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

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Showing 3551–3600 of 10420 papers

TitleStatusHype
Fixing Weight Decay Regularization in Adam—0
Food Image Classification and Segmentation with Attention-based Multiple Instance Learning—0
DFDG: Data-Free Dual-Generator Adversarial Distillation for One-Shot Federated Learning—0
Energy-efficient Amortized Inference with Cascaded Deep Classifiers—0
DevNet: A Deep Event Network for Multimedia Event Detection and Evidence Recounting—0
Energy-Efficient Classification at the Wireless Edge with Reliability Guarantees—0
Energy-Efficient Deployment of Machine Learning Workloads on Neuromorphic Hardware—0
Energy Efficient Hadamard Neural Networks—0
Anatomy-specific classification of medical images using deep convolutional nets—0
Energy-Efficient Model Compression and Splitting for Collaborative Inference Over Time-Varying Channels—0
Energy-entropy competition and the effectiveness of stochastic gradient descent in machine learning—0
Development of CNN Architectures using Transfer Learning Methods for Medical Image Classification—0
An Artificial Neural Network for Image Classification Inspired by Aversive Olfactory Learning Circuits in Caenorhabditis Elegans—0
Classification and Retrieval of Digital Pathology Scans: A New Dataset—0
Enhanced Attacks on Defensively Distilled Deep Neural Networks—0
Enhanced Gradient for Differentiable Architecture Search—0
Development Of A Fire Detection System On Satellite Images—0
Enhanced Image Classification With Data Augmentation Using Position Coordinates—0
Enhanced Infield Agriculture with Interpretable Machine Learning Approaches for Crop Classification—0
Classification Driven Dynamic Image Enhancement—0
Classification-Driven Dynamic Image Enhancement—0
Enhanced Object Detection via Fusion With Prior Beliefs from Image Classification—0
Fine-Grained Recognition as HSnet Search for Informative Image Parts—0
Enhanced Prototypical Part Network (EPPNet) For Explainable Image Classification Via Prototypes—0
Developing Convolutional Neural Networks using a Novel Lamarckian Co-Evolutionary Algorithm—0
Developing a Recommendation Benchmark for MLPerf Training and Inference—0
Enhancing Accuracy and Robustness through Adversarial Training in Class Incremental Continual Learning—0
Anticipating Future Object Compositions without Forgetting—0
Dual-Activated Lightweight Attention ResNet50 for Automatic Histopathology Breast Cancer Image Classification—0
DetNet: Design Backbone for Object Detection—0
Enhancing CNN Classification with Lamarckian Memetic Algorithms and Local Search—0
Enhancing Continuous Domain Adaptation with Multi-Path Transfer Curriculum—0
Bias mitigation techniques in image classification: fair machine learning in human heritage collections—0
A Closed-Form Learned Pooling for Deep Classification Networks—0
Classification of diffraction patterns using a convolutional neural network in single particle imaging experiments performed at X-ray free-electron lasers—0
An approach based on class activation maps for investigating the effects of data augmentation on neural networks for image classification—0
2nd Place Solution for ICCV 2021 VIPriors Image Classification Challenge: An Attract-and-Repulse Learning Approach—0
Enhancing Fine-grained Image Classification through Attentive Batch Training—0
Enhancing Fine-Grained Image Classifications via Cascaded Vision Language Models—0
Classification of Lung Pathologies in Neonates using Dual Tree Complex Wavelet Transform—0
Fine-Grained Image Classification via Combining Vision and Language—0
Enhancing Glass Defect Detection with Diffusion Models: Addressing Imbalanced Datasets in Manufacturing Quality Control—0
Enhancing Image Classification in Small and Unbalanced Datasets through Synthetic Data Augmentation—0
Enhancing Instance-Level Image Classification with Set-Level Labels—0
Enhancing Interpretable Image Classification Through LLM Agents and Conditional Concept Bottleneck Models—0
Enhancing Intrinsic Features for Debiasing via Investigating Class-Discerning Common Attributes in Bias-Contrastive Pair—0
Enhancing JEPAs with Spatial Conditioning: Robust and Efficient Representation Learning—0
Enhancing Layer Attention Efficiency through Pruning Redundant Retrievals—0
Fine-Grained Neural Architecture Search—0
Detection of Plant Leaf Disease Directly in the JPEG Compressed Domain using Transfer Learning Technique—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