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 3551–3575 of 10420 papers

TitleStatusHype
DFDG: Data-Free Dual-Generator Adversarial Distillation for One-Shot Federated Learning—0
DevNet: A Deep Event Network for Multimedia Event Detection and Evidence Recounting—0
Anatomy-specific classification of medical images using deep convolutional nets—0
Energy-efficient Amortized Inference with Cascaded Deep Classifiers—0
FickleNet: Weakly and Semi-supervised Semantic Image Segmentation using Stochastic Inference—0
Energy-Efficient Classification at the Wireless Edge with Reliability Guarantees—0
Energy-Efficient Deployment of Machine Learning Workloads on Neuromorphic Hardware—0
Energy Efficient Hadamard Neural Networks—0
Development of CNN Architectures using Transfer Learning Methods for Medical Image Classification—0
An Artificial Neural Network for Image Classification Inspired by Aversive Olfactory Learning Circuits in Caenorhabditis Elegans—0
Energy-entropy competition and the effectiveness of stochastic gradient descent in machine learning—0
Development Of A Fire Detection System On Satellite Images—0
Fighting Fire with Fire: Avoiding DNN Shortcuts through Priming—0
Classification and Retrieval of Digital Pathology Scans: A New Dataset—0
Enhanced Attacks on Defensively Distilled Deep Neural Networks—0
Enhanced Gradient for Differentiable Architecture Search—0
Developing Convolutional Neural Networks using a Novel Lamarckian Co-Evolutionary Algorithm—0
Enhanced Image Classification With Data Augmentation Using Position Coordinates—0
Enhanced Infield Agriculture with Interpretable Machine Learning Approaches for Crop Classification—0
Classification Driven Dynamic Image Enhancement—0
Developing a Recommendation Benchmark for MLPerf Training and Inference—0
Enhanced Object Detection via Fusion With Prior Beliefs from Image Classification—0
DetNet: Design Backbone for Object Detection—0
Enhanced Prototypical Part Network (EPPNet) For Explainable Image Classification Via Prototypes—0
Bias mitigation techniques in image classification: fair machine learning in human heritage collections—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