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 9351–9400 of 10420 papers

TitleStatusHype
DetNet: A Backbone network for Object DetectionCode0
Rafiki: Machine Learning as an Analytics Service SystemCode0
ShapeShifter: Robust Physical Adversarial Attack on Faster R-CNN Object DetectorCode0
SparseNet: A Sparse DenseNet for Image Classification—0
Deep Neural Networks Motivated by Partial Differential EquationsCode0
Adversarial Alignment of Class Prediction Uncertainties for Domain Adaptation—0
Pooling is neither necessary nor sufficient for appropriate deformation stability in CNNs—0
Deep Learning For Computer Vision Tasks: A review—0
Unsupervised and semi-supervised learning with Categorical Generative Adversarial Networks assisted by Wasserstein distance for dermoscopy image Classification—0
A Systematic DNN Weight Pruning Framework using Alternating Direction Method of MultipliersCode0
Assessment of Breast Cancer Histology using Densely Connected Convolutional Networks—0
HyperDense-Net: A hyper-densely connected CNN for multi-modal image segmentationCode1
NetAdapt: Platform-Aware Neural Network Adaptation for Mobile ApplicationsCode0
AMNet: Memorability Estimation with AttentionCode0
Ordinal Pooling Networks: For Preserving Information over Shrinking Feature MapsCode0
Learn To Pay AttentionCode0
Self-supervised Learning of Geometrically Stable Features Through Probabilistic Introspection—0
The Tsetlin Machine - A Game Theoretic Bandit Driven Approach to Optimal Pattern Recognition with Propositional LogicCode0
Multi-Scale Spatially-Asymmetric Recalibration for Image Classification—0
The Structure Transfer Machine Theory and ApplicationsCode0
In-depth Question classification using Convolutional Neural Networks—0
Compare and Contrast: Learning Prominent Visual Differences—0
Class Subset Selection for Transfer Learning using Submodularity—0
Joint Optimization Framework for Learning with Noisy LabelsCode0
Parallel Grid Pooling for Data AugmentationCode0
Hierarchical Transfer Convolutional Neural Networks for Image Classification—0
ClickBAIT-v2: Training an Object Detector in Real-Time—0
Fast Parametric Learning with Activation Memorization—0
Recent Developments from Attribute Profiles for Remote Sensing Image Classification—0
Canonical Correlation Analysis of Datasets with a Common Source Graph—0
Efficient Image Dataset Classification Difficulty Estimation for Predicting Deep-Learning AccuracyCode0
Multi-scale Processing of Noisy Images using Edge Preservation LossesCode0
Quantum Entanglement in Deep Learning Architectures—0
BAGAN: Data Augmentation with Balancing GANCode1
Lifting Layers: Analysis and ApplicationsCode0
Detecting Adversarial Perturbations with Saliency—0
Learning Deep Context-Network Architectures for Image Annotation—0
Context Encoding for Semantic SegmentationCode2
Entrenamiento de una red neuronal para el reconocimiento de imagenes de lengua de senas capturadas con sensores de profundidad—0
A Quantization-Friendly Separable Convolution for MobileNetsCode0
What do Deep Networks Like to See?Code0
MLtuner: System Support for Automatic Machine Learning TuningCode0
A Neural Markovian Multiresolution Image Labeling Algorithm—0
Weakly Supervised Object Localization on grocery shelves using simple FCN and Synthetic Dataset—0
D^2: Decentralized Training over Decentralized Data—0
Improving Transferability of Adversarial Examples with Input DiversityCode0
Fast Neural Architecture Construction using EnvelopeNets—0
Evolving Deep Convolutional Neural Networks by Variable-length Particle Swarm Optimization for Image Classification—0
TBD: Benchmarking and Analyzing Deep Neural Network Training—0
Studying Invariances of Trained Convolutional Neural Networks—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