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 7851–7875 of 10420 papers

TitleStatusHype
Q-CapsNets: A Specialized Framework for Quantizing Capsule Networks—0
A Hybrid Method for Training Convolutional Neural Networks—0
Stochastic batch size for adaptive regularization in deep network optimization—0
Detached Error Feedback for Distributed SGD with Random Sparsification—0
Exploring Optimal Deep Learning Models for Image-based Malware Variant Classification—0
ASL Recognition with Metric-Learning based Lightweight Network—0
TensorProjection Layer: A Tensor-Based Dimension Reduction Method in Deep Neural NetworksCode0
Dithered backprop: A sparse and quantized backpropagation algorithm for more efficient deep neural network training—0
Empirical Perspectives on One-Shot Semi-supervised Learning—0
Towards Reusable Network Components by Learning Compatible Representations—0
Radon cumulative distribution transform subspace modeling for image classificationCode0
Teacher-Class Network: A Neural Network Compression MechanismCode0
Inspector Gadget: A Data Programming-based Labeling System for Industrial Images—0
Increasing the Inference and Learning Speed of Tsetlin Machines with Clause Indexing—0
Two-Stage Resampling for Convolutional Neural Network Training in the Imbalanced Colorectal Cancer Image Classification—0
Generative Adversarial Zero-shot Learning via Knowledge Graphs—0
Large-scale spatiotemporal photonic reservoir computer for image classification—0
Attribute Mix: Semantic Data Augmentation for Fine Grained Recognition—0
Comparative Analysis of Multiple Deep CNN Models for Waste Classification—0
Approximate Manifold Defense Against Multiple Adversarial PerturbationsCode0
Group Based Deep Shared Feature Learning for Fine-grained Image Classification—0
Generative Adversarial Networks Based on Collaborative Learning and Attention Mechanism for Hyperspectral Image Classification—0
Predicting the outputs of finite deep neural networks trained with noisy gradients—0
Learning Sparse & Ternary Neural Networks with Entropy-Constrained Trained Ternarization (EC2T)Code0
In Automation We Trust: Investigating the Role of Uncertainty in Active Learning Systems—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
5DaViT-HTop 1 Accuracy90.2—Unverified
6Meta Pseudo Labels (EfficientNet-L2)Top 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