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 7551–7575 of 10420 papers

TitleStatusHype
A Methodology to Study the Impact of Spiking Neural Network Parameters considering Event-Based Automotive Data—0
PRKAN: Parameter-Reduced Kolmogorov-Arnold Networks—0
Adaptive Ensemble Learning: Boosting Model Performance through Intelligent Feature Fusion in Deep Neural Networks—0
Deep Learning and Medical Imaging for COVID-19 Diagnosis: A Comprehensive Survey—0
Inplace knowledge distillation with teacher assistant for improved training of flexible deep neural networks—0
Deep Learning and Machine Learning, Advancing Big Data Analytics and Management: Tensorflow Pretrained Models—0
InPK: Infusing Prior Knowledge into Prompt for Vision-Language Models—0
Probabilistic Label Trees for Efficient Large Scale Image Classification—0
In-Memory Nearest Neighbor Search with FeFET Multi-Bit Content-Addressable Memories—0
Probabilistic Model-Based Dynamic Architecture Search—0
Probabilistic Spatial Analysis in Quantitative Microscopy with Uncertainty-Aware Cell Detection using Deep Bayesian Regression of Density Maps—0
Deep learning and hand-crafted features for virus image classification—0
Initializing Perturbations in Multiple Directions for Fast Adversarial Training—0
Probability Guided Loss for Long-Tailed Multi-Label Image Classification—0
Initialization Using Perlin Noise for Training Networks with a Limited Amount of Data—0
Deep learning and face recognition: the state of the art—0
Backdoor Attack Detection in Computer Vision by Applying Matrix Factorization on the Weights of Deep Networks—0
Probing Network Decisions: Capturing Uncertainties and Unveiling Vulnerabilities Without Label Information—0
Initialization Noise in Image Gradients and Saliency Maps—0
Problem-dependent attention and effort in neural networks with applications to image resolution and model selection—0
Deep Learning Algorithms with Applications to Video Analytics for A Smart City: A Survey—0
In-Hindsight Quantization Range Estimation for Quantized Training—0
Informed Non-convex Robust Principal Component Analysis with Features—0
Deep Learning Algorithms for Early Diagnosis of Acute Lymphoblastic Leukemia—0
Informative Robust Causal Representation for Generalizable 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