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3D-DCDAE: Unsupervised Music Latent Representations Learning Method Based on a Deep 3D Convolutional Denoising Autoencoder for Music Genre Classification

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-642-21735-7_7openalex-snapshot
Stacked Convolutional Auto-Encoders for Hierarchical Feature Extraction
inferredcites →https://doi.org/10.1007/s10479-005-5724-zopenalex-snapshot
A Tutorial on the Cross-Entropy Method
inferredcites →https://doi.org/10.1016/j.asoc.2016.12.024openalex-snapshot
An evaluation of Convolutional Neural Networks for music classification using spectrograms
inferredcites →https://doi.org/10.1016/j.neucom.2018.02.076openalex-snapshot
Music auto-tagging using deep Recurrent Neural Networks
inferredcites →https://doi.org/10.1016/j.neucom.2019.09.054openalex-snapshot
Deep attention based music genre classification
inferredcites →https://doi.org/10.1109/eait.2018.8470441openalex-snapshot
Music Genre Classification Using Frequency Domain Features
inferredcites →https://doi.org/10.1109/ic3.2018.8530557openalex-snapshot
A Hybrid Model for Music Genre Classification Using LSTM and SVM
inferredcites →https://doi.org/10.1109/icassp.2014.6854950openalex-snapshot
End-to-end learning for music audio
inferredcites →https://doi.org/10.1109/icassp.2017.7952585openalex-snapshot
Convolutional recurrent neural networks for music classification
inferredcites →https://doi.org/10.1109/isemantic50169.2020.9234199openalex-snapshot
Comparison of SVM, KNN, and NB Classifier for Genre Music Classification based on Metadata
inferredcites →https://doi.org/10.1109/mmsp.2016.7813376openalex-snapshot
Robust sound event classification by using denoising autoencoder
inferredcites →https://doi.org/10.1109/msp.2008.930649openalex-snapshot
Mean squared error: Love it or leave it? A new look at Signal Fidelity Measures
inferredcites →https://doi.org/10.1109/msp.2018.2874383openalex-snapshot
Deep Learning for Audio-Based Music Classification and Tagging: Teaching Computers to Distinguish Rock from Bach
inferredcites →https://doi.org/10.1109/taslp.2019.2938863openalex-snapshot
Unsupervised Speech Representation Learning Using WaveNet Autoencoders
inferredcites →https://doi.org/10.1145/2187980.2188222openalex-snapshot
The million song dataset challenge
inferredcites →https://doi.org/10.1145/3273024.3273035openalex-snapshot
On large-scale genre classification in symbolically encoded music by automatic identification of repeating patterns
inferredcites →https://doi.org/10.1186/s13673-020-00252-8openalex-snapshot
Newspaper article-based agent control in smart city simulations
inferredcites →https://doi.org/10.21437/interspeech.2016-1236openalex-snapshot
Improved Music Genre Classification with Convolutional Neural Networks
inferredcites →https://doi.org/10.32470/ccn.2018.1153-0openalex-snapshot
Convolutional Neural Network Achieves Human-level Accuracy in Music Genre Classification
inferredcites →https://doi.org/10.3390/app8010150openalex-snapshot
SampleCNN: End-to-End Deep Convolutional Neural Networks Using Very Small Filters for Music Classification
inferredcites →https://doi.org/10.3390/math8030460openalex-snapshot
FastText-Based Local Feature Visualization Algorithm for Merged Image-Based Malware Classification Framework for Cyber Security and Cyber Defense
inferredcites →https://doi.org/10.3390/math9050530openalex-snapshot
DBTMPE: Deep Bidirectional Transformers-Based Masked Predictive Encoder Approach for Music Genre Classification
inferredcites →https://doi.org/10.3390/s20133741openalex-snapshot
Open Set Audio Classification Using Autoencoders Trained on Few Data
inferredcites →https://doi.org/10.3837/tiis.2018.04.026openalex-snapshot
Korean Traditional Music Genre Classification Using Sample and MIDI Phrases
inferredcites →https://doi.org/10.5281/zenodo.1416287openalex-snapshot
Feature Extraction And Machine Learning On Symbolic Music Using The Music21 Toolkit.
inferredcites →https://doi.org/10.5555/1756006.1953039openalex-snapshot
Stacked Denoising Autoencoders: Learning Useful Representations in a Deep Network with a Local Denoising Criterion

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1007/s00034-024-02696-0openalex-snapshot
Fisher Discriminative Embedding Low-Rank Sparse Representation for Music Genre Classification
inferred← citeshttps://doi.org/10.1007/s00530-021-00886-3openalex-snapshot
Music genre classification based on auditory image, spectral and acoustic features
inferred← citeshttps://doi.org/10.1016/j.eswa.2023.119809openalex-snapshot
CAM-CAN: Class activation map-based categorical adversarial network
inferred← citeshttps://doi.org/10.1109/access.2023.3244620openalex-snapshot
Music Deep Learning: Deep Learning Methods for Music Signal Processing—A Review of the State-of-the-Art
inferred← citeshttps://doi.org/10.1109/access.2023.3318015openalex-snapshot
A Survey of Audio Classification Using Deep Learning
inferred← citeshttps://doi.org/10.1109/access.2025.3620096openalex-snapshot
Non-Contact Hand Tremor Detection Via Water Pouring Sound Recognition
inferred← citeshttps://doi.org/10.1109/iccect60629.2024.10545770openalex-snapshot
A Feature Extraction Intelligent Music Genre Classification Method Based on Deep Learning Technology
inferred← citeshttps://doi.org/10.1109/icrtec56977.2023.10111926openalex-snapshot
A Survey on Music Genre Classification Using Multimodal Information Processing and Retrieval
inferred← citeshttps://doi.org/10.1109/jsen.2025.3635607openalex-snapshot
Listening to Temperature: A Novel Temperature Measurement for Flowing Water Using Audio Recognition Techniques
inferred← citeshttps://doi.org/10.26599/ijcs.2025.9100011openalex-snapshot
Applications of Artificial Intelligence in Music: A Review
inferred← citeshttps://doi.org/10.3390/info14070358openalex-snapshot
Measurement of Music Aesthetics Using Deep Neural Networks and Dissonances
inferred← citeshttps://doi.org/10.3390/math10152747openalex-snapshot
Enhanced Evaluation Method of Musical Instrument Digital Interface Data based on Random Masking and Seq2Seq Model
inferred← citeshttps://doi.org/10.3390/math11041050openalex-snapshot
Hybrid Traffic Accident Classification Models
inferred← citeshttps://doi.org/10.3390/math11071743openalex-snapshot
Traffic Accident Detection Method Using Trajectory Tracking and Influence Maps
inferred← citeshttps://doi.org/10.3390/math11132884openalex-snapshot
Traffic Accident Detection Using Background Subtraction and CNN Encoder–Transformer Decoder in Video Frames
inferred← citeshttps://doi.org/10.3390/math12101549openalex-snapshot
Music Genre Classification Based on VMD-IWOA-XGBOOST
inferred← citeshttps://doi.org/10.5121/csit.2023.130517openalex-snapshot
A Fully Automated Music Equalizer based on Music Genre Detection using Deep Learning and Neural Network
inferred← citeshttps://doi.org/10.52783/jes.2291openalex-snapshot
Breast Cancer Classification Utilizing Deep Learning Techniques on Medical Images: A Comprehensive Review
inferred← citeshttps://doi.org/10.58195/emi.2018.1006openalex-snapshot
Clustering-based Categorization of Music Users through Unsupervised Learning
inferred← citeshttps://doi.org/10.58195/emi.2022.1006openalex-snapshot
Clustering-based Categorization of Music Users through Unsupervised Learning
inferred← citeshttps://doi.org/10.7759/s44389-025-04209-9openalex-snapshot
Artificial Intelligence in Music Genre Classification: A Systematic Review of Techniques, Applications, and Emerging Trends
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