attribution Classification using Gradient-weighted Class Activation Mapping—0
Directional Gradient Projection for Robust Fine-Tuning of Foundation Models—0
Direct Quantization for Training Highly Accurate Low Bit-width Deep Neural Networks—0
Dirichlet-based Histogram Feature Transform for Image Classification—0
DiSa: Directional Saliency-Aware Prompt Learning for Generalizable Vision-Language Models—0
Disaggregated Deep Learning via In-Physics Computing at Radio Frequency—0
DISCO: Distributed Inference with Sparse Communications—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