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  • Open Access

    ARTICLE

    Human Pose Estimation and Object Interaction for Sports Behaviour

    Ayesha Arif1, Yazeed Yasin Ghadi2, Mohammed Alarfaj3, Ahmad Jalal1, Shaharyar Kamal1, Dong-Seong Kim4,*

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1-18, 2022, DOI:10.32604/cmc.2022.023553

    Abstract In the new era of technology, daily human activities are becoming more challenging in terms of monitoring complex scenes and backgrounds. To understand the scenes and activities from human life logs, human-object interaction (HOI) is important in terms of visual relationship detection and human pose estimation. Activities understanding and interaction recognition between human and object along with the pose estimation and interaction modeling have been explained. Some existing algorithms and feature extraction procedures are complicated including accurate detection of rare human postures, occluded regions, and unsatisfactory detection of objects, especially small-sized objects. The existing HOI… More >

  • Open Access

    ARTICLE

    Computer-Vision Based Object Detection and Recognition for Service Robot in Indoor Environment

    Kiran Jot Singh1, Divneet Singh Kapoor1,*, Khushal Thakur1, Anshul Sharma1, Xiao-Zhi Gao2

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 197-213, 2022, DOI:10.32604/cmc.2022.022989

    Abstract The near future has been envisioned as a collaboration of humans with mobile robots to help in the day-to-day tasks. In this paper, we present a viable approach for a real-time computer vision based object detection and recognition for efficient indoor navigation of a mobile robot. The mobile robotic systems are utilized mainly for home assistance, emergency services and surveillance, in which critical action needs to be taken within a fraction of second or real-time. The object detection and recognition is enhanced with utilization of the proposed algorithm based on the modification of You Look… More >

  • Open Access

    ARTICLE

    Deep Reinforcement Learning Enabled Smart City Recycling Waste Object Classification

    Mesfer Al Duhayyim1, Taiseer Abdalla Elfadil Eisa2, Fahd N. Al-Wesabi3,4, Abdelzahir Abdelmaboud5, Manar Ahmed Hamza6,*, Abu Sarwar Zamani6, Mohammed Rizwanullah6, Radwa Marzouk7,8

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5699-5715, 2022, DOI:10.32604/cmc.2022.024431

    Abstract The Smart City concept revolves around gathering real time data from citizen, personal vehicle, public transports, building, and other urban infrastructures like power grid and waste disposal system. The understandings obtained from the data can assist municipal authorities handle assets and services effectually. At the same time, the massive increase in environmental pollution and degradation leads to ecological imbalance is a hot research topic. Besides, the progressive development of smart cities over the globe requires the design of intelligent waste management systems to properly categorize the waste depending upon the nature of biodegradability. Few of… More >

  • Open Access

    ARTICLE

    Fruits and Vegetables Freshness Categorization Using Deep Learning

    Labiba Gillani Fahad1, Syed Fahad Tahir2,*, Usama Rasheed1, Hafsa Saqib1, Mehdi Hassan2, Hani Alquhayz3

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5083-5098, 2022, DOI:10.32604/cmc.2022.023357

    Abstract The nutritional value of perishable food items, such as fruits and vegetables, depends on their freshness levels. The existing approaches solve a binary class problem by classifying a known fruit\vegetable class into fresh or rotten only. We propose an automated fruits and vegetables categorization approach that first recognizes the class of object in an image and then categorizes that fruit or vegetable into one of the three categories: pure-fresh, medium-fresh, and rotten. We gathered a dataset comprising of 60K images of 11 fruits and vegetables, each is further divided into three categories of freshness, using… More >

  • Open Access

    ARTICLE

    Improved Energy Based Multi-Sensor Object Detection in Wireless Sensor Networks

    Thirumoorthy Palanisamy1,*, Daniyal Alghazzawi2, Surbhi Bhatia3, Areej Abbas Malibari2, Pankaj Dadheech4, Sudhakar Sengan5

    Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 227-244, 2022, DOI:10.32604/iasc.2022.023692

    Abstract Wireless Sensor Networks (WSNs) are spatially distributed to independent sensor networks that can sense physical characteristics such as temperature, sound, pressure, energy, and so on. WSNs have secure link to physical environment and robustness. Data Aggregation (DA) plays a key role in WSN, and it helps to minimize the Energy Consumption (EC). In order to have trustworthy DA with a rate of high aggregation for WSNs, the existing research works have focused on Data Routing for In-Network Aggregation (DRINA). Yet, there is no accomplishment of an effective balance between overhead and routing. But EC required… More >

  • Open Access

    ARTICLE

    Object Detection for Cargo Unloading System Based on Fuzzy C Means

    Sunwoo Hwang1, Jaemin Park1, Jongun Won2, Yongjang Kwon3, Youngmin Kim1,*

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 4167-4181, 2022, DOI:10.32604/cmc.2022.023295

    Abstract With the recent increase in the utilization of logistics and courier services, it is time for research on logistics systems fused with the fourth industry sector. Algorithm studies related to object recognition have been actively conducted in convergence with the emerging artificial intelligence field, but so far, algorithms suitable for automatic unloading devices that need to identify a number of unstructured cargoes require further development. In this study, the object recognition algorithm of the automatic loading device for cargo was selected as the subject of the study, and a cargo object recognition algorithm applicable to More >

  • Open Access

    ARTICLE

    An Automated Real-Time Face Mask Detection System Using Transfer Learning with Faster-RCNN in the Era of the COVID-19 Pandemic

    Maha Farouk S. Sabir1, Irfan Mehmood2,*, Wafaa Adnan Alsaggaf3, Enas Fawai Khairullah3, Samar Alhuraiji4, Ahmed S. Alghamdi5, Ahmed A. Abd El-Latif6

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 4151-4166, 2022, DOI:10.32604/cmc.2022.017865

    Abstract Today, due to the pandemic of COVID-19 the entire world is facing a serious health crisis. According to the World Health Organization (WHO), people in public places should wear a face mask to control the rapid transmission of COVID-19. The governmental bodies of different countries imposed that wearing a face mask is compulsory in public places. Therefore, it is very difficult to manually monitor people in overcrowded areas. This research focuses on providing a solution to enforce one of the important preventative measures of COVID-19 in public places, by presenting an automated system that automatically… More >

  • Open Access

    ARTICLE

    Vision Based Real Time Monitoring System for Elderly Fall Event Detection Using Deep Learning

    G. Anitha1,*, S. Baghavathi Priya2

    Computer Systems Science and Engineering, Vol.42, No.1, pp. 87-103, 2022, DOI:10.32604/csse.2022.020361

    Abstract Human fall detection plays a vital part in the design of sensor based alarming system, aid physical therapists not only to lessen after fall effect and also to save human life. Accurate and timely identification can offer quick medical services to the injured people and prevent from serious consequences. Several vision-based approaches have been developed by the placement of cameras in diverse everyday environments. At present times, deep learning (DL) models particularly convolutional neural networks (CNNs) have gained much importance in the fall detection tasks. With this motivation, this paper presents a new vision based… More >

  • Open Access

    ARTICLE

    Traffic Accident Detection Based on Deformable Frustum Proposal and Adaptive Space Segmentation

    Peng Chen1, Weiwei Zhang1,*, Ziyao Xiao1, Yongxiang Tian2

    CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.1, pp. 97-109, 2022, DOI:10.32604/cmes.2022.016632

    Abstract Road accident detection plays an important role in abnormal scene reconstruction for Intelligent Transportation Systems and abnormal events warning for autonomous driving. This paper presents a novel 3D object detector and adaptive space partitioning algorithm to infer traffic accidents quantitatively. Using 2D region proposals in an RGB image, this method generates deformable frustums based on point cloud for each 2D region proposal and then frustum-wisely extracts features based on the farthest point sampling network (FPS-Net) and feature extraction network (FE-Net). Subsequently, the encoder-decoder network (ED-Net) implements 3D-oriented bounding box (OBB) regression. Meanwhile, the adaptive least More >

  • Open Access

    ARTICLE

    Deep Learning Based Audio Assistive System for Visually Impaired People

    S. Kiruthika Devi*, C. N. Subalalitha

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1205-1219, 2022, DOI:10.32604/cmc.2022.020827

    Abstract Vision impairment is a latent problem that affects numerous people across the globe. Technological advancements, particularly the rise of computer processing abilities like Deep Learning (DL) models and emergence of wearables pave a way for assisting visually-impaired persons. The models developed earlier specifically for visually-impaired people work effectually on single object detection in unconstrained environment. But, in real-time scenarios, these systems are inconsistent in providing effective guidance for visually-impaired people. In addition to object detection, extra information about the location of objects in the scene is essential for visually-impaired people. Keeping this in mind, the… More >

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