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 7051–7075 of 10420 papers

TitleStatusHype
Deep Neural Networks for Marine Debris Detection in Sonar Images—0
Batch Normalization: Accelerating Deep Network Training byReducing Internal Covariate Shift—0
On-Off Pattern Encoding and Path-Count Encoding as Deep Neural Network Representations—0
On Parameter Tuning in Meta-learning for Computer Vision—0
A Multi-resolution Model for Histopathology Image Classification and Localization with Multiple Instance Learning—0
Keep your distance: learning dispersed embeddings on S_m—0
Keep Your AI-es on the Road: Tackling Distracted Driver Detection with Convolutional Neural Networks and Targeted Data Augmentation—0
Deep Neural Networks Based Weight Approximation and Computation Reuse for 2-D Image Classification—0
On Space Folds of ReLU Neural Networks—0
On Study of the Binarized Deep Neural Network for Image Classification—0
Keep Learning: Self-supervised Meta-learning for Learning from Inference—0
On the ability of CNNs to extract color invariant intensity based features for image classification—0
On the Activation Function Dependence of the Spectral Bias of Neural Networks—0
Deep Neural Networks and PIDE discretizations—0
Keeping Representation Similarity in Finetuning for Medical Image Analysis—0
On the benefits of robust models in modulation recognition—0
Deep Neural Networks—0
On the Computational Inefficiency of Large Batch Sizes for Stochastic Gradient Descent—0
On the Confidence of Neural Network Predictions for some NLP Tasks—0
On the Convergence of Continual Learning with Adaptive Methods—0
KCRC-LCD: Discriminative Kernel Collaborative Representation with Locality Constrained Dictionary for Visual Categorization—0
Deep Neural Network Models Trained With A Fixed Random Classifier Transfer Better Across Domains—0
A Multiresolution Clinical Decision Support System Based on Fractal Model Design for Classification of Histological Brain Tumours—0
Adaptive Mixture of Low-Rank Factorizations for Compact Neural Modeling—0
KANs for Computer Vision: An Experimental Study—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