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 92019225 of 10420 papers

TitleStatusHype
Reversed Active Learning based Atrous DenseNet for Pathological Image Classification0
YouTube for Patient Education: A Deep Learning Approach for Understanding Medical Knowledge from User-Generated Videos0
TextTopicNet - Self-Supervised Learning of Visual Features Through Embedding Images on Semantic Text SpacesCode0
Uncorrelated Feature Encoding for Faster Image Style Transfer0
Selective Deep Convolutional Neural Network for Low Cost Distorted Image Classification0
Neonatal Pain Expression Recognition Using Transfer Learning0
Building Damage Annotation on Post-Hurricane Satellite Imagery Based on Convolutional Neural NetworksCode0
Iterative Attention Mining for Weakly Supervised Thoracic Disease Pattern Localization in Chest X-Rays0
Elastic Neural Networks: A Scalable Framework for Embedded Computer Vision0
Classifying neuromorphic data using a deep learning framework for image classification0
Knowledge-Embedded Representation Learning for Fine-Grained Image Recognition0
Deep Residual Network based Automatic Image Grading for Diabetic Macular EdemaCode0
D^2: Decentralized Training over Decentralized Data0
Learning Longer-term Dependencies in RNNs with Auxiliary Losses0
Pushing the Limits of Radiology with Joint Modeling of Visual and Textual Information0
Two Methods for Domain Adaptation of Bilingual Tasks: Delightfully Simple and Broadly ApplicableCode0
Autonomous Deep Learning: A Genetic DCNN Designer for Image Classification0
Fractional Wavelet Scattering Network and Applications0
A Benchmark for Interpretability Methods in Deep Neural NetworksCode0
This Looks Like That: Deep Learning for Interpretable Image RecognitionCode1
Understanding Dropout as an Optimization Trick0
Generating Counterfactual Explanations with Natural Language0
Constructing Deep Neural Networks by Bayesian Network Structure Learning0
DARTS: Differentiable Architecture SearchCode1
Defending Malware Classification Networks Against Adversarial Perturbations with Non-Negative Weight Restrictions0
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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