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 8851–8900 of 10420 papers

TitleStatusHype
Unsupervised Deep Transfer Feature Learning for Medical Image Classification—0
Selective Kernel NetworksCode0
Superpixel Contracted Graph-Based Learning for Hyperspectral Image ClassificationCode0
Learning Dependency Structures for Weak Supervision Models—0
Improving Neural Architecture Search Image Classifiers via Ensemble LearningCode0
All You Need is a Few Shifts: Designing Efficient Convolutional Neural Networks for Image ClassificationCode0
DeepOBS: A Deep Learning Optimizer Benchmark SuiteCode0
Signal Demodulation with Machine Learning Methods for Physical Layer Visible Light Communications: Prototype Platform, Open Dataset and Algorithms—0
Spiking-YOLO: Spiking Neural Network for Energy-Efficient Object Detection—0
Image Classification base on PCA of Multi-view Deep Representation—0
Structured Knowledge Distillation for Dense PredictionCode0
Spatial-Aware Non-Local Attention for Fashion Landmark Detection—0
Using satellite image classification and digital terrain modelling to assess forest species distribution on mountain slopes.A case study in Varatec Forest District—0
Sliced Wasserstein Discrepancy for Unsupervised Domain AdaptationCode0
A Hybrid GA-PSO Method for Evolving Architecture and Short Connections of Deep Convolutional Neural Networks—0
Research on the pixel-based and object-oriented methods of urban feature extraction with GF-2 remote-sensing images—0
Inductive Transfer for Neural Architecture Optimization—0
Deep CNN-based Multi-task Learning for Open-Set RecognitionCode0
Label Embedded Dictionary Learning for Image ClassificationCode0
Analysis Dictionary Learning: An Efficient and Discriminative Solution—0
Weakly Supervised Complementary Parts Models for Fine-Grained Image Classification from the Bottom UpCode0
ViTOR: Learning to Rank Webpages Based on Visual Features—0
Activation Atlas—0
Detecting Overfitting via Adversarial Examples—0
Safeguarded Dynamic Label Regression for Generalized Noisy SupervisionCode0
Evolutionary Cell Aided Design for Neural Network Architectures—0
Statistical Guarantees for the Robustness of Bayesian Neural NetworksCode0
Semi-Supervised Brain Lesion Segmentation with an Adapted Mean Teacher ModelCode0
Hyperspectral Image Classification with Deep Metric Learning and Conditional Random Field—0
Neural Networks Trained on Natural Scenes Exhibit Gestalt ClosureCode0
Accelerating Training of Deep Neural Networks with a Standardization LossCode0
A Kernelized Manifold Mapping to Diminish the Effect of Adversarial PerturbationsCode0
Quaternion Convolutional Neural NetworksCode0
Cascaded Recurrent Neural Networks for Hyperspectral Image Classification—0
A Novel Multi-Attention Driven System For Multi-Label Remote Sensing Image Classification—0
FixyNN: Efficient Hardware for Mobile Computer Vision via Transfer LearningCode0
Disentangled Deep Autoencoding Regularization for Robust Image Classification—0
FickleNet: Weakly and Semi-supervised Semantic Image Segmentation using Stochastic Inference—0
Unsupervised Attention Mechanism across Neural Network LayersCode0
The Best Defense Is a Good Offense: Adversarial Attacks to Avoid Modulation Detection—0
Tensor Dropout for Robust Learning—0
Unsupervised Part Mining for Fine-grained Image Classification—0
Learning Implicitly Recurrent CNNs Through Parameter SharingCode0
Learning a Deep ConvNet for Multi-label Classification with Partial Labels—0
Diagnosis of Alzheimer's Disease via Multi-modality 3D Convolutional Neural Network—0
Recurrent Convolution for Compact and Cost-Adjustable Neural Networks: An Empirical Study—0
GFCN: A New Graph Convolutional Network Based on Parallel Flows—0
Quantifying error contributions of computational steps, algorithms and hyperparameter choices in image classification pipelines—0
Visualization, Discriminability and Applications of Interpretable Saak Features—0
Image Classification on IoT Edge Devices: Profiling and Modeling—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