Youngeun An, Jimin Lee, EunSang Bak^*, Sungbum Pan^*

CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 1817-1832, 2023, DOI:10.32604/cmc.2023.039460

Abstract Emotion recognition based on facial expressions is one of the most critical elements of human-machine interfaces. Most conventional methods for emotion recognition using facial expressions use the entire facial image to extract features and then recognize specific emotions through a pre-trained model. In contrast, this paper proposes a novel feature vector extraction method using the Euclidean distance between the landmarks changing their positions according to facial expressions, especially around the eyes, eyebrows, nose, and mouth. Then, we apply a new classifier using an ensemble network to increase emotion recognition accuracy. The emotion recognition performance was compared with the conventional algorithms… More >

Noreen Mushtaq¹, Arfat Ahmad Khan², Faizan Ahmed Khan³, Muhammad Junaid Ali⁴, Malik Muhammad Ali Shahid⁵, Chitapong Wechtaisong^2,*, Peerapong Uthansakul²

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5793-5806, 2022, DOI:10.32604/cmc.2022.024316

Abstract Astrocytoma IV or glioblastoma is one of the fatal and dangerous types of brain tumors. Early detection of brain tumor increases the survival rate and helps in reducing the fatality rate. Various imaging modalities have been used for diagnosing by expert radiologists, and Medical Resonance Image (MRI) is considered a better option for detecting brain tumors as MRI is a non-invasive technique and provides better visualization of the brain region. One of the challenging issues is to identify the tumorous region from the MRI scans correctly. Manual segmentation is performed by medical experts, which is a time-consuming task and got… More >