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
Fundamental Limits of Transfer Learning in Binary Classifications—0
A Novel Site-Agnostic Multimodal Deep Learning Model to Identify Pro-Eating Disorder Content on Social Media—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 Novel Solution of an Elastic Net Regularization for Dementia Knowledge Discovery using Deep Learning—0
Function-Space Variational Inference for Deep Bayesian Classification—0
Continual Learning with Bayesian Model based on a Fixed Pre-trained Feature Extractor—0
Function-Space Regularization for Deep Bayesian Classification—0
On Space Folds of ReLU Neural Networks—0
On Study of the Binarized Deep Neural Network for Image Classification—0
A study of the effect of JPG compression on adversarial images—0
On the ability of CNNs to extract color invariant intensity based features for image classification—0
OReole-FM: successes and challenges toward billion-parameter foundation models for high-resolution satellite imagery—0
Enabling Deep Learning on Edge Devices through Filter Pruning and Knowledge Transfer—0
A Framework for Generalizing Critical Heat Flux Detection Models Using Unsupervised Image-to-Image Translation—0
On the benefits of robust models in modulation recognition—0
On the Calibration of Pre-trained Language Models using Mixup Guided by Area Under the Margin and Saliency—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
Active Generative Adversarial Network for Image Classification—0
On the Convergence of Nonconvex Continual Learning with Adaptive Learning Rate—0
On the Cost of Model-Serving Frameworks: An Experimental Evaluation—0
EncodeNet: A Framework for Boosting DNN Accuracy with Entropy-driven Generalized Converting Autoencoder—0
Fully Hyperbolic Convolutional Neural Networks—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
10RevCol-HTop 1 Accuracy90—Unverified