A Review of Infant Cry Recognition and Classification based on Computer-Aided Diagnoses
Author:
Affiliation:
1. Tokat Gaziosmanpaşa University,Department of Computer Engineering,Tokat,Turkey,60100
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9799780/9799803/09800038.pdf?arnumber=9800038
Reference117 articles.
1. Automatic Diagnosis of Asphyxia Infant Cry Signals Using Wavelet Based Mel Frequency Cepstrum Features
2. Infant Cry Classification Using Semi-supervised K-Nearest Neighbor Approach
3. Binary Particle Swarm Optimization for selection of features in the recognition of infants cries with asphyxia
4. Infant cry classification to identify asphyxia using time-frequency analysis and radial basis neural networks
5. Pathological infant cry analysis using wavelet packet transform and probabilistic neural network
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1. Infant cry classification using an efficient graph structure and attention-based model;Kuwait Journal of Science;2024-07
2. Comparative Performance Analysis of Metaheuristic Feature Selection Methods for Speech Emotion Recognition;Measurement Science Review;2024-04-01
3. Can You Understand Why I Am Crying? A Decision-making System for Classifying Infants’ Cry Languages Based on DeepSVM Model;ACM Transactions on Asian and Low-Resource Language Information Processing;2024-01-15
4. Infant cry classification by using different deep neural network models and hand-crafted features;Biomedical Signal Processing and Control;2023-05
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