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 27012725 of 10420 papers

TitleStatusHype
How to use model architecture and training environment to estimate the energy consumption of DL trainingCode0
Invariant Scattering Transform for Medical Imaging0
Distilling Self-Supervised Vision Transformers for Weakly-Supervised Few-Shot Classification & Segmentation0
Learning Curves for Noisy Heterogeneous Feature-Subsampled Ridge EnsemblesCode0
A Novel Site-Agnostic Multimodal Deep Learning Model to Identify Pro-Eating Disorder Content on Social Media0
Art Authentication with Vision Transformers0
The Role of Subgroup Separability in Group-Fair Medical Image ClassificationCode0
Multi-Similarity Contrastive Learning0
Revisiting Computer-Aided Tuberculosis DiagnosisCode1
Benchmarking Test-Time Adaptation against Distribution Shifts in Image ClassificationCode1
Improving the Efficiency of Human-in-the-Loop Systems: Adding Artificial to Human ExpertsCode0
Distilling Large Vision-Language Model with Out-of-Distribution GeneralizabilityCode1
Multi-Scale U-Shape MLP for Hyperspectral Image Classification0
UX Heuristics and Checklist for Deep Learning powered Mobile Applications with Image Classification0
Rethinking Multiple Instance Learning for Whole Slide Image Classification: A Good Instance Classifier is All You NeedCode1
Multi-Scale Prototypical Transformer for Whole Slide Image Classification0
Make A Long Image Short: Adaptive Token Length for Vision Transformers0
Adversarial Attacks on Image Classification Models: FGSM and Patch Attacks and their Impact0
A ChatGPT Aided Explainable Framework for Zero-Shot Medical Image Diagnosis0
A Neural Collapse Perspective on Feature Evolution in Graph Neural NetworksCode0
Continual Learning in Open-vocabulary Classification with Complementary Memory SystemsCode0
Mitigating Bias: Enhancing Image Classification by Improving Model Explanations0
In-Domain Self-Supervised Learning Improves Remote Sensing Image Scene Classification0
Review helps learn better: Temporal Supervised Knowledge Distillation0
Structured Network Pruning by Measuring Filter-wise Interactions0
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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