SOTAVerified

General Classification

Algorithms trying to solve the general task of classification.

Papers

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Showing 9401–9425 of 14581 papers

TitleStatusHype
Dendritic Spine Shape Analysis: A Clustering Perspective—0
Denoising Adversarial Autoencoders: Classifying Skin Lesions Using Limited Labelled Training Data—0
Dense Adaptive Cascade Forest: A Self Adaptive Deep Ensemble for Classification Problems—0
Dense Bag-of-Temporal-SIFT-Words for Time Series Classification—0
Dense Classification and Implanting for Few-Shot Learning—0
Dense Fusion Classmate Network for Land Cover Classification—0
Dense Image Representation with Spatial Pyramid VLAD Coding of CNN for Locally Robust Captioning—0
Dense Prediction on Sequences with Time-Dilated Convolutions for Speech Recognition—0
Dense semantic labeling of sub-decimeter resolution images with convolutional neural networks—0
Dense v.s. Sparse: A Comparative Study of Sampling Analysis in Scene Classification of High-Resolution Remote Sensing Imagery—0
Density-Aware Convolutional Networks with Context Encoding for Airborne LiDAR Point Cloud Classification—0
Density-Wise Two Stage Mammogram Classification using Texture Exploiting Descriptors—0
DepecheMood: a Lexicon for Emotion Analysis from Crowd-Annotated News—0
Dependency Based Embeddings for Sentence Classification Tasks—0
Dependency Extraction for Knowledge-based Domain Classification—0
Dependency Graph Enhanced Dual-transformer Structure for Aspect-based Sentiment Classification—0
Dependency Network Syntax: From Dependency Treebanks to a Classification of Chinese Function Words—0
Depth and depth-based classification with R-package ddalpha—0
Enhanced Transfer Learning with ImageNet Trained Classification Layer—0
Derivation of Document Vectors from Adaptation of LSTM Language Model—0
Deriving a Quantitative Relationship Between Resolution and Human Classification Error—0
Deriving de/het gender classification for Dutch nouns for rule-based MT generation tasks—0
Deriving reproducible biomarkers from multi-site resting-state data: An Autism-based example—0
Deriving star cluster parameters with convolutional neural networks. II. Extinction and cluster/background classification—0
Dermatologist Level Dermoscopy Skin Cancer Classification Using Different Deep Learning Convolutional Neural Networks Algorithms—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