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 9301–9325 of 10420 papers

TitleStatusHype
Two Methods for Domain Adaptation of Bilingual Tasks: Delightfully Simple and Broadly ApplicableCode0
Fractional Wavelet Scattering Network and Applications—0
A Benchmark for Interpretability Methods in Deep Neural NetworksCode0
Understanding Dropout as an Optimization Trick—0
Generating Counterfactual Explanations with Natural Language—0
Constructing Deep Neural Networks by Bayesian Network Structure Learning—0
Defending Malware Classification Networks Against Adversarial Perturbations with Non-Negative Weight Restrictions—0
Considerations for a PAP Smear Image Analysis System with CNN Features—0
Pixel-level Reconstruction and Classification for Noisy Handwritten Bangla Characters—0
Finding Original Image Of A Sub Image Using CNNs—0
Inference of Quantized Neural Networks on Heterogeneous All-Programmable Devices—0
A convex method for classification of groups of examples—0
DPP-Net: Device-aware Progressive Search for Pareto-optimal Neural Architectures—0
Maximally Invariant Data Perturbation as ExplanationCode0
Classification of remote sensing images using attribute profiles and feature profiles from different trees: a comparative study—0
Non-Negative Networks Against Adversarial AttacksCode0
Recurrent Multiresolution Convolutional Networks for VHR Image Classification—0
Image classification and retrieval with random depthwise signed convolutional neural networksCode0
Three dimensional Deep Learning approach for remote sensing image classification—0
NetScore: Towards Universal Metrics for Large-scale Performance Analysis of Deep Neural Networks for Practical On-Device Edge Usage—0
GLoMo: Unsupervisedly Learned Relational Graphs as Transferable RepresentationsCode0
Efficient Active Learning for Image Classification and Segmentation using a Sample Selection and Conditional Generative Adversarial Network—0
Crowd-Powered Data Mining—0
Benchmarks for Image Classification and Other High-dimensional Pattern Recognition Problems—0
Human Activity Recognition Based on Wearable Sensor Data: A Standardization of the State-of-the-ArtCode0
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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