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 6451–6500 of 10420 papers

TitleStatusHype
Modelling Multi-modal Cross-interaction for ML-FSIC Based on Local Feature Selection—0
ModelLock: Locking Your Model With a Spell—0
Geometry aware convolutional filters for omnidirectional images representation—0
Byzantines can also Learn from History: Fall of Centered Clipping in Federated Learning—0
Models Developed for Spiking Neural Networks—0
Convolutional neural networks compression with low rank and sparse tensor decompositions—0
Model Specialization for Inference Via End-to-End Distillation, Pruning, and Cascades—0
ModelVerification.jl: a Comprehensive Toolbox for Formally Verifying Deep Neural Networks—0
Modern Neural Networks Generalize on Small Data Sets—0
Modified Diversity of Class Probability Estimation Co-training for Hyperspectral Image Classification—0
Multi-task Dictionary Learning based Convolutional Neural Network for Computer aided Diagnosis with Longitudinal Images—0
Reinforcement Based Learning on Classification Task Could Yield Better Generalization and Adversarial Accuracy—0
Multi-task Image Classification via Collaborative, Hierarchical Spike-and-Slab Priors—0
Geometric Scattering for Graph Data Analysis—0
Geometric Neural Phrase Pooling: Modeling the Spatial Co-occurrence of Neurons—0
Asymmetric Duos: Sidekicks Improve Uncertainty—0
Geometric Median Matching for Robust k-Subset Selection from Noisy Data—0
MoKD: Multi-Task Optimization for Knowledge Distillation—0
Geometric Mean Improves Loss For Few-Shot Learning—0
MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images—0
Convolutional Neural Networks and Vision Transformers for Fashion MNIST Classification: A Literature Review—0
Agile Modeling: From Concept to Classifier in Minutes—0
Asymmetric Distribution Measure for Few-shot Learning—0
Convolutional Neural Network Pruning Using Filter Attenuation—0
Geodesics of learned representations—0
Convolutional Neural Network Compression through Generalized Kronecker Product Decomposition—0
Multi-Subspace Neural Network for Image Recognition—0
Multi-task Learning on MNIST Image Datasets—0
Asymmetric Diffusion Based Channel-Adaptive Secure Wireless Semantic Communications—0
Convolutional neural network classification of cancer cytopathology images: taking breast cancer as an example—0
Active Learning in Video Tracking—0
Monotonicity as a requirement and as a regularizer: efficient methods and applications—0
Monotonicity Regularization: Improved Penalties and Novel Applications to Disentangled Representation Learning and Robust Classification—0
Monotonic Neural Network: combining Deep Learning with Domain Knowledge for Chiller Plants Energy Optimization—0
Monte Carlo Deep Neural Network Arithmetic—0
Monte-Carlo Sampling applied to Multiple Instance Learning for Histological Image Classification—0
GenMix: Effective Data Augmentation with Generative Diffusion Model Image Editing—0
GenMix: Combining Generative and Mixture Data Augmentation for Medical Image Classification—0
Convolutional Neural Fabrics—0
Multisource Collaborative Domain Generalization for Cross-Scene Remote Sensing Image Classification—0
Genetic Programming-Based Evolutionary Deep Learning for Data-Efficient Image Classification—0
More for Less: Compact Convolutional Transformers Enable Robust Medical Image Classification with Limited Data—0
Rectifying Open-set Object Detection: A Taxonomy, Practical Applications, and Proper Evaluation—0
More Side Information, Better Pruning: Shared-Label Classification as a Case Study—0
Convolutional Low-Resolution Fine-Grained Classification—0
GeneSys: Enabling Continuous Learning through Neural Network Evolution in Hardware—0
Convolutional Kernel Networks—0
DRO-Augment Framework: Robustness by Synergizing Wasserstein Distributionally Robust Optimization and Data Augmentation—0
An Extendable, Efficient and Effective Transformer-based Object Detector—0
Asymmetric Co-Training with Explainable Cell Graph Ensembling for Histopathological Image Classification—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