Mostafa Diba^*, Hossein Khosravi

Intelligent Automation & Soft Computing, Vol.38, No.3, pp. 315-332, 2023, DOI:10.32604/iasc.2023.046590

Abstract Convolutional neural networks continually evolve to enhance accuracy in addressing various problems, leading to an increase in computational cost and model size. This paper introduces a novel approach for pruning face recognition models based on convolutional neural networks. The proposed method identifies and removes inefficient filters based on the information volume in feature maps. In each layer, some feature maps lack useful information, and there exists a correlation between certain feature maps. Filters associated with these two types of feature maps impose additional computational costs on the model. By eliminating filters related to these categories of feature maps, the reduction… More >

Adnan Nadeem^1,*, Amir Mehmood², Kashif Rizwan³, Muhammad Ashraf⁴, Nauman Qadeer³, Ali Alzahrani¹, Qammer H. Abbasi⁵, Fazal Noor¹, Majed Alhaisoni⁶, Nadeem Mahmood⁷

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6065-6080, 2023, DOI:10.32604/cmc.2023.035012

Abstract This paper presents a large gathering dataset of images extracted from publicly filmed videos by 24 cameras installed on the premises of Masjid Al-Nabvi, Madinah, Saudi Arabia. This dataset consists of raw and processed images reflecting a highly challenging and unconstraint environment. The methodology for building the dataset consists of four core phases; that include acquisition of videos, extraction of frames, localization of face regions, and cropping and resizing of detected face regions. The raw images in the dataset consist of a total of 4613 frames obtained from video sequences. The processed images in the dataset consist of the face… More >

Wenjun Zhang¹, Wenfeng Wang^2,3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.3, pp. 1597-1619, 2023, DOI:10.32604/cmes.2022.020517

Abstract Face recognition has been rapidly developed and widely used. However, there is still considerable uncertainty in the computational intelligence based on human-centric visual understanding. Emerging challenges for face recognition are resulted from information loss. This study aims to tackle these challenges with a broad learning system (BLS). We integrated two models, IR³C with BLS and IR³C with a triplet loss, to control the learning process. In our experiments, we used different strategies to generate more challenging datasets and analyzed the competitiveness, sensitivity, and practicability of the proposed two models. In the model of IR3C with BLS, the recognition rates for… More >

Ratnesh Kumar Shukla^1,*, Arvind Kumar Tiwari²

Computer Systems Science and Engineering, Vol.45, No.1, pp. 293-309, 2023, DOI:10.32604/csse.2023.027986

Abstract Corona virus (COVID-19) is once in a life time calamity that has resulted in thousands of deaths and security concerns. People are using face masks on a regular basis to protect themselves and to help reduce corona virus transmission. During the on-going coronavirus outbreak, one of the major priorities for researchers is to discover effective solution. As important parts of the face are obscured, face identification and verification becomes exceedingly difficult. The suggested method is a transfer learning using MobileNet V2 based technology that uses deep feature such as feature extraction and deep learning model, to identify the problem of… More >

R. Punithavathi^1,*, S. Thenmozhi², R. Jothilakshmi³, V. Ellappan⁴, Islam Md Tahzib Ul⁵

Computer Systems Science and Engineering, Vol.45, No.1, pp. 247-261, 2023, DOI:10.32604/csse.2023.025972

Abstract During Covid pandemic, many individuals are suffering from suicidal ideation in the world. Social distancing and quarantining, affects the patient emotionally. Affective computing is the study of recognizing human feelings and emotions. This technology can be used effectively during pandemic for facial expression recognition which automatically extracts the features from the human face. Monitoring system plays a very important role to detect the patient condition and to recognize the patterns of expression from the safest distance. In this paper, a new method is proposed for emotion recognition and suicide ideation detection in COVID patients. This helps to alert the nurse,… 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 >

Fauzi A. Bala^1,2,*, Osman N. Ucan¹, Oguz Bayat¹

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 2187-2204, 2022, DOI:10.32604/cmc.2022.024205

Abstract Designing an authentication system for securing the power plants are important to allow only specific staffs of the power plant to access the certain blocks so that they can be restricted from using high risk-oriented equipment. This authentication is also vital to prevent any security threats or risks like compromises of business server, release of confidential data etc. Though conventional works attempted to accomplish better authentication, they lacked with respect to accuracy. Hence, the study aims to enhance the recognition rate by introducing a voice recognition system as a personal authentication based on Deep Learning (DL) due to its ability… More >

Anil Kumar Yadav¹, R. K. Pateriya², Nirmal Kumar Gupta³, Punit Gupta^4,*, Dinesh Kumar Saini⁴, Mohammad Alahmadi⁵

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2697-2712, 2022, DOI:10.32604/cmc.2022.023052

Abstract Face recognition systems have enhanced human-computer interactions in the last ten years. However, the literature reveals that current techniques used for identifying or verifying faces are not immune to limitations. Principal Component Analysis-Support Vector Machine (PCA-SVM) and Principal Component Analysis-Artificial Neural Network (PCA-ANN) are among the relatively recent and powerful face analysis techniques. Compared to PCA-ANN, PCA-SVM has demonstrated generalization capabilities in many tasks, including the ability to recognize objects with small or large data samples. Apart from requiring a minimal number of parameters in face detection, PCA-SVM minimizes generalization errors and avoids overfitting problems better than PCA-ANN. PCA-SVM, however,… More >

P. Karuppanan^1,*, K. Dhanalakshmi²

Intelligent Automation & Soft Computing, Vol.33, No.2, pp. 1025-1043, 2022, DOI:10.32604/iasc.2022.023712

Abstract Facial recognition is a trending technology that can identify or verify an individual from a video frame or digital image from any source. A major concern of facial recognition is achieving the accuracy on classification, precision, recall and F1-Score. Traditionally, numerous techniques involved in the working principle of facial recognition, as like Principle Component Analysis (PCA), Linear Discriminant Analysis (LDA), Subspace Decomposition Method, Eigen Feature extraction Method and all are characterized as instable, poor generalization which leads to poor classification. But the simplified method is feature extraction by comparing the particular facial features of the images from the collected dataset… More >

Yudan Zhao^*, Chaoyu Wang

Journal of Information Hiding and Privacy Protection, Vol.3, No.3, pp. 121-130, 2021, DOI:10.32604/jihpp.2021.026380

Abstract Heart rate is an important data reflecting human vital characteristics and an important reference index to describe human physical and mental state. Currently, widely used heart rate measurement devices require direct contact with a person’s skin, which is not suitable for people with burns, delicate skin, newborns and the elderly. Therefore, the research of non-contact heart rate measurement method is of great significance. Based on the basic principle of Photoplethysmography, we use the camera of computer equipment to capture the face image, detect the face region accurately, and detect multiple faces in the image based on multi-target tracking algorithm. Then… More >