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 6001–6050 of 10420 papers

TitleStatusHype
Less or More From Teacher: Exploiting Trilateral Geometry For Knowledge Distillation—0
Locality Guided Neural Networks for Explainable Artificial Intelligence—0
Localization-Aware Active Learning for Object Detection—0
Localized Adversarial Training for Increased Accuracy and Robustness in Image Classification—0
Localizing Interpretable Multi-scale informative Patches Derived from Media Classification Task—0
An Automated CNN Recommendation System for Image Classification Tasks—0
A Dataset for Troll Classification of TamilMemes—0
Lessons learned from the NeurIPS 2021 MetaDL challenge: Backbone fine-tuning without episodic meta-learning dominates for few-shot learning image classification—0
Less is More: Dimension Reduction Finds On-Manifold Adversarial Examples in Hard-Label Attacks—0
Locally Differentially Private Gradient Tracking for Distributed Online Learning over Directed Graphs—0
big.LITTLE Vision Transformer for Efficient Visual Recognition—0
Training Data Subset Search with Ensemble Active Learning—0
Less-forgetful Learning for Domain Expansion in Deep Neural Networks—0
Lesion2Vec: Deep Metric Learning for Few-Shot Multiple Lesions Recognition in Wireless Capsule Endoscopy Video—0
AED: An black-box NLP classifier model attacker—0
LeOCLR: Leveraging Original Images for Contrastive Learning of Visual Representations—0
Lensless-camera based machine learning for image classification—0
LoCa: Logit Calibration for Knowledge Distillation—0
LeDNet: Localization-enabled Deep Neural Network for Multi-Label Radiography Image Classification—0
DFRD: Data-Free Robustness Distillation for Heterogeneous Federated Learning—0
Learn to Predict Sets Using Feed-Forward Neural Networks—0
DFDL: Discriminative Feature-oriented Dictionary Learning for Histopathological Image Classification—0
BigEarthNet-MM: A Large Scale Multi-Modal Multi-Label Benchmark Archive for Remote Sensing Image Classification and Retrieval—0
An Attention Module for Convolutional Neural Networks—0
A Dataset and Benchmarks for Multimedia Social Analysis—0
A Closer Look at Benchmarking Self-Supervised Pre-training with Image Classification—0
2-speed network ensemble for efficient classification of incremental land-use/land-cover satellite image chips—0
Logarithmic Lenses: Exploring Log RGB Data for Image Classification—0
1D-Convolutional Capsule Network for Hyperspectral Image Classification—0
Learn like a Pathologist: Curriculum Learning by Annotator Agreement for Histopathology Image Classification—0
Learning with SASQuaTCh: a Novel Variational Quantum Transformer Architecture with Kernel-Based Self-Attention—0
DFDG: Data-Free Dual-Generator Adversarial Distillation for One-Shot Federated Learning—0
Learning with Recursive Perceptual Representations—0
LoGra-Med: Long Context Multi-Graph Alignment for Medical Vision-Language Model—0
Learning with Noisy Ground Truth: From 2D Classification to 3D Reconstruction—0
DevNet: A Deep Event Network for Multimedia Event Detection and Evidence Recounting—0
Anatomy-specific classification of medical images using deep convolutional nets—0
Learning with Neighbor Consistency for Noisy Labels—0
Learning with Limited Samples -- Meta-Learning and Applications to Communication Systems—0
Learning with Label Noise for Image Retrieval by Selecting Interactions—0
Development of CNN Architectures using Transfer Learning Methods for Medical Image Classification—0
Learning with Inadequate and Incorrect Supervision—0
Learning with Hierarchical Complement Objective—0
Learning with Differentiable Algorithms—0
Development Of A Fire Detection System On Satellite Images—0
Looking Beyond Single Images for Contrastive Semantic Segmentation Learning—0
An Artificial Neural Network for Image Classification Inspired by Aversive Olfactory Learning Circuits in Caenorhabditis Elegans—0
Learning with convolution and pooling operations in kernel methods—0
Continual Learning with Evolving Class Ontologies—0
Developing Convolutional Neural Networks using a Novel Lamarckian Co-Evolutionary Algorithm—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