SOTAVerified

General Classification

Algorithms trying to solve the general task of classification.

Papers

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Showing 10001–10025 of 14581 papers

TitleStatusHype
Endowing Robots with Longer-term Autonomy by Recovering from External Disturbances in Manipulation through Grounded Anomaly Classification and Recovery Policies—0
End-to-End Adversarial White Box Attacks on Music Instrument Classification—0
End-to-End Audiovisual Fusion with LSTMs—0
End-to-End Auditory Object Recognition via Inception Nucleus—0
End-to-End Automatic Sleep Stage Classification Using Spectral-Temporal Sleep Features—0
End to End Binarized Neural Networks for Text Classification—0
End-to-End Data Visualization by Metric Learning and Coordinate Transformation—0
End-to-End Deep Diagnosis of X-ray Images—0
End-to-End Diagnosis and Segmentation Learning from Cardiac Magnetic Resonance Imaging—0
End-To-End Dilated Variational Autoencoder with Bottleneck Discriminative Loss for Sound Morphing -- A Preliminary Study—0
End-to-End Discriminative Deep Network for Liver Lesion Classification—0
End-to-End Learning via a Convolutional Neural Network for Cancer Cell Line Classification—0
End-to-End Lip Synchronisation Based on Pattern Classification—0
End-to-End Mandarin Tone Classification with Short Term Context Information—0
1-D Convlutional Neural Networks for the Analysis of Pupil Size Variations in Scotopic Conditions—0
End-to-End Multi-View Lipreading—0
End-to-End Multi-View Networks for Text Classification—0
End-to-End Neural Relation Extraction with Global Optimization—0
End-to-End Non-Autoregressive Neural Machine Translation with Connectionist Temporal Classification—0
End-to-End Parkinson Disease Diagnosis using Brain MR-Images by 3D-CNN—0
End-to-End Radio Fingerprinting with Neural Networks—0
End-to-End Radio Traffic Sequence Recognition with Deep Recurrent Neural Networks—0
End-to-end Relation Extraction using Neural Networks and Markov Logic Networks—0
End-to-End Tracking and Semantic Segmentation Using Recurrent Neural Networks—0
End-to-End Trainable Attentive Decoder for Hierarchical Entity Classification—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
1XBNETAccuracy100—Unverified
2MONT3Accuracy100—Unverified
#ModelMetricClaimedVerifiedStatus
1CAEAccuracy42—Unverified
#ModelMetricClaimedVerifiedStatus
1CAEAccuracy67.7—Unverified
#ModelMetricClaimedVerifiedStatus
1CAEAccuracy68.5—Unverified
#ModelMetricClaimedVerifiedStatus
1CAEAccuracy13.4—Unverified
#ModelMetricClaimedVerifiedStatus
1CAEAccuracy90.6—Unverified
#ModelMetricClaimedVerifiedStatus
1MONT3Accuracy100—Unverified