Optimizing Disease Prediction with Artificial Intelligence Driven Feature Selection and Attention Networks
D Dhinakaran, SE Raja, M Thiyagarajan… - arXiv preprint arXiv …, 2024 - arxiv.org
The rapid integration of machine learning methodologies in healthcare has ignited
innovative strategies for disease prediction, particularly with the vast repositories of …
innovative strategies for disease prediction, particularly with the vast repositories of …
SSTE: Syllable-Specific Temporal Encoding to FORCE-learn audio sequences with an associative memory approach
The circuitry and pathways in the brains of humans and other species have long inspired
researchers and system designers to develop accurate and efficient systems capable of …
researchers and system designers to develop accurate and efficient systems capable of …
[PDF][PDF] 基于改进ECAPA-TDNN 的法庭自动说话人识别
万玫汐， 王华朋， 闫道申， 刘鹏展， 许铭洋 - 科学技术与工程, 2024 - stae.com.cn
基于改进ECAPA-TDNN 的法庭自动说话人识别 Page 1 投稿网址:www. stae. com. cn 2024 年
第24 卷第27 期 2024, 24(27):11763 -11 科学技术与工程 Science Technology and …
第24 卷第27 期 2024, 24(27):11763 -11 科学技术与工程 Science Technology and …
Anomalous Machine Sound Detection Based on Time Domain Gammatone Spectrogram Feature and IDNN Model
PA Hafiz, CO Mawalim, DP Lestari… - 2024 Asia Pacific …, 2024 - ieeexplore.ieee.org
Anomalous sound detection (ASD) systems distinguish normal and abnormal machinery
conditions on the basis of sound. While most ASD systems rely on the log Mel spectrogram …
conditions on the basis of sound. While most ASD systems rely on the log Mel spectrogram …
AI-Based Percussive Acoustic Signal Classification for Fastener Strength Inspection of Stator Wedge
HM Park, D Shon, TH Yoon, WS Jung… - … on Information and …, 2024 - ieeexplore.ieee.org
This paper proposes a two-stage AI-based method for automatically inspecting the fastener
strength of generator stator wedges. This approach includes a 'Noise removal …
strength of generator stator wedges. This approach includes a 'Noise removal …
Speaker Identification Under Noisy Conditions Using Hybrid Deep Learning Model
Speaker identification is a biometric mechanism that determines a person who is speaking
from a set of known speakers. It has vital applications in areas like security, surveillance …
from a set of known speakers. It has vital applications in areas like security, surveillance …
[PDF][PDF] Advanced Noise Filtering Techniques with Horizontal Visibility Graphs and LogNNet: A Study on White Noise Suppression
A Velichko, JA Conejero, Y Izotov, VT Pham - 2025 - preprints.org
In modern audio processing systems like speech recognition, medical devices, and IoT
sensors, effective noise filtering is crucial. High noise levels degrade signal quality and …
sensors, effective noise filtering is crucial. High noise levels degrade signal quality and …
Mechanical Fault Diagnosis Using Audio Signal Feature Fusion and Fuzzy Inference
L Tang, H Tian, H Huang, J Xie - 2023 China Automation …, 2023 - ieeexplore.ieee.org
Fault diagnosis is one of the key technologies for achieving intelligent manufacturing.
However, implementing fault diagnosis in special environments, such as high-pressure, high …
However, implementing fault diagnosis in special environments, such as high-pressure, high …
[PDF][PDF] Speaker identification under noisy conditions using hybrid convolutional neural network and gated recurrent unit
Speaker identification is biometrics that classifies or identifies a person from other speakers
based on speech characteristics. Recently, deep learning models outperformed …
based on speech characteristics. Recently, deep learning models outperformed …
[引用][C] The Bi-Directional Hybrid Deep Learning model for Speaker Iden-tification
R Srinivasagan, A Alzahrani - International Journal of Advanced Science and …, 2024