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 7351–7400 of 10420 papers

TitleStatusHype
A general approach to compute the relevance of middle-level input features—0
A Comparative Study on Efficiencies of Variants of Convolutional Neural Networks based on Image Classification TaskCode0
Does Data Augmentation Benefit from Split BatchNorms—0
LiteDepthwiseNet: An Extreme Lightweight Network for Hyperspectral Image Classification—0
Why Layer-Wise Learning is Hard to Scale-up and a Possible Solution via Accelerated Downsampling—0
Improved Multi-Source Domain Adaptation by Preservation of Factors—0
Ferrograph image classification—0
Effects of the Nonlinearity in Activation Functions on the Performance of Deep Learning ModelsCode0
An Evasion Attack against Stacked Capsule AutoencoderCode0
Deep Ensembles for Low-Data Transfer Learning—0
Human-interpretable model explainability on high-dimensional data—0
Few-shot Action Recognition with Implicit Temporal Alignment and Pair Similarity Optimization—0
Are all negatives created equal in contrastive instance discrimination?—0
RMDL: Recalibrated multi-instance deep learning for whole slide gastric image classification—0
Tensor Train Factorization and Completion under Noisy Data with Prior Analysis and Rank EstimationCode0
Robust Two-Stream Multi-Feature Network for Driver Drowsiness Detection—0
A Very Compact Embedded CNN Processor Design Based on Logarithmic Computing—0
Satellite Image Classification with Deep Learning—0
CC-Loss: Channel Correlation Loss For Image Classification—0
Beyond the Attention: Distinguish the Discriminative and Confusable Features For Fine-grained Image Classification—0
Increasing the Robustness of Semantic Segmentation Models with Painting-by-Numbers—0
Webly Supervised Image Classification with Metadata: Automatic Noisy Label Correction via Visual-Semantic GraphCode0
ByzShield: An Efficient and Robust System for Distributed TrainingCode0
Block-term Tensor Neural Networks—0
Explaining Clinical Decision Support Systems in Medical Imaging using Cycle-Consistent Activation Maximization—0
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
5Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2—Unverified
6DaViT-HTop 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