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

Showing 13511375 of 10420 papers

TitleStatusHype
Reliable Deep Learning Plant Leaf Disease Classification Based on Light-Chroma Separated BranchesCode1
Subspace Regularizers for Few-Shot Class Incremental LearningCode1
Well-classified Examples are Underestimated in Classification with Deep Neural NetworksCode1
NAS-Bench-360: Benchmarking Neural Architecture Search on Diverse TasksCode1
Revitalizing CNN Attentions via Transformers in Self-Supervised Visual Representation LearningCode1
Heavy Ball Neural Ordinary Differential EquationsCode1
Class-Balanced Active Learning for Image ClassificationCode1
Automatic Recognition of Abdominal Organs in Ultrasound Images based on Deep Neural Networks and K-Nearest-Neighbor ClassificationCode1
On the Importance of Firth Bias Reduction in Few-Shot ClassificationCode1
Deep Transfer Learning for Land Use and Land Cover Classification: A Comparative StudyCode1
Weak Novel Categories without Tears: A Survey on Weak-Shot LearningCode1
ResNet strikes back: An improved training procedure in timmCode1
Learning Compact Representations of Neural Networks using DiscriminAtive Masking (DAM)Code1
TyXe: Pyro-based Bayesian neural nets for PytorchCode1
Combining Human Predictions with Model Probabilities via Confusion Matrices and CalibrationCode1
NASViT: Neural Architecture Search for Efficient Vision Transformers with Gradient Conflict aware Supernet TrainingCode1
WaveMix: Multi-Resolution Token Mixing for ImagesCode1
Second-Order Neural ODE OptimizerCode1
Evaluation of Deep Neural Network Domain Adaptation Techniques for Image RecognitionCode1
Compressive Visual RepresentationsCode1
Disentangled Feature Representation for Few-shot Image ClassificationCode1
BiTr-Unet: a CNN-Transformer Combined Network for MRI Brain Tumor SegmentationCode1
FedProc: Prototypical Contrastive Federated Learning on Non-IID dataCode1
Balanced-MixUp for Highly Imbalanced Medical Image ClassificationCode1
PP-LCNet: A Lightweight CPU Convolutional Neural NetworkCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CoCa (finetuned)Top 1 Accuracy91Unverified
2Model soups (BASIC-L)Top 1 Accuracy90.98Unverified
3Model soups (ViT-G/14)Top 1 Accuracy90.94Unverified
4DaViT-GTop 1 Accuracy90.4Unverified
5Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2Unverified
6DaViT-HTop 1 Accuracy90.2Unverified
7SwinV2-GTop 1 Accuracy90.17Unverified
8MAWS (ViT-6.5B)Top 1 Accuracy90.1Unverified
9Florence-CoSwin-HTop 1 Accuracy90.05Unverified
10RevCol-HTop 1 Accuracy90Unverified