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 8201–8250 of 10420 papers

TitleStatusHype
A Programmable Approach to Neural Network CompressionCode0
Towards Large yet Imperceptible Adversarial Image Perturbations with Perceptual Color DistanceCode0
Hyperspectral Image Classification via Sparse Representation With Incremental DictionariesCode0
Coverage Guided Testing for Recurrent Neural Networks—0
A Spectral Nonlocal Block for Neural Networks—0
An Algorithm for Routing Capsules in All Domains—0
Self-Adaptive Scaling for Learnable Residual Structure—0
Adaptive Precision Training: Quantify Back Propagation in Neural Networks with Fixed-point Numbers—0
Very high resolution Airborne PolSAR Image Classification using Convolutional Neural Networks—0
ALERT: Accurate Learning for Energy and Timeliness—0
Hierarchical Expert Networks for Meta-Learning—0
Are Out-of-Distribution Detection Methods Effective on Large-Scale Datasets?—0
Deep Metric Learning-Based Feature Embedding for Hyperspectral Image ClassificationCode0
Decomposable-Net: Scalable Low-Rank Compression for Neural NetworksCode0
Best Practices for Convolutional Neural Networks Applied to Object Recognition in Images—0
LeanConvNets: Low-cost Yet Effective Convolutional Neural Networks—0
Training Set Effect on Super Resolution for Automated Target Recognition—0
Neighborhood Watch: Representation Learning with Local-Margin Triplet Loss and Sampling Strategy for K-Nearest-Neighbor Image Classification—0
Secure Evaluation of Quantized Neural Networks—0
Shoestring: Graph-Based Semi-Supervised Learning with Severely Limited Labeled DataCode0
Asynchronous Decentralized SGD with Quantized and Local Updates—0
Spectral Algorithm for Low-rank Multitask Regression—0
Deep Learning for Hyperspectral Image Classification: An Overview—0
LPRNet: Lightweight Deep Network by Low-rank Pointwise Residual Convolution—0
Adversarial Feature Alignment: Avoid Catastrophic Forgetting in Incremental Task Lifelong Learning—0
Q-GADMM: Quantized Group ADMM for Communication Efficient Decentralized Machine Learning—0
Occlusions for Effective Data Augmentation in Image Classification—0
Detecting Out-of-Distribution Inputs in Deep Neural Networks Using an Early-Layer OutputCode0
Wasserstein Smoothing: Certified Robustness against Wasserstein Adversarial Attacks—0
Structure Matters: Towards Generating Transferable Adversarial Images—0
Kernel computations from large-scale random features obtained by Optical Processing UnitsCode0
Improving the Gating Mechanism of Recurrent Neural NetworksCode0
Improving singing voice separation with the Wave-U-Net using Minimum Hyperspherical EnergyCode0
Abnormal Client Behavior Detection in Federated Learning—0
Recovering Localized Adversarial Attacks—0
Self-supervised classification of dynamic obstacles using the temporal information provided by videos—0
Boosting Mapping Functionality of Neural Networks via Latent Feature Generation based on Reversible Learning—0
Hyperspectral Image Classification Based on Adaptive Sparse Deep Network—0
Boosting Network Weight Separability via Feed-Backward Reconstruction—0
Differentiable Deep Clustering with Cluster Size Constraints—0
Image recognition from raw labels collected without annotatorsCode0
NASIB: Neural Architecture Search withIn Budget—0
MixModule: Mixed CNN Kernel Module for Medical Image Segmentation—0
Reflecting After Learning for Understanding—0
Differentiable Combinatorial Losses through Generalized Gradients of Linear Programs—0
Texture Bias Of CNNs Limits Few-Shot Classification Performance—0
Toward Metrics for Differentiating Out-of-Distribution SetsCode0
KerCNNs: biologically inspired lateral connections for classification of corrupted images—0
Semi-supervised Learning using Adversarial Training with Good and Bad Samples—0
Effect of Superpixel Aggregation on Explanations in LIME -- A Case Study with Biological DataCode0
Show:102550
← PrevPage 165 of 209Next →
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