Mel frequency cepstral coefficient and its applications: A review
ZK Abdul, AK Al-Talabani - IEEE Access, 2022 - ieeexplore.ieee.org
Feature extraction and representation has significant impact on the performance of any
machine learning method. Mel Frequency Cepstrum Coefficient (MFCC) is designed to …
machine learning method. Mel Frequency Cepstrum Coefficient (MFCC) is designed to …
Comprehensive review of retinal blood vessel segmentation and classification techniques: intelligent solutions for green computing in medical images, current …
AA Abdulsahib, MA Mahmoud, MA Mohammed… - … Modeling Analysis in …, 2021 - Springer
Recently, there has been an advancement in the development of innovative computer-aided
techniques for the segmentation and classification of retinal vessels, the application of which …
techniques for the segmentation and classification of retinal vessels, the application of which …
A novel hybrid model integrating MFCC and acoustic parameters for voice disorder detection
Voice is an essential component of human communication, serving as a fundamental
medium for expressing thoughts, emotions, and ideas. Disruptions in vocal fold vibratory …
medium for expressing thoughts, emotions, and ideas. Disruptions in vocal fold vibratory …
Breast cancer diagnosis using the fast learning network algorithm
The use of machine learning (ML) and data mining algorithms in the diagnosis of breast
cancer (BC) has recently received a lot of attention. The majority of these efforts, however …
cancer (BC) has recently received a lot of attention. The majority of these efforts, however …
[PDF][PDF] Convolutional neural network for the detection of coronavirus based on X-ray images
EH Ahmed, MRM Alsemawi, MH Mutar… - Indonesian Journal of …, 2022 - researchgate.net
Nowadays, the coronavirus disease (COVID-19) is considered an ongoing pandemic that
spread quickly in most countries around the world. The COVID-19 causes severe acute …
spread quickly in most countries around the world. The COVID-19 causes severe acute …
Speech emotion recognition using optimized genetic algorithm-extreme learning machine
Abstract Automatic Emotion Speech Recognition (ESR) is considered as an active research
field in the Human-Computer Interface (HCI). Typically, the ESR system is consisting of two …
field in the Human-Computer Interface (HCI). Typically, the ESR system is consisting of two …
Detection and classification of conflict flows in SDN using machine learning algorithms
Software-Defined Networking (SDN) is a new type of technology that embraces high
flexibility and adaptability. The applications in SDN have the ability to manage and control …
flexibility and adaptability. The applications in SDN have the ability to manage and control …
Grey wolf optimization-extreme learning machine for automatic spoken language identification
Natural language classification and determination based on a particular content and dataset
is carried out using Spoken Language Identification (LID) which typically involves the …
is carried out using Spoken Language Identification (LID) which typically involves the …
Fast learning network algorithm for voice pathology detection and classification
The utilisation of ML (Machine Learning) techniques in the detection of the VP (Voice
Pathology) has recently gained a lot of consideration. However, these efforts still have …
Pathology) has recently gained a lot of consideration. However, these efforts still have …
A novel pathological voice identification technique through simulated cochlear implant processing systems
This paper presents a pathological voice identification system employing signal processing
techniques through cochlear implant models. The fundamentals of the biological process for …
techniques through cochlear implant models. The fundamentals of the biological process for …