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 8051–8100 of 10420 papers

TitleStatusHype
Improving the Gating Mechanism of Recurrent Neural NetworksCode0
Improving singing voice separation with the Wave-U-Net using Minimum Hyperspherical EnergyCode0
Structure Matters: Towards Generating Transferable Adversarial Images—0
Abnormal Client Behavior Detection in Federated Learning—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
Recovering Localized Adversarial Attacks—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
Toward Metrics for Differentiating Out-of-Distribution SetsCode0
Semi-supervised Learning using Adversarial Training with Good and Bad Samples—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
KerCNNs: biologically inspired lateral connections for classification of corrupted images—0
Effect of Superpixel Aggregation on Explanations in LIME -- A Case Study with Biological DataCode0
Deep Sub-Ensembles for Fast Uncertainty Estimation in Image ClassificationCode0
Do Explanations Reflect Decisions? A Machine-centric Strategy to Quantify the Performance of Explainability Algorithms—0
Consistency-based Semi-supervised Active Learning: Towards Minimizing Labeling Cost—0
MUTE: Data-Similarity Driven Multi-hot Target Encoding for Neural Network Design—0
Transfer Learning for Algorithm Recommendation—0
Optimizing Convolutional Neural Networks for Embedded Systems by Means of Neuroevolution—0
Scale-Equivariant Steerable NetworksCode0
DeepSearch: A Simple and Effective Blackbox Attack for Deep Neural NetworksCode0
A CNN-RNN Framework for Image Annotation from Visual Cues and Social Network Metadata—0
Generative Image Translation for Data Augmentation in Colorectal Histopathology ImagesCode0
Drop to Adapt: Learning Discriminative Features for Unsupervised Domain AdaptationCode0
Cross-Domain Image Classification through Neural-Style Transfer Data AugmentationCode0
Context-Gated ConvolutionCode0
Blink: Fast and Generic Collectives for Distributed ML—0
The Expressivity and Training of Deep Neural Networks: toward the Edge of Chaos?—0
Demon: Improved Neural Network Training with Momentum DecayCode0
Multi-Stage Pathological Image Classification using Semantic Segmentation—0
On the adequacy of untuned warmup for adaptive optimizationCode0
Cribriform pattern detection in prostate histopathological images using deep learning models—0
ECA-Net: Efficient Channel Attention for Deep Convolutional Neural NetworksCode2
Dynamic Mode Decomposition based feature for Image ClassificationCode0
Observer Dependent Lossy Image CompressionCode0
Deformable Kernels: Adapting Effective Receptive Fields for Object DeformationCode0
Deep Neural Network Compression for Image Classification and Object DetectionCode0
Deep Kernel Learning via Random Fourier Features—0
Algorithmic Probability-guided Supervised Machine Learning on Non-differentiable Spaces—0
Soft-Label Dataset Distillation and Text Dataset DistillationCode1
Covariance-free Partial Least Squares: An Incremental Dimensionality Reduction MethodCode0
Distributed Learning of Deep Neural Networks using Independent Subnet TrainingCode0
Tensor-based algorithms for image classificationCode0
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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