Qingyang Zhou¹, Jiaohua Qin^1,*, Xuyu Xiang¹, Yun Tan¹, Neal N. Xiong²

CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 159-174, 2021, DOI:10.32604/cmc.2021.017480

Abstract The existing safety helmet detection methods are mainly based on one-stage object detection algorithms with high detection speed to reach the real-time detection requirements, but they can’t accurately detect small objects and objects with obstructions. Therefore, we propose a helmet detection algorithm based on the attention mechanism (AT-YOLO). First of all, a channel attention module is added to the YOLOv3 backbone network, which can adaptively calibrate the channel features of the direction to improve the feature utilization, and a spatial attention module is added to the neck of the YOLOv3 network to capture the correlation between any positions in the… More >

Javaria Amin¹, Muhammad Sharif², Muhammad Almas Anjum³, Ayesha Siddiqa¹, Seifedine Kadry⁴, Yunyoung Nam^5,*, Mudassar Raza²

CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 785-799, 2021, DOI:10.32604/cmc.2021.015249

Abstract White blood cells (WBCs) are a vital part of the immune system that protect the body from different types of bacteria and viruses. Abnormal cell growth destroys the body’s immune system, and computerized methods play a vital role in detecting abnormalities at the initial stage. In this research, a deep learning technique is proposed for the detection of leukemia. The proposed methodology consists of three phases. Phase I uses an open neural network exchange (ONNX) and YOLOv2 to localize WBCs. The localized images are passed to Phase II, in which 3D-segmentation is performed using deeplabv3 as a base network of… More >

Jinxing Niu^1,*, Qingsheng Hu¹, Yi Niu¹, Tao Zhang¹, Sunil Kumar Jha²

CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2221-2229, 2021, DOI:10.32604/cmc.2021.017073

Abstract Object recognition and location has always been one of the research hotspots in machine vision. It is of great value and significance to the development and application of current service robots, industrial automation, unmanned driving and other fields. In order to realize the real-time recognition and location of indoor scene objects, this article proposes an improved YOLOv3 neural network model, which combines densely connected networks and residual networks to construct a new YOLOv3 backbone network, which is applied to the detection and recognition of objects in indoor scenes. In this article, RealSense D415 RGB-D camera is used to obtain the… More >

Javaria Amin¹, Muhammad Almas Anjum², Muhammad Sharif³, Seifedine Kadry⁴, Yunyoung Nam^5,*, ShuiHua Wang⁶

CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2693-2709, 2021, DOI:10.32604/cmc.2021.016871

Abstract Recognition of human gait is a difficult assignment, particularly for unobtrusive surveillance in a video and human identification from a large distance. Therefore, a method is proposed for the classification and recognition of different types of human gait. The proposed approach is consisting of two phases. In phase I, the new model is proposed named convolutional bidirectional long short-term memory (Conv-BiLSTM) to classify the video frames of human gait. In this model, features are derived through convolutional neural network (CNN) named ResNet-18 and supplied as an input to the LSTM model that provided more distinguishable temporal information. In phase II,… More >

Xinyue Lv¹, Xiaofeng Lian^2,*, Li Tan¹, Yanyan Song¹, Chenyu Wang³

Intelligent Automation & Soft Computing, Vol.28, No.2, pp. 513-526, 2021, DOI:10.32604/iasc.2021.016450

Abstract With the rapid development of the Internet of Things and advanced sensors, vision-based monitoring and forecasting applications have been widely used. In the context of the Internet of Things, visual devices can be regarded as network perception nodes that perform complex tasks, such as real-time monitoring of road traffic flow, target detection, and multi-target tracking. We propose the High-Performance detection and Multi-Correlation measurement algorithm (HPMC) to address the problem of target occlusion and perform trajectory correlation matching for multi-target tracking. The algorithm consists of three modules: 1) For the detection module, we proposed the You Only Look Once(YOLO)v3_plus model, which… More >

Qiyuan Liu, Shuhua Lu^*, Lingqiang Lan

Computer Systems Science and Engineering, Vol.37, No.2, pp. 283-295, 2021, DOI:10.32604/csse.2021.014086

Abstract In recent years, face detection has attracted much attention and achieved great progress due to its extensively practical applications in the field of face based computer vision. However, the tradeoff between accuracy and efficiency of the face detectors still needs to be further studied. In this paper, using Darknet-53 as backbone, we propose an improved YOLOv3-attention model by introducing attention mechanism and data augmentation to obtain the robust face detector with high accuracy and efficiency. The attention mechanism is introduced to enhance much higher discrimination of the deep features, and the trick of data augmentation is used in the training… More >

Huifang Qian¹, Xuan Zhou^{1, *}, Mengmeng Zheng¹

CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2153-2167, 2020, DOI:10.32604/cmc.2020.011843

Abstract The core technology in an intelligent video surveillance system is that detecting and recognizing abnormal behaviors timely and accurately. The key breakthrough point in recognizing abnormal behaviors is how to obtain the effective features of the picture, so as to solve the problem of recognizing them. In response to this difficulty, this paper introduces an adjustable jump link coefficients model based on the residual network. The effective coefficients for each layer of the network can be set after using this model to further improving the recognition accuracy of abnormal behavior. A convolution kernel of 1×1 size is added to reduce… More >

Yanming Wang^{1, 2, 3}, Kebin Jia^{1, 2, 3}, Pengyu Liu^{1, 2, 3, *}

Journal on Artificial Intelligence, Vol.2, No.3, pp. 113-124, 2020, DOI:10.32604/jai.2020.010137

Abstract In recent years, the problem of “Impolite Pedestrian” in front of the zebra crossing has aroused widespread concern from all walks of life. The traffic sector’s governance measures have become more serious. The traditional way of governance is onsite law enforcement, which requires a lot of manpower and material resources and is low efficiency. An enhanced YOLOv3-tiny model is proposed for pedestrians and vehicle detection in traffic monitoring. By modifying the backbone network structure of YOLOv3- tiny model, introducing deep detachable convolution operation, and designing the basic residual block unit of the network, the feature extraction ability of the backbone… More >

Hongrui Zhang¹, Wenxue Wei^{1, *}, Xinguang Xiao¹, Song Yang¹, Wanlu Shao¹

CMC-Computers, Materials & Continua, Vol.63, No.1, pp. 457-468, 2020, DOI:10.32604/cmc.2020.06988

Abstract This DC-YOLO Model was designed in order to improve the efficiency for appraising dangerous class of buildings and avoid manual intervention, thereby making the appraisal results more objective. It is an automated method designed based on deep learning and target detection algorithms to appraise the dangerous class of building masonry component. Specifically, it (1) adopted K-means clustering to obtain the quantity and size of the prior boxes; (2) expanded the grid size to improve identification to small targets; (3) introduced in deformable convolution to adapt to the irregular shape of the masonry component cracks. The experimental results show that, comparing… More >

SONIA ROSENFELDT, BEATRIZ GLORIA GALATI

BIOCELL, Vol.32, No.1, pp. 41-47, 2008, DOI:10.32604/biocell.2008.32.041

Abstract Eleven Oxalis L. species from the province of Buenos Aires (Argentina) were investigated with scanning and transmission electron microscopes. We identified four different types and two subtypes of orbicules. We conclude that the close morphological similarity between these species is also reflected in their orbicules, and we suggest that the orbicules morphology may be a useful character in systematic studies. More >