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 9001–9050 of 10420 papers

TitleStatusHype
DART: Domain-Adversarial Residual-Transfer Networks for Unsupervised Cross-Domain Image Classification—0
Fine-tuning Convolutional Neural Networks for fine art classification—0
Greedy Layerwise Learning Can Scale to ImageNetCode0
Neural Architecture Search Over a Graph Search Space—0
Adversarial Attack and Defense on Graph Data: A SurveyCode0
Attention Branch Network: Learning of Attention Mechanism for Visual ExplanationCode0
Privacy-Preserving Collaborative Deep Learning with Unreliable Participants—0
Guessing Smart: Biased Sampling for Efficient Black-Box Adversarial AttacksCode0
Learning from Web Data: the Benefit of Unsupervised Object Localization—0
DAC: Data-free Automatic Acceleration of Convolutional NetworksCode0
One-Class Feature Learning Using Intra-Class Splitting—0
An Empirical Evaluation of Sketched SVD and its Application to Leverage Score Ordering—0
Toward Multimodal Model-Agnostic Meta-Learning—0
TOP-GAN: Label-Free Cancer Cell Classification Using Deep Learning with a Small Training Set—0
Attending Category Disentangled Global Context for Image Classification—0
The Recognition Of Persian Phonemes Using PPNet—0
Not Using the Car to See the Sidewalk: Quantifying and Controlling the Effects of Context in Classification and Segmentation—0
Pre-Trained Convolutional Neural Network Features for Facial Expression Recognition—0
Efficient Super Resolution Using Binarized Neural Network—0
Flatten-T Swish: a thresholded ReLU-Swish-like activation function for deep learningCode0
Evolutionary Neural Architecture Search for Image Restoration—0
Rethinking Layer-wise Feature Amounts in Convolutional Neural Network ArchitecturesCode0
Generating Hard Examples for Pixel-wise Classification—0
Impact of Data Normalization on Deep Neural Network for Time Series Forecasting—0
Learning to Learn from Noisy Labeled DataCode0
Thwarting Adversarial Examples: An L_0-RobustSparse Fourier Transform—0
ECG Arrhythmia Classification Using Transfer Learning from 2-Dimensional Deep CNN Features—0
A Main/Subsidiary Network Framework for Simplifying Binary Neural Network—0
Reproduction Report on "Learn to Pay Attention"Code0
Layer-Parallel Training of Deep Residual Neural NetworksCode0
Defending Against Universal Perturbations With Shared Adversarial Training—0
Feature Denoising for Improving Adversarial RobustnessCode0
Detecting Adversarial Examples in Convolutional Neural Networks—0
Variational Saccading: Efficient Inference for Large Resolution ImagesCode0
Adversarial Defense of Image Classification Using a Variational Auto-EncoderCode0
Optimizing speed/accuracy trade-off for person re-identification via knowledge distillation—0
Pseudo-Rehearsal: Achieving Deep Reinforcement Learning without Catastrophic ForgettingCode0
Fooling Network Interpretation in Image Classification—0
Teacher-Student Compression with Generative Adversarial NetworksCode0
Blockchain Enabled Trustless API Marketplace—0
Ladder Networks for Semi-Supervised Hyperspectral Image Classification—0
Auto-tuning TensorFlow Threading Model for CPU Backend—0
Energy Efficient Hardware for On-Device CNN Inference via Transfer Learning—0
Prototype-based Neural Network Layers: Incorporating Vector Quantization—0
Parameter Re-Initialization through Cyclical Batch Size Schedules—0
Singing Voice Separation Using a Deep Convolutional Neural Network Trained by Ideal Binary Mask and Cross EntropyCode0
Universal Perturbation Attack Against Image Retrieval—0
Adversarial Domain Randomization—0
Knowledge Distillation with Feature Maps for Image Classification—0
Deep Learning for Classical Japanese LiteratureCode0
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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