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 8576–8600 of 10420 papers

TitleStatusHype
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
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
10RevCol-HTop 1 Accuracy90—Unverified