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 6976–7000 of 10420 papers

TitleStatusHype
Identifying Misinformation from Website Screenshots—0
Perceptually Constrained Adversarial Attacks—0
Naturalizing Neuromorphic Vision Event Streams Using GANs—0
Multi-class Generative Adversarial Nets for Semi-supervised Image Classification—0
Segmenting two-dimensional structures with strided tensor networksCode0
Depthwise Separable Convolutions Allow for Fast and Memory-Efficient Spectral Normalization—0
A Large Batch Optimizer Reality Check: Traditional, Generic Optimizers Suffice Across Batch Sizes—0
Detecting Localized Adversarial Examples: A Generic Approach using Critical Region Analysis—0
Distribution Adaptive INT8 Quantization for Training CNNs—0
WheaCha: A Method for Explaining the Predictions of Models of Code—0
Rationally Inattentive Utility Maximization for Interpretable Deep Image ClassificationCode0
Flow-Mixup: Classifying Multi-labeled Medical Images with Corrupted Labels—0
Soccer Event Detection Using Deep Learning—0
Mitigating belief projection in explainable artificial intelligence via Bayesian TeachingCode0
Privacy-Preserving Video Classification with Convolutional Neural Networks—0
Weight Rescaling: Effective and Robust Regularization for Deep Neural Networks with Batch Normalization—0
Achieving Explainability for Plant Disease Classification with Disentangled Variational Autoencoders—0
Hyperspherical embedding for novel class classification—0
On the Reproducibility of Neural Network Predictions—0
A Deeper Look into Convolutions via Eigenvalue-based PruningCode0
Deep reinforcement learning-based image classification achieves perfect testing set accuracy for MRI brain tumors with a training set of only 30 images—0
A Supervised Segmentation Network for Hyperspectral Image Classification—0
Multi-Instance Learning by Utilizing Structural Relationship among Instances—0
Deep CNNs for large scale species classification—0
Probabilistic Trust Intervals for Out of Distribution DetectionCode0
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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