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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 5851–5900 of 10420 papers

TitleStatusHype
Learning to Teach—0
Learning to Reweight with Deep Interactions—0
Learning to Teach with Dynamic Loss Functions—0
Group Sparse Coding—0
CowScape: Quantitative reconstruction of the conformational landscape of biological macromolecules from cryo-EM data—0
Group Invariant Deep Representations for Image Instance Retrieval—0
Grouping-By-ID: Guarding Against Adversarial Domain Shifts—0
CovXR: Automated Detection of COVID-19 Pneumonia in Chest X-Rays through Machine Learning—0
Attend Who is Weak: Pruning-assisted Medical Image Localization under Sophisticated and Implicit Imbalances—0
Group Based Deep Shared Feature Learning for Fine-grained Image Classification—0
Learning transformer-based heterogeneously salient graph representation for multimodal remote sensing image classification—0
COVIDLite: A depth-wise separable deep neural network with white balance and CLAHE for detection of COVID-19—0
Maximal function pooling with applications—0
Learning Visual Conditioning Tokens to Correct Domain Shift for Fully Test-time Adaptation—0
Maximal Independent Sets for Pooling in Graph Neural Networks—0
MaxUp: Lightweight Adversarial Training With Data Augmentation Improves Neural Network Training—0
Measuring the Effectiveness of Self-Supervised Learning using Calibrated Learning Curves—0
Learning What Makes a Difference from Counterfactual Examples and Gradient Supervision—0
Continual Learning with Evolving Class Ontologies—0
Learning with convolution and pooling operations in kernel methods—0
MIC: Medical Image Classification Using Chest X-ray (COVID-19 and Pneumonia) Dataset with the Help of CNN and Customized CNN—0
Accelerated PDEs for Construction and Theoretical Analysis of an SGD Extension—0
Attending Category Disentangled Global Context for Image Classification—0
Matching Distributions via Optimal Transport for Semi-Supervised Learning—0
GROOD: Gradient-Aware Out-of-Distribution Detection—0
Learning with Label Noise for Image Retrieval by Selecting Interactions—0
Learning with Limited Samples -- Meta-Learning and Applications to Communication Systems—0
Learning with Neighbor Consistency for Noisy Labels—0
Covid-19: Automatic detection from X-Ray images utilizing Transfer Learning with Convolutional Neural Networks—0
A Hybrid Feature Fusion Deep Learning Framework for Leukemia Cancer Detection in Microscopic Blood Sample Using Gated Recurrent Unit and Uncertainty Quantification—0
How Out-of-Distribution Detection Learning Theory Enhances Transformer: Learnability and Reliability—0
Learning with Recursive Perceptual Representations—0
Coverage Testing of Deep Learning Models using Dataset Characterization—0
Massively Scaling Heteroscedastic Classifiers—0
Matching Feature Sets for Few-Shot Image Classification—0
flexgrid2vec: Learning Efficient Visual Representations Vectors—0
A Hybrid Differential Evolution Approach to Designing Deep Convolutional Neural Networks for Image Classification—0
Learn to Predict Sets Using Feed-Forward Neural Networks—0
DFDL: Discriminative Feature-oriented Dictionary Learning for Histopathological Image Classification—0
Offline Writer Identification Using Convolutional Neural Network Activation Features—0
LeDNet: Localization-enabled Deep Neural Network for Multi-Label Radiography Image Classification—0
Covariance-corrected Whitening Alleviates Network Degeneration on Imbalanced Classification—0
Lensless-camera based machine learning for image classification—0
LeOCLR: Leveraging Original Images for Contrastive Learning of Visual Representations—0
G-RepsNet: A Fast and General Construction of Equivariant Networks for Arbitrary Matrix Groups—0
Coupling Visual Semantics of Artificial Neural Networks and Human Brain Function via Synchronized Activations—0
AED: An black-box NLP classifier model attacker—0
Training Data Subset Search with Ensemble Active Learning—0
Active Transfer Learning with Zero-Shot Priors: Reusing Past Datasets for Future Tasks—0
Greedy Policy Search: A Simple Baseline for Learnable Test-Time Augmentation—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