Aida Haryati Jamadi¹, Nadlene Razali^1,3,*, Sivakumar Dhar Malingam^1,3, Mastura Mohammad Taha^2,3

Journal of Renewable Materials, Vol.11, No.8, pp. 3261-3276, 2023, DOI:10.32604/jrm.2023.028280

Abstract Natural fibre as a reinforcing agent has been widely used in many industrial applications. Nevertheless, several factors need to be considered, such as the size and weight percentage of the fibre used in binding. Using fused deposition modelling (FDM), this factor was investigated by varying the size of natural fibre as the responding variable with a fixed weight percentage of kenaf fibre. The process of modifying the natural fibre in terms of size might increase the dispersion of kenaf fibre in the polymer matrix and increase the adhesion bonding between the fibre and matrix of composites, subsequently improving the interfacial… More >

Qiuyu Hu¹, Wu Zeng^1,*, Yi Sheng¹, Jian Xu¹, Weihua Ou², Ruochen Tan³

Computer Systems Science and Engineering, Vol.44, No.2, pp. 1397-1408, 2023, DOI:10.32604/csse.2023.027980

Abstract Heart rate is an important vital characteristic which indicates physical and mental health status. Typically heart rate measurement instruments require direct contact with the skin which is time-consuming and costly. Therefore, the study of non-contact heart rate measurement methods is of great importance. Based on the principles of photoelectric volumetric tracing, we use a computer device and camera to capture facial images, accurately detect face regions, and to detect multiple facial images using a multi-target tracking algorithm. Then after the regional segmentation of the facial image, the signal acquisition of the region of interest is further resolved. Finally, frequency detection… More >

Rawan Sulaiman Howyan^1,2,*, Emad Sami Jaha¹

Intelligent Automation & Soft Computing, Vol.31, No.1, pp. 555-580, 2022, DOI:10.32604/iasc.2022.019533

Abstract Human face is one of the most widely used biometrics based on computer-vision to derive various useful information such as gender, ethnicity, age, and even identity. Facial age estimation has received great attention during the last decades because of its influence in many applications, like face recognition and verification, which may be affected by aging changes and signs which appear on human face along with age progression. Thus, it becomes a prominent challenge for many researchers. One of the most influential factors on age estimation is the type of features used in the model training process. Computer-vision is characterized by… More >

Khalil Khan¹, Rehan Ullah Khan², Jehad Ali³, Irfan Uddin⁴, Sahib Khan⁵, Byeong-hee Roh^3,*

CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3483-3498, 2021, DOI:10.32604/cmc.2021.016535

Abstract Race classification is a long-standing challenge in the field of face image analysis. The investigation of salient facial features is an important task to avoid processing all face parts. Face segmentation strongly benefits several face analysis tasks, including ethnicity and race classification. We propose a race-classification algorithm using a prior face segmentation framework. A deep convolutional neural network (DCNN) was used to construct a face segmentation model. For training the DCNN, we label face images according to seven different classes, that is, nose, skin, hair, eyes, brows, back, and mouth. The DCNN model developed in the first phase was used… More >