Carlos Rojas¹, Cristian Bravo¹, Carlos Enrique Montenegro-Marín¹, Rubén González-Crespo^2,*

CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 5489-5507, 2025, DOI:10.32604/cmc.2025.067394 - 23 October 2025

Abstract The increasing prevalence of violent incidents in public spaces has created an urgent need for intelligent surveillance systems capable of detecting dangerous objects in real time. While traditional video surveillance relies on human monitoring, this approach suffers from limitations such as fatigue and delayed response times. This study addresses these challenges by developing an automated detection system using advanced deep learning techniques to enhance public safety. Our approach leverages state-of-the-art convolutional neural networks (CNNs), specifically You Only Look Once version 4 (YOLOv4) and EfficientDet, for real-time object detection. The system was trained on a comprehensive… More >

Mohammad Tabrez Quasim^*, Khair Ul Nisa

CMC-Computers, Materials & Continua, Vol.83, No.1, pp. 1239-1255, 2025, DOI:10.32604/cmc.2025.061541 - 26 March 2025

Abstract The blockchain-based audiovisual transmission systems were built to create a distributed and flexible smart transport system (STS). This system lets customers, video creators, and service providers directly connect with each other. Blockchain-based STS devices need a lot of computer power to change different video feed quality and forms into different versions and structures that meet the needs of different users. On the other hand, existing blockchains can’t support live streaming because they take too long to process and don’t have enough computer power. Large amounts of video data being sent and analyzed put too much… More >

A. Manju¹, A. Revathi², M. Arivukarasi¹, S. Hariharan³, V. Umarani⁴, Shih-Yu Chen^5,*, Jin Wang⁶

Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 905-920, 2023, DOI:10.32604/iasc.2023.038444 - 29 April 2023

Abstract With the proliferation of the internet, big data continues to grow exponentially, and video has become the largest source. Video big data introduces many technological challenges, including compression, storage, transmission, analysis, and recognition. The increase in the number of multimedia resources has brought an urgent need to develop intelligent methods to organize and process them. The integration between Semantic link Networks and multimedia resources provides a new prospect for organizing them with their semantics. The tags and surrounding texts of multimedia resources are used to measure their semantic association. Two evaluation methods including clustering and… More >

Latifah Almuqren¹, Manar Ahmed Hamza^2,*, Abdullah Mohamed³, Amgad Atta Abdelmageed²

CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 4917-4933, 2023, DOI:10.32604/cmc.2023.037738 - 29 April 2023

Abstract Face recognition technology automatically identifies an individual from image or video sources. The detection process can be done by attaining facial characteristics from the image of a subject face. Recent developments in deep learning (DL) and computer vision (CV) techniques enable the design of automated face recognition and tracking methods. This study presents a novel Harris Hawks Optimization with deep learning-empowered automated face detection and tracking (HHODL-AFDT) method. The proposed HHODL-AFDT model involves a Faster region based convolution neural network (RCNN)-based face detection model and HHO-based hyperparameter optimization process. The presented optimal Faster RCNN model… More >

Wu Song¹, Yayuan Tang^2,3,*, Wenxue Tan¹, Sheng Ren¹

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 509-526, 2023, DOI:10.32604/cmes.2023.026933 - 23 April 2023

Abstract In the environment of smart examination rooms, it is important to quickly and accurately detect abnormal behavior (human standing) for the construction of a smart campus. Based on deep learning, we propose an intelligent standing human detection (ISHD) method based on an improved single shot multibox detector to detect the target of standing human posture in the scene frame of exam room video surveillance at a specific examination stage. ISHD combines the MobileNet network in a single shot multibox detector network, improves the posture feature extractor of a standing person, merges prior knowledge, and introduces More >

Sareer Ul Amin¹, Yongjun Kim², Irfan Sami³, Sangoh Park^1,*, Sanghyun Seo^4,*

Computer Systems Science and Engineering, Vol.46, No.3, pp. 3939-3958, 2023, DOI:10.32604/csse.2023.034805 - 03 April 2023

Abstract In the present technological world, surveillance cameras generate an immense amount of video data from various sources, making its scrutiny tough for computer vision specialists. It is difficult to search for anomalous events manually in these massive video records since they happen infrequently and with a low probability in real-world monitoring systems. Therefore, intelligent surveillance is a requirement of the modern day, as it enables the automatic identification of normal and aberrant behavior using artificial intelligence and computer vision technologies. In this article, we introduce an efficient Attention-based deep-learning approach for anomaly detection in surveillance… More >

MD. Yasar Arafath^1,*, A. Niranjil Kumar²

Computer Systems Science and Engineering, Vol.46, No.2, pp. 2489-2508, 2023, DOI:10.32604/csse.2023.035732 - 09 February 2023

Abstract For intelligent surveillance videos, anomaly detection is extremely important. Deep learning algorithms have been popular for evaluating real-time surveillance recordings, like traffic accidents, and criminal or unlawful incidents such as suicide attempts. Nevertheless, Deep learning methods for classification, like convolutional neural networks, necessitate a lot of computing power. Quantum computing is a branch of technology that solves abnormal and complex problems using quantum mechanics. As a result, the focus of this research is on developing a hybrid quantum computing model which is based on deep learning. This research develops a Quantum Computing-based Convolutional Neural Network… More >

S. Prabu^1,*, J. M. Gnanasekar²

Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 2257-2271, 2023, DOI:10.32604/iasc.2023.029877 - 19 July 2022

Abstract Object detection plays a vital role in the video surveillance systems. To enhance security, surveillance cameras are now installed in public areas such as traffic signals, roadways, retail malls, train stations, and banks. However, monitoring the video continually at a quicker pace is a challenging job. As a consequence, security cameras are useless and need human monitoring. The primary difficulty with video surveillance is identifying abnormalities such as thefts, accidents, crimes, or other unlawful actions. The anomalous action does not occur at a higher rate than usual occurrences. To detect the object in a video,… More >

Erssa Arif^1,*, Syed Khuram Shahzad², Muhammad Waseem Iqbal³, Muhammad Arfan Jaffar⁴, Abdullah S. Alshahrani⁵, Ahmed Alghamdi⁶

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4615-4630, 2022, DOI:10.32604/cmc.2022.027571 - 21 April 2022

Abstract The conventional Close circuit television (CCTV) cameras-based surveillance and control systems require human resource supervision. Almost all the criminal activities take place using weapons mostly a handheld gun, revolver, pistol, swords etc. Therefore, automatic weapons detection is a vital requirement now a day. The current research is concerned about the real-time detection of weapons for the surveillance cameras with an implementation of weapon detection using Efficient–Net. Real time datasets, from local surveillance department's test sessions are used for model training and testing. Datasets consist of local environment images and videos from different type and resolution More >

Esam A. AlQaralleh¹, Fahad Aldhaban², Halah Nasseif², Malek Z. Alksasbeh³, Bassam A. Y. Alqaralleh^2,*

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5593-5605, 2022, DOI:10.32604/cmc.2022.026666 - 21 April 2022

Abstract Real-time video surveillance system is commonly employed to aid security professionals in preventing crimes. The use of deep learning (DL) technologies has transformed real-time video surveillance into smart video surveillance systems that automate human behavior classification. The recognition of events in the surveillance videos is considered a hot research topic in the field of computer science and it is gaining significant attention. Human action recognition (HAR) is treated as a crucial issue in several applications areas and smart video surveillance to improve the security level. The advancements of the DL models help to accomplish improved… More >