Abstract: Contrast-enhanced ultrasound (CEUS) image analysis plays a critical role in the detection and characterization of focal liver lesions (FLL) such as hemangioma, hepatocellular carcinoma, and ...

Abstract: This research aims to classify mad recitation in Surah Al-Fatihah using Mel Frequency Cepstral Coefficient (MFCC) feature extraction and Convolutional Neural Network (CNN) algorithm.

Collected Voices of different peoples given to MfCC to extract the features from everyone voices later on RandomForest model is applied to train the model at last PCA ...

Thai speaker identification system using MFCC features with SVM, RF, KNN, GBM classifiers. Trained on podcast audio with 85.12% CV accuracy and Google STT transcription.