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 7901–7950 of 10420 papers

TitleStatusHype
Ensemble learning in CNN augmented with fully connected subnetworksCode0
Efficient Deep Representation Learning by Adaptive Latent Space Sampling—0
LANCE: Efficient Low-Precision Quantized Winograd Convolution for Neural Networks Based on Graphics Processing Units—0
A Dynamic Reduction Network for Point CloudsCode0
Rectified Meta-Learning from Noisy Labels for Robust Image-based Plant Disease Diagnosis—0
Teacher-Student chain for efficient semi-supervised histology image classification—0
SiamSNN: Siamese Spiking Neural Networks for Energy-Efficient Object Tracking—0
Assessing Robustness to Noise: Low-Cost Head CT Triage—0
SlimConv: Reducing Channel Redundancy in Convolutional Neural Networks by Weights Flipping—0
Developing a Recommendation Benchmark for MLPerf Training and Inference—0
Deep Adaptive Semantic Logic (DASL): Compiling Declarative Knowledge into Deep Neural Networks—0
NoiseRank: Unsupervised Label Noise Reduction with Dependence Models—0
Stochastic gradient descent with random learning rate—0
A Simple Probabilistic Method for Deep Classification under Input-Dependent Label Noise—0
Policy-Based Federated LearningCode0
The GraphNet Zoo: An All-in-One Graph Based Deep Semi-Supervised Framework for Medical Image Classification—0
FrImCla: A Framework for Image Classification Using Traditional and Transfer Learning TechniquesCode0
Extended Batch Normalization—0
GPCA: A Probabilistic Framework for Gaussian Process Embedded Channel AttentionCode0
Learning to be Global Optimizer—0
LIMEADE: From AI Explanations to Advice TakingCode0
Implementation of Deep Neural Networks to Classify EEG Signals using Gramian Angular Summation Field for Epilepsy Diagnosis—0
Decentralized SGD with Over-the-Air Computation—0
Search Space of Adversarial Perturbations against Image Filters—0
Accelerator-aware Neural Network Design using AutoML—0
Metrics and methods for robustness evaluation of neural networks with generative modelsCode0
Joint Device-Edge Inference over Wireless Links with Pruning—0
On the rate of convergence of image classifiers based on convolutional neural networks—0
Anytime Inference with Distilled Hierarchical Neural EnsemblesCode0
A multiple-instance densely-connected ConvNet for aerial scene classificationCode0
Bayesian Neural Networks With Maximum Mean Discrepancy RegularizationCode0
Unsupervised Domain Adaptation for Mammogram Image Classification: A Promising Tool for Model Generalization—0
Iterative Averaging in the Quest for Best Test Error—0
Soft-Root-Sign Activation Function—0
Learning Cross-domain Generalizable Features by Representation Disentanglement—0
Conjugate-gradient-based Adam for stochastic optimization and its application to deep learning—0
Bridging the Gap between Spatial and Spectral Domains: A Survey on Graph Neural Networks—0
Using a thousand optimization tasks to learn hyperparameter search strategies—0
A Free-Energy Principle for Representation Learning—0
ParasNet: Fast Parasites Detection with Neural Networks—0
Relevant-features based Auxiliary Cells for Energy Efficient Detection of Natural Errors—0
Using Wavelets to Analyze Similarities in Image-Classification DatasetsCode0
Video Monitoring Queries—0
Improving STDP-based Visual Feature Learning with Whitening—0
PoET-BiN: Power Efficient Tiny Binary Neurons—0
Communication-Efficient Edge AI: Algorithms and Systems—0
An Optimization and Generalization Analysis for Max-Pooling Networks—0
Exploiting the Full Capacity of Deep Neural Networks while Avoiding Overfitting by Targeted Sparsity Regularization—0
Introducing Fuzzy Layers for Deep Learning—0
Greedy Policy Search: A Simple Baseline for Learnable Test-Time Augmentation—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