Darthy Rabecka V^1,*, Britto Pari J¹, Man-Fai Leung^2,*

CMC-Computers, Materials & Continua, Vol.85, No.1, pp. 827-853, 2025, DOI:10.32604/cmc.2025.064924 - 29 August 2025

Abstract Techniques in deep learning have significantly boosted the accuracy and productivity of computer vision segmentation tasks. This article offers an intriguing architecture for semantic, instance, and panoptic segmentation using EfficientNet-B7 and Bidirectional Feature Pyramid Networks (Bi-FPN). When implemented in place of the EfficientNet-B5 backbone, EfficientNet-B7 strengthens the model’s feature extraction capabilities and is far more appropriate for real-world applications. By ensuring superior multi-scale feature fusion, Bi-FPN integration enhances the segmentation of complex objects across various urban environments. The design suggested is examined on rigorous datasets, encompassing Cityscapes, Common Objects in Context, KITTI Karlsruhe Institute of… More >

Ling Huang^1,2, Hao Zhang^1,2, Jiwei Mo^1,2, Yuehong Liu^1,2, Qiu Lu^1,2,*, Shuiwang Li^1,2,*

Journal of Information Hiding and Privacy Protection, Vol.7, pp. 45-60, 2025, DOI:10.32604/jihpp.2025.066524 - 31 July 2025

Abstract Rapid advances in computer vision have enabled powerful visual perception systems in areas such as surveillance, autonomous driving, healthcare, and augmented reality. However, these systems often raise serious privacy concerns due to their ability to identify and track individuals without consent. This paper explores the emerging field of identity-hiding visual perception, which aims to protect personal identity within visual data through techniques such as anonymization, obfuscation, and privacy-aware modeling. We provide a system-level overview of current technologies, categorize application scenarios, and analyze major challenges—particularly the trade-off between privacy and utility, technical complexity, and ethical risks. More >

Hengfu Yang^1,2,*, Mingfang Jiang^1,2, Zhichen Gao³

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5173-5189, 2023, DOI:10.32604/cmc.2023.034819 - 28 December 2022

Abstract Few previous Reversible Visible Watermarking (RVW) schemes have both good transparency and watermark visibility. An adaptive RVW scheme that integrates Total Variation and visual perception in Block Truncation Coding (BTC) compressed domain, called TVB-RVW is proposed in this paper. A new mean image estimation method for BTC-compressed images is first developed with the help of Total Variation. Then, a visual perception factor computation model is devised by fusing texture and luminance characteristics. An adaptive watermark embedding strategy is used to embed the visible watermark with the effect of the visual perception factor in the BTC More >

Fayadh Alenezi^*

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3425-3443, 2022, DOI:10.32604/cmc.2022.023339 - 07 December 2021

Abstract Image dehazing is still an open research topic that has been undergoing a lot of development, especially with the renewed interest in machine learning-based methods. A major challenge of the existing dehazing methods is the estimation of transmittance, which is the key element of haze-affected imaging models. Conventional methods are based on a set of assumptions that reduce the solution search space. However, the multiplication of these assumptions tends to restrict the solutions to particular cases that cannot account for the reality of the observed image. In this paper we reduce the number of simplified… More >

Debajit Datta¹, Pramod Kumar Maurya¹, Kathiravan Srinivasan², Chuan-Yu Chang^3,*, Rishav Agarwal¹, Ishita Tuteja¹, V. Bhavyashri Vedula¹

CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2545-2561, 2021, DOI:10.32604/cmc.2021.015478 - 13 April 2021

Abstract The pandemic situation in 2020 brought about a ‘digitized new normal’ and created various issues within the current education systems. One of the issues is the monitoring of students during online examination situations. A system to determine the student’s eye gazes during an examination can help to eradicate malpractices. In this work, we track the users’ eye gazes by incorporating twelve facial landmarks around both eyes in conjunction with computer vision and the HAAR classifier. We aim to implement eye gaze detection by considering facial landmarks with two different Convolutional Neural Network (CNN) models, namely More >