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 4651–4700 of 10420 papers

TitleStatusHype
Cascaded Cross-Attention Networks for Data-Efficient Whole-Slide Image Classification Using Transformers—0
Meta-Learners for Few-Shot Weakly-Supervised Medical Image SegmentationCode0
Medical supervised masked autoencoders: Crafting a better masking strategy and efficient fine-tuning schedule for medical image classificationCode0
Explainable Knowledge Distillation for On-device Chest X-Ray Classification—0
A Multi-modal Approach to Single-modal Visual Place Classification—0
Alternating Gradient Descent and Mixture-of-Experts for Integrated Multimodal Perception—0
Fashion CUT: Unsupervised domain adaptation for visual pattern classification in clothes using synthetic data and pseudo-labels—0
Investigating the Corruption Robustness of Image Classifiers with Random Lp-norm CorruptionsCode0
Architectural Vision for Quantum Computing in the Edge-Cloud ContinuumCode0
Semantic Embedded Deep Neural Network: A Generic Approach to Boost Multi-Label Image Classification Performance—0
Understanding Gaussian Attention Bias of Vision Transformers Using Effective Receptive FieldsCode0
Creative Discovery using QD SearchCode0
LABO: Towards Learning Optimal Label Regularization via Bi-level Optimization—0
Pick your Poison: Undetectability versus Robustness in Data Poisoning Attacks—0
Boldness-Recalibration for Binary Event Predictions—0
Semantic Segmentation using Vision Transformers: A survey—0
Human Attention-Guided Explainable Artificial Intelligence for Computer Vision Models—0
Breast Cancer Diagnosis Using Machine Learning Techniques—0
Image Captioners Sometimes Tell More Than Images They See—0
LatentAugment: Dynamically Optimized Latent Probabilities of Data AugmentationCode0
Forward-Forward Contrastive Learning—0
Unsupervised Mutual Transformer Learning for Multi-Gigapixel Whole Slide Image Classification—0
On the Impact of Data Quality on Image Classification Fairness—0
mAedesID: Android Application for Aedes Mosquito Species Identification using Convolutional Neural Network—0
FCA: Taming Long-tailed Federated Medical Image Classification by Classifier AnchoringCode0
TPMIL: Trainable Prototype Enhanced Multiple Instance Learning for Whole Slide Image ClassificationCode0
Detecting Novelties with Empty Classes—0
Instruction-ViT: Multi-Modal Prompts for Instruction Learning in ViT—0
MMViT: Multiscale Multiview Vision Transformers—0
Advancing Ischemic Stroke Diagnosis: A Novel Two-Stage Approach for Blood Clot Origin Identification—0
PVP: Pre-trained Visual Parameter-Efficient Tuning—0
Tensor Decomposition for Model Reduction in Neural Networks: A Review—0
iMixer: hierarchical Hopfield network implies an invertible, implicit and iterative MLP-MixerCode0
Sample-Specific Debiasing for Better Image-Text Models—0
Now You See Me: Robust approach to Partial Occlusions—0
Evaluating Adversarial Robustness on Document Image Classification—0
Graph Convolutional Networks based on Manifold Learning for Semi-Supervised Image Classification—0
The Case for Hierarchical Deep Learning Inference at the Network Edge—0
Improving Classification Neural Networks by using Absolute activation function (MNIST/LeNET-5 example)Code0
SATIN: A Multi-Task Metadataset for Classifying Satellite Imagery using Vision-Language Models—0
Vision Transformer for Efficient Chest X-ray and Gastrointestinal Image Classification—0
Exploiting Patch Sizes and Resolutions for Multi-Scale Deep Learning in Mammogram Image Classification—0
Picking Up Quantization Steps for Compressed Image ClassificationCode0
DeformableFormer: Classification of Endoscopic Ultrasound Guided Fine Needle Biopsy in Pancreatic Diseases—0
Hyperbolic Geometry in Computer Vision: A Survey—0
WATT-EffNet: A Lightweight and Accurate Model for Classifying Aerial Disaster ImagesCode0
Graph based Label Enhancement for Multi-instance Multi-label learning—0
A baseline on continual learning methods for video action recognition—0
Angle based dynamic learning rate for gradient descentCode0
Multi-domain learning CNN model for microscopy image classification—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