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 7601–7650 of 10420 papers

TitleStatusHype
Maximum Entropy Regularization and Chinese Text Recognition—0
Learning to Reweight with Deep Interactions—0
StyPath: Style-Transfer Data Augmentation For Robust Histology Image ClassificationCode0
AUSN: Approximately Uniform Quantization by Adaptively Superimposing Non-uniform Distribution for Deep Neural Networks—0
Consistency Regularization with Generative Adversarial Networks for Semi-Supervised Learning—0
Classification with 2-D Convolutional Neural Networks for breast cancer diagnosisCode0
C2G-Net: Exploiting Morphological Properties for Image Classification—0
Deep Reinforcement Learning and its Neuroscientific Implications—0
Learning the Prediction Distribution for Semi-Supervised Learning with Normalising FlowsCode0
Learning Embeddings for Image Clustering: An Empirical Study of Triplet Loss Approaches—0
Bespoke vs. Prêt-à-Porter Lottery Tickets: Exploiting Mask Similarity for Trainable Sub-Network Finding—0
Deep Learning for Apple Diseases: Classification and Identification—0
Weakly Supervised Domain Adaptation for Built-up Region Segmentation in Aerial and Satellite ImageryCode0
On Connections between Regularizations for Improving DNN Robustness—0
Surrogate-assisted Particle Swarm Optimisation for Evolving Variable-length Transferable Blocks for Image Classification—0
CacheNet: A Model Caching Framework for Deep Learning Inference on the Edge—0
Selecting Regions of Interest in Large Multi-Scale Images for Cancer Pathology—0
Self-supervised Neural Architecture Search—0
Interactive Knowledge Distillation—0
Increasing Trustworthiness of Deep Neural Networks via Accuracy Monitoring—0
Towards Robust Deep Learning with Ensemble Networks and Noisy Layers—0
Self-Supervised GAN CompressionCode0
Are there any 'object detectors' in the hidden layers of CNNs trained to identify objects or scenes?Code0
Channel Compression: Rethinking Information Redundancy among Channels in CNN Architecture—0
A Novel BGCapsule Network for Text Classification—0
A deep primal-dual proximal network for image restoration—0
Learning ordered pooling weights in image classificationCode0
Image Analysis Based on Nonnegative/Binary Matrix Factorization—0
Estimation with Uncertainty via Conditional Generative Adversarial Networks—0
Robust and Accurate Authorship Attribution via Program Normalization—0
Language to Network: Conditional Parameter Adaptation with Natural Language Descriptions—0
Robustifying the Deployment of tinyML Models for Autonomous mini-vehicles—0
SeqVAT: Virtual Adversarial Training for Semi-Supervised Sequence Labeling—0
HACT-Net: A Hierarchical Cell-to-Tissue Graph Neural Network for Histopathological Image Classification—0
Extracurricular Learning: Knowledge Transfer Beyond Empirical Distribution—0
Training highly effective connectivities within neural networks with randomly initialized, fixed weightsCode0
Explainable 3D Convolutional Neural Networks by Learning Temporal Transformations—0
Conditional Classification: A Solution for Computational Energy Reduction—0
Matrix Shuffle-Exchange Networks for Hard 2D TasksCode0
Harnessing Adversarial Distances to Discover High-Confidence ErrorsCode0
Active Ensemble Deep Learning for Polarimetric Synthetic Aperture Radar Image Classification—0
Compositional Convolutional Neural Networks: A Robust and Interpretable Model for Object Recognition under Occlusion—0
Performing Image Classification for 10 Different Monkey Species using CNN—0
Frequency learning for image classification—0
Unsupervised Deep Representation Learning and Few-Shot Classification of PolSAR Images—0
An Evoked Potential-Guided Deep Learning Brain Representation For Visual Classification—0
ReMarNet: Conjoint Relation and Margin Learning for Small-Sample Image ClassificationCode0
End-to-end training of deep kernel map networks for image classification—0
Not all Failure Modes are Created Equal: Training Deep Neural Networks for Explicable (Mis)Classification—0
​4S-DT: Self Supervised Super Sample Decomposition for Transfer learning with application to COVID-19 detection—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