Enhanced IoT Security: Blockchain, Cryptography, and CNN Integration for Mask Detection
Journal of Electrical and Computer Engineering, Volume 2026, Issue 1, 2026.Security concerns have become paramount, especially with the increasing reliance on facial recognition technology for identity verification. The use of masks, while essential for health protection, poses a significant challenge for these systems, hindering accurate identification.
Imen Hagui +3 more
wiley +1 more source
Faces in places: humans and machines make similar face detection errors.
PLoS ONE, 2011 The human visual system seems to be particularly efficient at detecting faces. This efficiency sometimes comes at the cost of wrongfully seeing faces in arbitrary patterns, including famous examples such as a rock configuration on Mars or a toast's roast
Bernard Marius 't Hart +2 more
doaj +1 more source
Реализация распознавания жестов в реальном времени [PDF]
, 2015 This paper describes a realization of method of Human-Computer interaction based on using video-stream.
Бауэр, А. В.
core
AI‐ and Image‐Based Analysis of Emulsification Processes: Opportunities and Challenges
Chemie Ingenieur Technik, Volume 97, Issue 11-12, Page 1070-1084, November 2025.Smart sensor system and its usage for analysis show great potential for process industry. The development and application of an image‐based sensor using the single‐stage detector YOLO for real‐time analysis of liquid–liquid processes is presented. Opportunities and challenges using real‐time object detection for analysis in laboratory and industrial ...
Inga Burke‐Oeing (née Burke) +3 more
wiley +1 more source
Concurrent Viola Jones classifiers on a portable Beowulf cluster : a thesis presented in partial fulfilment of the requirements for the degree of Master of Engineering in Mechatronics at Massey University [PDF]
, 2008 Real-time Computer Vision is an interesting application for supercomputing, real-time applications (vision processing in particular) employ special purpose hardware such as DSPs to achieve high performance.
Chemudugunta, Ravi Kiran
core
Vision Transformer‐Enhanced Multi‐Descriptor Approach for Robust Age‐Invariant Face Recognition
Applied AI Letters, Volume 6, Issue 3, October 2025.ABSTRACT This study presents a robust age‐invariant face recognition framework, addressing challenges posed by age‐related facial variations. Evaluated on the FGNet and Morph II datasets, the system integrates Viola‐Jones for face detection, SIFT and LBP for feature extraction, and Vision Transformers (ViTs) for global feature representation.
Justice Kwame Appati +3 more
wiley +1 more source
Learning Rate Analysis for Pain Recognition Through Viola-Jones and Deep Learning Methods
Jurnal Nasional Teknik Elektro dan Teknologi InformasiDeep learning is growing and widely used in various fields of life. One of which is the recognition of pain through facial expressions for patients with communication difficulties.
Raihan Islamadina +6 more
doaj +1 more source
Accelerated face detector training using the PSL framework [PDF]
, 2009 We train a face detection system using the PSL framework [1] which combines the AdaBoost learning algorithm and Haar-like features. We demonstrate the ability of this framework to overcome some of the challenges inherent in training classifiers that ...
Barczak, A.L.C. +2 more
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Implementation of the Viola-Jones Algorithm for a Hand Sign Language Translation System
Emitor: Jurnal Teknik ElektroPeople who speech impaired that uses body movements to deliver information. In everyday life, it is not uncommon for people with disabilities to communicate with normal people who do not understand the meaning of what is delivered.
Atik Novianti +2 more
doaj +1 more source
Rejection-Cascade of Gaussians: Real-time adaptive background subtraction framework
, 2019 Background-Foreground classification is a well-studied problem in computer vision. Due to the pixel-wise nature of modeling and processing in the algorithm, it is usually difficult to satisfy real-time constraints. There is a trade-off between the speed (
B Valentine, BR Kiran, J Zuo, T Bouwmans
core +1 more source