Eric Yocam¹, Ahmad Alomari², Amjad Gawanmeh^3,*, Wathiq Mansoor³

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3091-3110, 2023, DOI:10.32604/cmc.2023.032826

Abstract A person’s privacy has become a growing concern, given the nature of an expansive reliance on real-time video activities with video capture, stream, and storage. This paper presents an innovative system design based on a privacy-preserving model. The proposed system design is implemented by employing an enhanced capability that overcomes today’s single parameter-based access control protection mechanism for digital privacy preservation. The enhanced capability combines multiple access control parameters: facial expression, resource, environment, location, and time. The proposed system design demonstrated that a person’s facial expressions combined with a set of access control rules can achieve a person’s privacy-preserving preferences.… More >

Valliappan Raman¹, Khaled ELKarazle^2,*, Patrick Then²

Computer Systems Science and Engineering, Vol.44, No.2, pp. 1341-1355, 2023, DOI:10.32604/csse.2023.026674

Abstract Given the current expansion of the computer vision field, several applications that rely on extracting biometric information like facial gender for access control, security or marketing purposes are becoming more common. A typical gender classifier requires many training samples to learn as many distinguishable features as possible. However, collecting facial images from individuals is usually a sensitive task, and it might violate either an individual's privacy or a specific data privacy law. In order to bridge the gap between privacy and the need for many facial images for deep learning training, an artificially generated dataset of facial images is proposed.… More >

R. Haripriya^*, G. Kousalya

Computer Systems Science and Engineering, Vol.43, No.3, pp. 947-965, 2022, DOI:10.32604/csse.2022.024149

Abstract COVID-19 (Coronavirus disease of 2019) is caused by SARS-CoV2 (Severe Acute Respiratory Syndrome Coronavirus 2) and it was first diagnosed in December 2019 in China. As of 25th Aug 2021, there are 165 million confirmed COVID-19 positive cases and 4.4 million deaths globally. As of today, though there are approved COVID-19 vaccine candidates only 4 billion doses have been administered. Until 100% of the population is safe, no one is safe. Even though these vaccines can provide protection against getting seriously ill and dying from the disease, it does not provide 100% protection from getting infected and passing it on… More >

He Gong^1,3,4, Lin Chen¹, Haohong Pan¹, Shijun Li^2,5, Yin Guo¹, Lili Fu¹, Tianli Hu^1,3,4,*, Ye Mu^1,3, Thobela Louis Tyasi⁶

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 6015-6027, 2022, DOI:10.32604/cmc.2022.027160

Abstract The scale of deer breeding has gradually increased in recent years and better information management is necessary, which requires the identification of individual deer. In this paper, a deer face dataset is produced using face images obtained from different angles, and an improved residual neural network (ResNet)-based recognition model is proposed to extract the features of deer faces, which have high similarity. The model is based on ResNet-50, which reduces the depth of the model, and the network depth is only 29 layers; the model connects Squeeze-and-Excitation (SE) modules at each of the four layers where the channel changes to… More >

Valliappan Raman¹, Khaled ELKarazle^2,*, Patrick Then²

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 105-118, 2022, DOI:10.32604/iasc.2022.025608

Abstract Facial age is one of the prominent features needed to make decisions, such as accessing certain areas or resources, targeted advertising, or more straightforward decisions such as addressing one another. In machine learning, facial age estimation is a typical facial analysis subtask in which a model learns the different facial ageing features from several facial images. Despite several studies confirming a relationship between age and gender, very few studies explored the idea of introducing a gender-based system that consists of two separate models, each trained on a specific gender group. This study attempts to bridge this gap by introducing an… More >

Summra Saleem^1,2, M. Usman Ghani Khan^1,2, Tanzila Saba³, Ibrahim Abunadi³, Amjad Rehman^3,*, Saeed Ali Bahaj⁴

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 505-521, 2022, DOI:10.32604/cmc.2022.018871

Abstract Image translation plays a significant role in realistic image synthesis, entertainment tasks such as editing and colorization, and security including personal identification. In Edge GAN, the major contribution is attribute guided vector that enables high visual quality content generation. This research study proposes automatic face image realism from freehand sketches based on Edge GAN. We propose a density variant image synthesis model, allowing the input sketch to encompass face features with minute details. The density level is projected into non-latent space, having a linear controlled function parameter. This assists the user to appropriately devise the variant densities of facial sketches… More >

Kazeem Oyebode¹, Shengzhi Du^2,*, Barend Jacobus van Wyk³

Computer Systems Science and Engineering, Vol.38, No.2, pp. 229-238, 2021, DOI:10.32604/csse.2021.015372

Abstract Context-aware facial recognition regards the recognition of faces in association with their respective environments. This concept is useful for the domestic robot which interacts with humans when performing specific functions in indoor environments. Deep learning models have been relevant in solving facial and place recognition challenges; however, they require the procurement of training images for optimal performance. Pre-trained models have also been offered to reduce training time significantly. Regardless, for classification tasks, custom data must be acquired to ensure that learning models are developed from other pre-trained models. This paper proposes a place recognition model that is inspired by the… More >