Music recommender system via deep learning-Reference-Cited by-同舟云学术

Music recommender system via deep learning

Published:2022-07-04 Issue:5 Volume:43 Page:1081-1088
ISSN:0252-2667
Container-title:Journal of Information and Optimization Sciences
language:en
Short-container-title:Journal of Information and Optimization Sciences

Author:

Poulose Alwin¹,Reddy Chinthala Sreya²,Dash Shatarupa³,Sahu Bharat Jyoti Ranjan³

Affiliation:

1. Center for ICT & Automotive Convergence, Kyungpook National University, Daegu, South Korea

2. School of Computer Science and Engineering, Kyungpook National University, Daegu, South Korea

3. Department of Computer Science and Engineering, Institute of Technical Education and Research (ITER), Siksha ’O’ Anusandhan (Deemed to be University), Bhubaneswar, Odisha, India

Publisher

Taru Publications

Subject

General Earth and Planetary Sciences,General Environmental Science

Link

https://www.tandfonline.com/doi/pdf/10.1080/02522667.2022.2094546

Reference7 articles.

1. N. Pelchat and C. M. Gelowitz, “Neural network music genre classification,” in 2019 IEEE Canadian Conference of Electrical and Computer Engineering (CCECE), 2019, pp. 1-4.

2. Personalized query recommendation system : A genetic algorithm approach

3. A. Poulose and D. S. Han, “Feature-based deep LSTM network for indoor localization using UWB measurements,” in 2021 International Conference on Artificial Intelligence in Information and Communication (ICAIIC), 2021, pp. 298-301.

4. A. Poulose, J. H. Kim, and D. S. Han, “Feature Vector Extraction Technique for Facial Emotion Recognition Using Facial Landmarks,” in 2021 International Conference on Information and Communication Technology Convergence (ICTC), 2021, pp. 1072-1076.

5. A. Poulose, C. S. Reddy, J. H. Kim, and D. S. Han, “Foreground Extraction Based Facial Emotion Recognition Using Deep Learning Xception Model,” in 2021 Twelfth International Conference on Ubiquitous and Future Networks (ICUFN), 2021, pp. 356-360.

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2. Musical instrument classifier for early childhood percussion instruments;PLOS ONE;2024-04-02

3. Beyond the Trends: Evolution and Future Directions in Music Recommender Systems Research;IEEE Access;2024

4. Quantification of golgi dispersal and classification using machine learning models;Micron;2024-01

5. Exploration of Prototype Design for Internet Music Services Based on Data Grid;REV ADHES ADHES;2023