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 5476–5500 of 10420 papers

TitleStatusHype
A Comparison of Deep Saliency Map Generators on Multispectral Data in Object Detection—0
Effective and Robust Detection of Adversarial Examples via Benford-Fourier Coefficients—0
EffCNet: An Efficient CondenseNet for Image Classification on NXP BlueBox—0
EEG-NeXt: A Modernized ConvNet for The Classification of Cognitive Activity from EEG—0
Causal Analysis for Robust Interpretability of Neural Networks—0
EEG-based Image Feature Extraction for Visual Classification using Deep Learning—0
CA-UDA: Class-Aware Unsupervised Domain Adaptation with Optimal Assignment and Pseudo-Label Refinement—0
Cauchy activation function and XNet—0
Annotation-Free Group Robustness via Loss-Based Resampling—0
Advancing Security in AI Systems: A Novel Approach to Detecting Backdoors in Deep Neural Networks—0
Edge Detection and Deep Learning Based SETI Signal Classification Method—0
CAT: Learning to Collaborate Channel and Spatial Attention from Multi-Information Fusion—0
Edge-Cloud Cooperation for DNN Inference via Reinforcement Learning and Supervised Learning—0
Edge AI without Compromise: Efficient, Versatile and Accurate Neurocomputing in Resistive Random-Access Memory—0
Edge AI: Evaluation of Model Compression Techniques for Convolutional Neural Networks—0
EDDA: Explanation-driven Data Augmentation to Improve Explanation Faithfulness—0
Annotation Efficiency: Identifying Hard Samples via Blocked Sparse Linear Bandits—0
Advancing Multimodal Medical Capabilities of Gemini—0
A Comparative Study of Deep Learning Classification Methods on a Small Environmental Microorganism Image Dataset (EMDS-6): from Convolutional Neural Networks to Visual Transformers—0
ECO: Ensembling Context Optimization for Vision-Language Models—0
Category Disentangled Context: Turning Category-irrelevant Features Into Treasures—0
ECG Arrhythmia Classification Using Transfer Learning from 2-Dimensional Deep CNN Features—0
SCALES: Boost Binary Neural Network for Image Super-Resolution with Efficient Scalings—0
Catch-Up Mix: Catch-Up Class for Struggling Filters in CNN—0
An MRP Formulation for Supervised Learning: Generalized Temporal Difference Learning Models—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