SOTAVerified

General Classification

Algorithms trying to solve the general task of classification.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 5301–5350 of 14581 papers

TitleStatusHype
Color Face Recognition using High-Dimension Quaternion-based Adaptive Representation—0
Color Image Classification via Quaternion Principal Component Analysis Network—0
Coloring black boxes: visualization of neural network decisions—0
Coloring the Black Box: Visualizing neural network behavior with a self-introspective model—0
Color Texture Classification Based on Proposed Impulse-Noise Resistant Color Local Binary Patterns and Significant Points Selection Algorithm—0
ColorUNet: A convolutional classification approach to colorization—0
Columbia at SemEval-2019 Task 7: Multi-task Learning for Stance Classification and Rumour Verification—0
ColumbiaNLP at SemEval-2019 Task 8: The Answer is Language Model Fine-tuning—0
Combating Reinforcement Learning's Sisyphean Curse with Intrinsic Fear—0
Combinaison d'information visuelle, conceptuelle, et contextuelle pour la construction automatique de hierarchies semantiques adaptees a l'annotation d'images—0
Combinational neural network using Gabor filters for the classification of handwritten digits—0
Combination of PCA with SMOTE Resampling to Boost the Prediction Rate in Lung Cancer Dataset—0
Combine Convolution with Recurrent Networks for Text Classification—0
Combined Cleaning and Resampling Algorithm for Multi-Class Imbalanced Data with Label Noise—0
Combined convolutional and recurrent neural networks for hierarchical classification of images—0
Combined statistical and model based texture features for improved image classification—0
Combinets: Creativity via Recombination of Neural Networks—0
Combining Anatomical and Functional Networks for Neuropathology Identification: A Case Study on Autism Spectrum Disorder—0
Combining Crowd and Machines for Multi-predicate Item Screening—0
Combining Deep Learning and Linear Processing for Modulation Classification and Symbol Decoding—0
Combining Deep Transfer Learning with Signal-image Encoding for Multi-Modal Mental Wellbeing Classification—0
Combining Deep Universal Features, Semantic Attributes, and Hierarchical Classification for Zero-Shot Learning—0
Combining dependency information and generalization in a pattern-based approach to the classification of lexical-semantic relation instances—0
Combining Different Features of Idiomaticity for the Automatic Classification of Noun+Verb Expressions in Basque—0
Combining Discourse Markers and Cross-lingual Embeddings for Synonym--Antonym Classification—0
Combining Domain-Specific Meta-Learners in the Parameter Space for Cross-Domain Few-Shot Classification—0
Combining Generative and Discriminative Neural Networks for Sleep Stages Classification—0
Combining High-Level Features of Raw Audio Waves and Mel-Spectrograms for Audio Tagging—0
Combining Lightly-Supervised Text Classification Models for Accurate Contextual Advertising—0
Combining Machine Learning and Social Network Analysis to Reveal the Organizational Structures—0
Combining Multiple Algorithms in Classifier Ensembles using Generalized Mixture Functions—0
Combining Multiple Cues for Visual Madlibs Question Answering—0
Combining multiple resolutions into hierarchical representations for kernel-based image classification—0
Combining multiscale features for classification of hyperspectral images: a sequence based kernel approach—0
Combining Noise-to-Image and Image-to-Image GANs: Brain MR Image Augmentation for Tumor Detection—0
Combining One-Class Classifiers via Meta-Learning—0
Combining Real-Valued and Binary Gabor-Radon Features for Classification and Search in Medical Imaging Archives—0
Combining Recurrent and Convolutional Neural Networks for Relation Classification—0
Combining resources for MWE-token classification—0
Combining Scatter Transform and Deep Neural Networks for Multilabel Electrocardiogram Signal Classification—0
Combining Sentinel-1 and Sentinel-2 Time Series via RNN for object-based land cover classification—0
Combining Similarity and Adversarial Learning to Generate Visual Explanation: Application to Medical Image Classification—0
Combining Spiking Neural Network and Artificial Neural Network for Enhanced Image Classification—0
Combining Support Vector Machine and Elephant Herding Optimization for Cardiac Arrhythmias—0
Combining Texture and Shape Cues for Object Recognition With Minimal Supervision—0
Combining Unsupervised Pre-training and Annotator Rationales to Improve Low-shot Text Classification—0
Combining Weakly and Webly Supervised Learning for Classifying Food Images—0
Combining Word-Level and Character-Level Representations for Relation Classification of Informal Text—0
Combining Word Patterns and Discourse Markers for Paradigmatic Relation Classification—0
CommAI: Evaluating the first steps towards a useful general AI—0
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All datasetsXORirisActivityFashion-MNISTISOLETMice ProteinMNISTWine

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