Music deep learning: deep learning methods for music signal processing—a review of the state-of-the-art
The discipline of Deep Learning has been recognized for its strong computational tools,
which have been extensively used in data and signal processing, with innumerable …
which have been extensively used in data and signal processing, with innumerable …
Apple varieties and growth prediction with time series classification based on deep learning to impact the harvesting decisions
Apples are among the most popular fruits globally due to their health and nutritional benefits
for humans. Artificial intelligence in agriculture has advanced, but vision, which improves …
for humans. Artificial intelligence in agriculture has advanced, but vision, which improves …
The Challenges of Music Deep Learning for Traditional Music
Numerous applications for music listeners, educators, DJs, and musicians have been
created over the past decade as the field of Music Deep Learning has expanded. Evidently …
created over the past decade as the field of Music Deep Learning has expanded. Evidently …
Feature comparison for classification of Kaustinen fiddle playing style from archived recordings using deep learning
H Tahvanainen, T Ylönen, O Valo - 2024 32nd European …, 2024 - ieeexplore.ieee.org
The largest collection of the Finnish Folk Music Institute contains the recordings of Kaustinen
Folk Music festival since 1968. The recordings have been labelled by hand, and oftentimes …
Folk Music festival since 1968. The recordings have been labelled by hand, and oftentimes …
Recognition of Greek Orthodox Hymns Using Audio Fingerprint Techniques
K Karasavvidis, D Kampelopoulos… - 2023 8th South-East …, 2023 - ieeexplore.ieee.org
Audio fingerprinting was originally developed for music song identification, and over the
years has been used for many more cases. With fingerprinting, an equivalent signature of …
years has been used for many more cases. With fingerprinting, an equivalent signature of …
Music Genre Classification Using Long Short-Term Memory (LSTM) Networks: Analyzing Audio Spectrograms for Enhanced Multimedia Understanding
SK Swarnkar, YK Rathore - Machine Learning in Multimedia, 2025 - taylorfrancis.com
This examination explores music-type characterization utilizing long short-term memory
(LSTM) networks applied to sound spectrograms, intending to upgrade interactive media …
(LSTM) networks applied to sound spectrograms, intending to upgrade interactive media …
Genre Classification in Music using Convolutional Neural Networks
A Bawitlung, SK Dash - International Visual Informatics Conference, 2023 - Springer
With the advancement of technology and computational power, crafting a chart-topping song
has become more effortless than before, achievable from the convenience of our residences …
has become more effortless than before, achievable from the convenience of our residences …
Integrating Music Genre Classification for Precision in Constructing an Automatic Music Transcription Model for Ethiopian Begena
G Bisrat - 2023 - ir.bdu.edu.et
This thesis delves into the intricate realm of Automatic Music Transcription (AMT), with a
specific focus on the Begena, a ten-stringed Ethiopian musical instrument. The primary aim …
specific focus on the Begena, a ten-stringed Ethiopian musical instrument. The primary aim …
Nurul Farhanaa Zulkefli¹, Norizan Mat Diah1 (), Azlan Ismail¹
HFM Hanum¹, Z Ibrahim¹, YM Arif… - Advances in Visual …, 2023 - books.google.com
Problems with mental health are common presently and have been a worry for a long time.
Mental health problems, like anxiety, depression, and panic attacks, can be caused by …
Mental health problems, like anxiety, depression, and panic attacks, can be caused by …