G. Anitha^1,*, 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 elderly fall event detection using… More >

Peng Chen¹, Weiwei Zhang^1,*, 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 square regression (ALSR) method is… More >

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 current research work presents an… More >

Ajisha Mathias¹, Samiappan Dhanalakshmi^1,*, R. Kumar¹, R. Narayanamoorthi²

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5251-5267, 2022, DOI:10.32604/cmc.2022.021168

Abstract Object recognition and computer vision techniques for automated object identification are attracting marine biologist's interest as a quicker and easier tool for estimating the fish abundance in marine environments. However, the biggest problem posed by unrestricted aquatic imaging is low luminance, turbidity, background ambiguity, and context camouflage, which make traditional approaches rely on their efficiency due to inaccurate detection or elevated false-positive rates. To address these challenges, we suggest a systemic approach to merge visual features and Gaussian mixture models with You Only Look Once (YOLOv3) deep network, a coherent strategy for recognizing fish in challenging underwater images. As an… More >

Wen-Tsai Sung¹, Sung-Jung Hsiao^2,*, Chung-Yen Hsiao¹

Intelligent Automation & Soft Computing, Vol.31, No.2, pp. 1223-1240, 2022, DOI:10.32604/iasc.2022.020746

Abstract This research is based on the system architecture of Edge Computing in the AIoT (Artificial Intelligence & Internet of Things) field. In terms of receiving data, the authors proposed approach employed the camera module as the video source, the ultrasound module as the distance measurement source, and then compile C++ with Raspberry Pi 4B for image lane analysis, while Jetson Nano uses the YOLOv3 algorithm for image object detection. The analysis results of the two single-board computers are transmitted to Motoduino U1 in binary form via GPIO, which is used for data integration and load driving. The load drive has… More >

Shubham Mahajan^1,*, Akshay Raina², Mohamed Abouhawwash^3,4, Xiao-Zhi Gao⁵, Amit Kant Pandit¹

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1541-1556, 2022, DOI:10.32604/cmc.2022.019496

Abstract Like the Covid-19 pandemic, smallpox virus infection broke out in the last century, wherein 500 million deaths were reported along with enormous economic loss. But unlike smallpox, the Covid-19 recorded a low exponential infection rate and mortality rate due to advancement in medical aid and diagnostics. Data analytics, machine learning, and automation techniques can help in early diagnostics and supporting treatments of many reported patients. This paper proposes a robust and efficient methodology for the early detection of COVID-19 from Chest X-Ray scans utilizing enhanced deep learning techniques. Our study suggests that using the Prediction and Deconvolutional Modules in combination… More >

Dengyong Zhang^1,2, Jiawei Hu^1,2, Feng Li^1,2,*, Xiangling Ding³, Arun Kumar Sangaiah⁴, Victor S. Sheng⁵

CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1503-1517, 2021, DOI:10.32604/cmc.2021.017089

Abstract In the past several years, remarkable achievements have been made in the field of object detection. Although performance is generally improving, the accuracy of small object detection remains low compared with that of large object detection. In addition, localization misalignment issues are common for small objects, as seen in GoogLeNets and residual networks (ResNets). To address this problem, we propose an improved region-based fully convolutional network (R-FCN). The presented technique improves detection accuracy and eliminates localization misalignment by replacing position-sensitive region of interest (PS-RoI) pooling with position-sensitive precise region of interest (PS-Pr-RoI) pooling, which avoids coordinate quantization and directly calculates… More >

Huijin Park, Soobin Ou, Jongwoo Lee^*

Intelligent Automation & Soft Computing, Vol.29, No.1, pp. 247-258, 2021, DOI:10.32604/iasc.2021.015274

Abstract Blind people are highly exposed to numerous dangers when they walk alone outside as they cannot obtain sufficient information about their surroundings. While proceeding along a crosswalk, acoustic signals are played, though such signals are often faulty or difficult to hear. The bollards can also be dangerous if they are not made with flexible materials or are located improperly. Therefore, since the blind cannot detect proper information about these obstacles while walking, their environment can prove to be dangerous. In this paper, we propose an object recognition system that allows the blind to walk safely outdoors. The proposed system can… More >

Daniyal Baig¹, Tahir Alyas¹, Muhammad Hamid², Muhammad Saleem³, Saadia Malik⁴, Nadia Tabassum^5,*, Natash Ali Mian⁶

CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3653-3669, 2021, DOI:10.32604/cmc.2021.017948

Abstract The past two decades witnessed a broad-increase in web technology and on-line gaming. Enhancing the broadband confinements is viewed as one of the most significant variables that prompted new gaming technology. The immense utilization of web applications and games additionally prompted growth in the handled devices and moving the limited gaming experience from user devices to online cloud servers. As internet capabilities are enhanced new ways of gaming are being used to improve the gaming experience. In cloud-based video gaming, game engines are hosted in cloud gaming data centers, and compressed gaming scenes are rendered to the players over the… More >

Yunzuo Zhang^1,*, Shasha Zhang¹, Yi Li¹, Jiayu Zhang¹, Zhaoquan Cai², Shui Lam³

CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 4175-4190, 2021, DOI:10.32604/cmc.2021.017011

Abstract With the explosive growth of surveillance video data, browsing videos quickly and effectively has become an urgent problem. Video key frame extraction has received widespread attention as an effective solution. However, accurately capturing the local motion state changes of moving objects in the video is still challenging in key frame extraction. The target center offset can reflect the change of its motion state. This observation proposed a novel key frame extraction method based on moving objects center offset in this paper. The proposed method utilizes the center offset to obtain the global and local motion state information of moving objects,… More >