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

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Showing 8751–8800 of 10420 papers

TitleStatusHype
Safeguarded Dynamic Label Regression for Generalized Noisy SupervisionCode0
Evolutionary Cell Aided Design for Neural Network Architectures—0
Detecting Overfitting via Adversarial Examples—0
Activation Atlas—0
Statistical Guarantees for the Robustness of Bayesian Neural NetworksCode0
Hyperspectral Image Classification with Deep Metric Learning and Conditional Random Field—0
Neural Networks Trained on Natural Scenes Exhibit Gestalt ClosureCode0
Semi-Supervised Brain Lesion Segmentation with an Adapted Mean Teacher ModelCode0
A Kernelized Manifold Mapping to Diminish the Effect of Adversarial PerturbationsCode0
Accelerating Training of Deep Neural Networks with a Standardization LossCode0
Quaternion Convolutional Neural NetworksCode0
A Novel Multi-Attention Driven System For Multi-Label Remote Sensing Image Classification—0
Cascaded Recurrent Neural Networks for Hyperspectral Image Classification—0
FixyNN: Efficient Hardware for Mobile Computer Vision via Transfer LearningCode0
Unsupervised Attention Mechanism across Neural Network LayersCode0
FickleNet: Weakly and Semi-supervised Semantic Image Segmentation using Stochastic Inference—0
The Best Defense Is a Good Offense: Adversarial Attacks to Avoid Modulation Detection—0
Disentangled Deep Autoencoding Regularization for Robust Image Classification—0
Tensor Dropout for Robust Learning—0
Unsupervised Part Mining for Fine-grained Image Classification—0
Recurrent Convolution for Compact and Cost-Adjustable Neural Networks: An Empirical Study—0
Diagnosis of Alzheimer's Disease via Multi-modality 3D Convolutional Neural Network—0
Learning Implicitly Recurrent CNNs Through Parameter SharingCode0
Learning a Deep ConvNet for Multi-label Classification with Partial Labels—0
Quantifying error contributions of computational steps, algorithms and hyperparameter choices in image classification pipelines—0
GFCN: A New Graph Convolutional Network Based on Parallel Flows—0
Visualization, Discriminability and Applications of Interpretable Saak Features—0
Image Classification on IoT Edge Devices: Profiling and Modeling—0
Discriminative Pattern Mining for Breast Cancer Histopathology Image Classification via Fully Convolutional Autoencoder—0
Image Aesthetics Assessment Using Composite Features from off-the-Shelf Deep Models—0
Quantifying contribution and propagation of error from computational steps, algorithms and hyperparameter choices in image classification pipelinesCode0
ComplexFace: a Multi-Representation Approach for Image Classification with Small Dataset—0
Wasserstein Adversarial Examples via Projected Sinkhorn IterationsCode1
Adversarial Augmentation for Enhancing Classification of Mammography ImagesCode0
Meta-Weight-Net: Learning an Explicit Mapping For Sample WeightingCode1
Perceptual Quality-preserving Black-Box Attack against Deep Learning Image ClassifiersCode0
Learning with Inadequate and Incorrect Supervision—0
Spatially-Adaptive Filter Units for Compact and Efficient Deep Neural NetworksCode0
Simplifying Graph Convolutional NetworksCode1
Adaptive Cross-Modal Few-Shot LearningCode0
LocalNorm: Robust Image Classification through Dynamically Regularized Normalization—0
Contextual Encoder-Decoder Network for Visual Saliency PredictionCode0
HybridSN: Exploring 3D-2D CNN Feature Hierarchy for Hyperspectral Image ClassificationCode0
Evolutionary Neural AutoML for Deep LearningCode1
Deep Generalized Convolutional Sum-Product NetworksCode0
Min-Entropy Latent Model for Weakly Supervised Object DetectionCode0
DC-AL GAN: Pseudoprogression and True Tumor Progression of Glioblastoma Multiform Image Classification Based on DCGAN and AlexNet—0
Bayesian Image Classification with Deep Convolutional Gaussian Processes—0
Graph-RISE: Graph-Regularized Image Semantic Embedding—0
Transfusion: Understanding Transfer Learning for Medical ImagingCode0
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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