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 7376–7400 of 10420 papers

TitleStatusHype
Understanding Local Robustness of Deep Neural Networks under Natural VariationsCode0
A Novel ANN Structure for Image Recognition—0
Brain-inspired predictive coding dynamics improve the robustness of deep neural networksCode0
Be Your Own Best Competitor! Multi-Branched Adversarial Knowledge Transfer—0
Uncertainty-Aware Few-Shot Image Classification—0
Evaluating the Effectiveness of Efficient Neural Architecture Search for Sentence-Pair Tasks—0
R-MnasNet: Reduced MnasNet for Computer Vision—0
Interlocking Backpropagation: Improving depthwise model-parallelismCode0
SLCRF: Subspace Learning with Conditional Random Field for Hyperspectral Image Classification—0
Variational Feature Disentangling for Fine-Grained Few-Shot Classification—0
Explanation and Use of Uncertainty Quantified by Bayesian Neural Network Classifiers for Breast Histopathology Images—0
Conversion and Implementation of State-of-the-Art Deep Learning Algorithms for the Classification of Diabetic Retinopathy—0
From Artificial Intelligence to Brain Intelligence: The basis learning and memory algorithm for brain-like intelligence—0
Visualizing Color-wise Saliency of Black-Box Image Classification Models—0
Domain Adaptive Transfer Learning on Visual Attention Aware Data Augmentation for Fine-grained Visual Categorization—0
Microscopic fine-grained instance classification through deep attention—0
Usable Information and Evolution of Optimal Representations During Training—0
Descriptive analysis of computational methods for automating mammograms with practical applications—0
Contrastive Cross-Modal Pre-Training: A General Strategy for Small Sample Medical Imaging—0
Exploring the Interchangeability of CNN Embedding Spaces—0
CO2: Consistent Contrast for Unsupervised Visual Representation Learning—0
Robust High-dimensional Memory-augmented Neural Networks—0
Mixup-Transformer: Dynamic Data Augmentation for NLP Tasks—0
Lipschitz Bounded Equilibrium Networks—0
Feature Whitening via Gradient Transformation for Improved Convergence—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