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

Showing 83518375 of 10420 papers

TitleStatusHype
Invariant Risk MinimizationCode1
Blind Image Quality Assessment Using A Deep Bilinear Convolutional Neural NetworkCode0
Multi-Instance Multi-Scale CNN for Medical Image Classification0
FairNAS: Rethinking Evaluation Fairness of Weight Sharing Neural Architecture SearchCode0
Applying Transfer Learning To Deep Learned Models For EEG Analysis0
Low-Rank Subspace Override for Unsupervised Domain AdaptationCode0
An Automated Ensemble Learning Framework Using Genetic Programming for Image ClassificationCode0
Generating Natural Language Adversarial Examples through Probability Weighted Word SaliencyCode0
Learning to aggregate feature representations0
Single-Path Mobile AutoML: Efficient ConvNet Design and NAS Hyperparameter OptimizationCode0
Towards fully automated post-event data collection and analysis: pre-event and post-event information fusion0
Learning to Find Correlated Features by Maximizing Information Flow in Convolutional Neural Networks0
Fooling a Real Car with Adversarial Traffic Signs0
Unsupervised predictive coding models may explain visual brain representationCode0
Learning from Web Data with Self-Organizing Memory Module0
On the notion of number in humans and machinesCode0
Convolution Based Spectral Partitioning Architecture for Hyperspectral Image ClassificationCode0
On the performance of residual block design alternatives in convolutional neural networks for end-to-end audio classification0
One Size Does Not Fit All: Quantifying and Exposing the Accuracy-Latency Trade-off in Machine Learning Cloud Service APIs via Tolerance Tiers0
Learning Data Augmentation Strategies for Object DetectionCode1
AGAN: Towards Automated Design of Generative Adversarial Networks0
Active Learning Solution on Distributed Edge Computing0
Exploring Self-Supervised Regularization for Supervised and Semi-Supervised LearningCode0
Mixup of Feature Maps in a Hidden Layer for Training of Convolutional Neural Network0
Posterior-Guided Neural Architecture SearchCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CoCa (finetuned)Top 1 Accuracy91Unverified
2Model soups (BASIC-L)Top 1 Accuracy90.98Unverified
3Model soups (ViT-G/14)Top 1 Accuracy90.94Unverified
4DaViT-GTop 1 Accuracy90.4Unverified
5DaViT-HTop 1 Accuracy90.2Unverified
6Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2Unverified
7SwinV2-GTop 1 Accuracy90.17Unverified
8MAWS (ViT-6.5B)Top 1 Accuracy90.1Unverified
9Florence-CoSwin-HTop 1 Accuracy90.05Unverified
10RevCol-HTop 1 Accuracy90Unverified