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General Classification

Algorithms trying to solve the general task of classification.

Papers

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Showing 9501–9550 of 14581 papers

TitleStatusHype
Unsupervised Feedforward Feature (UFF) Learning for Point Cloud Classification and Segmentation—0
Unsupervised High-level Feature Learning by Ensemble Projection for Semi-supervised Image Classification and Image Clustering—0
Unsupervised Identification of Translationese—0
Unsupervised Joint Mining of Deep Features and Image Labels for Large-scale Radiology Image Categorization and Scene Recognition—0
Unsupervised Kernel Dimension Reduction—0
Unsupervised Label-aware Event Trigger and Argument Classification—0
Unsupervised Learning in Reservoir Computing for EEG-based Emotion Recognition—0
Unsupervised Learning of Semantic Audio Representations—0
Unsupervised Learning of Spatiotemporally Coherent Metrics—0
Unsupervised learning of the brain connectivity dynamic using residual D-net—0
Unsupervised Learning of the Set of Local Maxima—0
Unsupervised Learning with Self-Organizing Spiking Neural Networks—0
Unsupervised low-rank representations for speech emotion recognition—0
Unsupervisedly Learned Representations: Should the Quest be Over?—0
Unsupervised Meta-Learning For Few-Shot Image Classification—0
Unsupervised Multi-Task Feature Learning on Point Clouds—0
Unsupervised Online Learning With Multiple Postsynaptic Neurons Based on Spike-Timing-Dependent Plasticity Using a TFT-Type NOR Flash Memory Array—0
Unsupervised Paraphasia Classification in Aphasic Speech—0
Unsupervised part learning for visual recognition—0
Unsupervised Part Mining for Fine-grained Image Classification—0
Unsupervised patient representations from clinical notes with interpretable classification decisions—0
Unsupervised Person Re-identification via Multi-label Classification—0
Unsupervised Place Discovery for Visual Place Classification—0
Unsupervised Pre-trained Models from Healthy ADLs Improve Parkinson's Disease Classification of Gait Patterns—0
Unsupervised Regenerative Learning of Hierarchical Features in Spiking Deep Networks for Object Recognition—0
Self-Supervised Learning of Context-Aware Pitch Prosody Representations—0
Unsupervised Representation Learning of DNA Sequences—0
Unsupervised Segmentation Algorithms' Implementation in ITK for Tissue Classification via Human Head MRI Scans—0
Unsupervised Segmentation of Multispectral Images with Cellular Automata—0
Unsupervised seismic facies classification using deep convolutional autoencoder—0
Unsupervised Sequence Classification using Sequential Output Statistics—0
Unsupervised shape and motion analysis of 3822 cardiac 4D MRIs of UK Biobank—0
Unsupervised single-particle deep clustering via statistical manifold learning—0
Unsupervised Star Galaxy Classification with Cascade Variational Auto-Encoder—0
Unsupervised Steganalysis Based on Artificial Training Sets—0
Unsupervised Structure Discovery for Semantic Analysis of Audio—0
Unsupervised Task Design to Meta-Train Medical Image Classifiers—0
Unsupervised vehicle recognition using incremental reseeding of acoustic signatures—0
Unsupervised Visual Feature Learning with Spike-timing-dependent Plasticity: How Far are we from Traditional Feature Learning Approaches?—0
Untangling AdaBoost-based Cost-Sensitive Classification. Part I: Theoretical Perspective—0
Untangling AdaBoost-based Cost-Sensitive Classification. Part II: Empirical Analysis—0
Untangling Local and Global Deformations in Deep Convolutional Networks for Image Classification and Sliding Window Detection—0
UofL at SemEval-2016 Task 4: Multi Domain word2vec for Twitter Sentiment Classification—0
UPV-28-UNITO at SemEval-2019 Task 7: Exploiting Post's Nesting and Syntax Information for Rumor Stance Classification—0
Urban Land Cover Classification with Missing Data Modalities Using Deep Convolutional Neural Networks—0
Usage of multiple RTL features for Earthquake prediction—0
Use Dimensionality Reduction and SVM Methods to Increase the Penetration Rate of Computer Networks—0
Usefulness of interpretability methods to explain deep learning based plant stress phenotyping—0
Use HMM and KNN for classifying corneal data—0
Use of Ensembles of Fourier Spectra in Capturing Recurrent Concepts in Data Streams—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1KNNAccuracy93.1—Unverified
2RFAccuracy92.96—Unverified
3CARTAccuracy92.82—Unverified
4LDAAccuracy77.22—Unverified
#ModelMetricClaimedVerifiedStatus
1MONT3Accuracy100—Unverified
2XBNETAccuracy100—Unverified
#ModelMetricClaimedVerifiedStatus
1CAEAccuracy42—Unverified
#ModelMetricClaimedVerifiedStatus
1CAEAccuracy67.7—Unverified
#ModelMetricClaimedVerifiedStatus
1CAEAccuracy68.5—Unverified
#ModelMetricClaimedVerifiedStatus
1CAEAccuracy13.4—Unverified
#ModelMetricClaimedVerifiedStatus
1CAEAccuracy90.6—Unverified
#ModelMetricClaimedVerifiedStatus
1MONT3Accuracy100—Unverified