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 6501–6550 of 10420 papers

TitleStatusHype
Motion-Modulated Temporal Fragment Alignment Network for Few-Shot Action Recognition—0
Motorcycle Classification in Urban Scenarios using Convolutional Neural Networks for Feature Extraction—0
Convolutional neural network classification of cancer cytopathology images: taking breast cancer as an example—0
A Domain Decomposition-Based CNN-DNN Architecture for Model Parallel Training Applied to Image Recognition Problems—0
Moving Healthcare AI-Support Systems for Visually Detectable Diseases onto Constrained Devices—0
Active Learning in Video Tracking—0
MoVL:Exploring Fusion Strategies for the Domain-Adaptive Application of Pretrained Models in Medical Imaging Tasks—0
GenMix: Effective Data Augmentation with Generative Diffusion Model Image Editing—0
m-RevNet: Deep Reversible Neural Networks with Momentum—0
MRI-CORE: A Foundation Model for Magnetic Resonance Imaging—0
GenMix: Combining Generative and Mixture Data Augmentation for Medical Image Classification—0
MsaMIL-Net: An End-to-End Multi-Scale Aware Multiple Instance Learning Network for Efficient Whole Slide Image Classification—0
mSAM: Micro-Batch-Averaged Sharpness-Aware Minimization—0
Convolutional Neural Fabrics—0
MSD: Multi-Self-Distillation Learning via Multi-classifiers within Deep Neural Networks—0
MVP: Meta Visual Prompt Tuning for Few-Shot Remote Sensing Image Scene Classification—0
Genetic Programming-Based Evolutionary Deep Learning for Data-Efficient Image Classification—0
MS-GWNN:multi-scale graph wavelet neural network for breast cancer diagnosis—0
MSHCNet: Multi-Stream Hybridized Convolutional Networks with Mixed Statistics in Euclidean/Non-Euclidean Spaces and Its Application to Hyperspectral Image Classification—0
Convolutional Low-Resolution Fine-Grained Classification—0
GeneSys: Enabling Continuous Learning through Neural Network Evolution in Hardware—0
Convolutional Kernel Networks—0
DSAGL: Dual-Stream Attention-Guided Learning for Weakly Supervised Whole Slide Image Classification—0
MS-Twins: Multi-Scale Deep Self-Attention Networks for Medical Image Segmentation—0
Asymmetric Co-Training with Explainable Cell Graph Ensembling for Histopathological Image Classification—0
MTBF-33: A multi-temporal building footprint dataset for 33 counties in the United States (1900-2015)—0
MVQ:Towards Efficient DNN Compression and Acceleration with Masked Vector Quantization—0
Generic Semi-Supervised Adversarial Subject Translation for Sensor-Based Human Activity Recognition—0
Convolutional Clustering for Unsupervised Learning—0
MUFold-SS: Protein Secondary Structure Prediction Using Deep Inception-Inside-Inception Networks—0
Generic Image Classification Approaches Excel on Face Recognition—0
A Survey on Visual Transformer—0
Generative NeuroEvolution for Deep Learning—0
Multi-Agent Mutual Learning at Sentence-Level and Token-Level for Neural Machine Translation—0
Convolutional autoencoder-based multimodal one-class classification—0
An Improved CNN-based Neural Network Model for Fruit Sugar Level Detection—0
Multi-branch CNN and grouping cascade attention for medical image classification—0
Multi-branch fusion network for hyperspectral image classification—0
Generative Negative Text Replay for Continual Vision-Language Pretraining—0
Convolutional Architecture Exploration for Action Recognition and Image Classification—0
Multiclass ASMA vs Targeted PGD Attack in Image Segmentation—0
Multiclass Burn Wound Image Classification Using Deep Convolutional Neural Networks—0
Aggregative Self-Supervised Feature Learning from a Limited Sample—0
ConvNets and ImageNet Beyond Accuracy: Understanding Mistakes and Uncovering Biases—0
Multi-class Generative Adversarial Nets for Semi-supervised Image Classification—0
Dual-branch PolSAR Image Classification Based on GraphMAE and Local Feature Extraction—0
Generative Model for Models: Rapid DNN Customization for Diverse Tasks and Resource Constraints—0
Generatively Augmented Neural Network Watchdog for Image Classification Networks—0
A survey on Semi-, Self- and Unsupervised Learning for Image Classification—0
Generative Data Mining with Longtail-Guided Diffusion—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