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 5901–5950 of 10420 papers

TitleStatusHype
How Out-of-Distribution Detection Learning Theory Enhances Transformer: Learnability and Reliability—0
Coverage Testing of Deep Learning Models using Dataset Characterization—0
Measuring Unintended Memorisation of Unique Private Features in Neural Networks—0
flexgrid2vec: Learning Efficient Visual Representations Vectors—0
A Hybrid Differential Evolution Approach to Designing Deep Convolutional Neural Networks for Image Classification—0
Let's Go Shopping (LGS) -- Web-Scale Image-Text Dataset for Visual Concept Understanding—0
Diabetic retinopathy image classification method based on GreenBen data augmentation—0
Covariance-corrected Whitening Alleviates Network Degeneration on Imbalanced Classification—0
G-RepsNet: A Fast and General Construction of Equivariant Networks for Arbitrary Matrix Groups—0
Leveraging Chat-Based Large Vision Language Models for Multimodal Out-Of-Context Detection—0
Measuring the Effect of Causal Disentanglement on the Adversarial Robustness of Neural Network Models—0
Measuring the Interpretability of Unsupervised Representations via Quantized Reversed Probing—0
Coupling Visual Semantics of Artificial Neural Networks and Human Brain Function via Synchronized Activations—0
Leveraging Conditional Mutual Information to Improve Large Language Model Fine-Tuning For Classification—0
Leveraging counterfactual concepts for debugging and improving CNN model performance—0
Active Transfer Learning with Zero-Shot Priors: Reusing Past Datasets for Future Tasks—0
Leveraging Deep Learning and Xception Architecture for High-Accuracy MRI Classification in Alzheimer Diagnosis—0
Leveraging Diffusion Models for Synthetic Data Augmentation in Protein Subcellular Localization Classification—0
Greedy Policy Search: A Simple Baseline for Learnable Test-Time Augmentation—0
GreedyNAS: Towards Fast One-Shot NAS with Greedy Supernet—0
Diagnosis of Alzheimer's Disease via Multi-modality 3D Convolutional Neural Network—0
Leveraging Internal Representations of Model for Magnetic Image Classification—0
Measuring the Effectiveness of Self-Supervised Learning using Calibrated Learning Curves—0
Measuring the Success of Diffusion Models at Imitating Human Artists—0
Leveraging Mid-Level Deep Representations For Predicting Face Attributes in the Wild—0
Diagnosis of Skin Cancer Using VGG16 and VGG19 Based Transfer Learning Models—0
Text Descriptions are Compressive and Invariant Representations for Visual Learning—0
Leveraging Perceptual Scores for Dataset Pruning in Computer Vision Tasks—0
Leveraging Semi-Supervised Learning to Enhance Data Mining for Image Classification under Limited Labeled Data—0
Leveraging Spatial and Semantic Feature Extraction for Skin Cancer Diagnosis with Capsule Networks and Graph Neural Networks—0
Leveraging Superfluous Information in Contrastive Representation Learning—0
Leveraging Systematic Knowledge of 2D Transformations—0
MedFocusCLIP : Improving few shot classification in medical datasets using pixel wise attention—0
Break a Lag: Triple Exponential Moving Average for Enhanced Optimization—0
MDL-NAS: A Joint Multi-Domain Learning Framework for Vision Transformer—0
Attack Agnostic Statistical Method for Adversarial Detection—0
Grassmann Pooling as Compact Homogeneous Bilinear Pooling for Fine-Grained Visual Classification—0
LEVIS: Large Exact Verifiable Input Spaces for Neural Networks—0
GRASP: A Rehearsal Policy for Efficient Online Continual Learning—0
Coupled End-to-End Transfer Learning With Generalized Fisher Information—0
Measuring directional bias amplification in image captions using predictability—0
AT-SNN: Adaptive Tokens for Vision Transformer on Spiking Neural Network—0
GraphViz2Vec: A Structure-aware Feature Generation Model to Improve Classification in GNNs—0
DIET-SNN: Direct Input Encoding With Leakage and Threshold Optimization in Deep Spiking Neural Networks—0
Diff3Dformer: Leveraging Slice Sequence Diffusion for Enhanced 3D CT Classification with Transformer Networks—0
Lie Algebra Canonicalization: Equivariant Neural Operators under arbitrary Lie Groups—0
A Hybrid Architecture for On-Device Compressive Machine Learning—0
DiffCLIP: Leveraging Stable Diffusion for Language Grounded 3D Classification—0
Graph Structural Aggregation for Explainable Learning—0
Graphs for deep learning representations—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