SOTAVerified

General Classification

Algorithms trying to solve the general task of classification.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 5926–5950 of 14581 papers

TitleStatusHype
An Approach for Process Model Extraction By Multi-Grained Text ClassificationCode0
Fairness in Machine Learning with Tractable Models—0
Joint Learning of Neural Networks via Iterative Reweighted Least SquaresCode0
TRk-CNN: Transferable Ranking-CNN for image classification of glaucoma, glaucoma suspect, and normal eyes—0
Utilizing Deep Learning Towards Multi-modal Bio-sensing and Vision-based Affective Computing—0
Tracing cultural diachronic semantic shifts in Russian using word embeddings: test sets and baselinesCode0
ncRNA Classification with Graph Convolutional NetworksCode0
Semi-supervised learning based on generative adversarial network: a comparison between good GAN and bad GAN approach—0
Multi-task Learning for Chest X-ray Abnormality Classification on Noisy Labels—0
Online Normalization for Training Neural NetworksCode0
ROI Regularization for Semi-supervised and Supervised Learning—0
BiRA-Net: Bilinear Attention Net for Diabetic Retinopathy GradingCode0
Function Space Pooling For Graph Convolutional Networks—0
An Efficient Pre-processing Method to Eliminate Adversarial Effects—0
Addressing the Loss-Metric Mismatch with Adaptive Loss Alignment—0
GMNN: Graph Markov Neural NetworksCode0
A deep-learning-based approach for fast and robust steel surface defects classification—0
Environmental Sound Classification on Microcontrollers using Convolutional Neural NetworksCode0
Vehicle Shape and Color Classification Using Convolutional Neural Network—0
EasiCS: the objective and fine-grained classification method of cervical spondylosis dysfunction—0
Classification via an Embedded Approach—0
An Improved Self-supervised GAN via Adversarial Training—0
From Brain Imaging to Graph Analysis: a study on ADNI's patient cohort—0
PatentBERT: Patent Classification with Fine-Tuning a pre-trained BERT ModelCode0
Assessing the Difficulty of Classifying ConceptNet Relations in a Multi-Label Classification Setting—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