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  • Open Access

    ARTICLE

    Classification of Echocardiographic Standard Views Using a Hybrid Attention-based Approach

    Zi Ye1, Yogan Jaya Kumar2, Goh Ong Sing2, Fengyan Song3, Xianda Ni4,*

    Intelligent Automation & Soft Computing, Vol.33, No.2, pp. 1197-1215, 2022, DOI:10.32604/iasc.2022.023555

    Abstract The determination of the probe viewpoint forms an essential step in automatic echocardiographic image analysis. However, classifying echocardiograms at the video level is complicated, and previous observations concluded that the most significant challenge lies in distinguishing among the various adjacent views. To this end, we propose an ECHO-Attention architecture consisting of two parts. We first design an ECHO-ACTION block, which efficiently encodes Spatio-temporal features, channel-wise features, and motion features. Then, we can insert this block into existing ResNet architectures, combined with a self-attention module to ensure its task-related focus, to form an effective ECHO-Attention network. More >

  • Open Access

    ARTICLE

    Research of Insect Recognition Based on Improved YOLOv5

    Zhong Yuan1, Wei Fang1,2,*, Yongming Zhao3,*, Victor S. Sheng4

    Journal on Artificial Intelligence, Vol.3, No.4, pp. 145-152, 2021, DOI:10.32604/jai.2021.026902

    Abstract Insects play an important role in the natural ecology, it is of great significance for ecology to research on insects. Nowadays, the invasion of alien species has brought serious troubles and a lot of losses to local life. However, there is still much room for improvement in the accuracy of insect recognition to effectively prevent the invasion of alien species. As the latest target detection algorithm, YOLOv5 has been used in various scene detection tasks, because of its powerful recognition capabilities and extremely high accuracy. As the problem of imbalance of feature maps at different… More >

  • Open Access

    ARTICLE

    Facial Expression Recognition Based on the Fusion of Infrared and Visible Image

    Jiancheng Zou1, Jiaxin Li1,*, Juncun Wei1, Zhengzheng Li1, Xin Yang2

    Journal on Artificial Intelligence, Vol.3, No.3, pp. 123-134, 2021, DOI:10.32604/jai.2021.027069

    Abstract Facial expression recognition is a research hot spot in the fields of computer vision and pattern recognition. However, the existing facial expression recognition models are mainly concentrated in the visible light environment. They have insufficient generalization ability and low recognition accuracy, and are vulnerable to environmental changes such as illumination and distance. In order to solve these problems, we combine the advantages of the infrared and visible images captured simultaneously by array equipment our developed with two infrared and two visible lens, so that the fused image not only has the texture information of visible… More >

  • Open Access

    ARTICLE

    A Novel Feature Aggregation Approach for Image Retrieval Using Local and Global Features

    Yuhua Li1, Zhiqiang He1,2, Junxia Ma1,*, Zhifeng Zhang1,*, Wangwei Zhang1, Prasenjit Chatterjee3, Dragan Pamucar4

    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.1, pp. 239-262, 2022, DOI:10.32604/cmes.2022.016287

    Abstract The current deep convolution features based on retrieval methods cannot fully use the characteristics of the salient image regions. Also, they cannot effectively suppress the background noises, so it is a challenging task to retrieve objects in cluttered scenarios. To solve the problem, we propose a new image retrieval method that employs a novel feature aggregation approach with an attention mechanism and utilizes a combination of local and global features. The method first extracts global and local features of the input image and then selects keypoints from local features by using the attention mechanism. After… More >

  • Open Access

    ARTICLE

    Human Faces Detection and Tracking for Crowd Management in Hajj and Umrah

    Riad Alharbey1, Ameen Banjar1, Yahia Said2,3,*, Mohamed Atri4, Abdulrahman Alshdadi1, Mohamed Abid5

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 6275-6291, 2022, DOI:10.32604/cmc.2022.024272

    Abstract Hajj and Umrah are two main religious duties for Muslims. To help faithfuls to perform their religious duties comfortably in overcrowded areas, a crowd management system is a must to control the entering and exiting for each place. Since the number of people is very high, an intelligent crowd management system can be developed to reduce human effort and accelerate the management process. In this work, we propose a crowd management process based on detecting, tracking, and counting human faces using Artificial Intelligence techniques. Human detection and counting will be performed to calculate the number… More >

  • Open Access

    ARTICLE

    Deep Learning-based Wireless Signal Classification in the IoT Environment

    Hyeji Roh, Sheungmin Oh, Hajun Song, Jinseo Han, Sangsoon Lim*

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5717-5732, 2022, DOI:10.32604/cmc.2022.024135

    Abstract With the development of the Internet of Things (IoT), diverse wireless devices are increasing rapidly. Those devices have different wireless interfaces that generate incompatible wireless signals. Each signal has its own physical characteristics with signal modulation and demodulation scheme. When there exist different wireless devices, they can suffer from severe Cross-Technology Interferences (CTI). To reduce the communication overhead due to the CTI in the real IoT environment, a central coordinator can be able to detect and identify wireless signals existing in the same communication areas. This paper investigates how to classify various radio signals using… More >

  • Open Access

    ARTICLE

    Attention-Based Deep Learning Model for Early Detection of Parkinson's Disease

    Mohd Sadiq1, Mohd Tauheed Khan2,*, Sarfaraz Masood3

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5183-5200, 2022, DOI:10.32604/cmc.2022.020531

    Abstract Parkinson's disease (PD), classified under the category of a neurological syndrome, affects the brain of a person which leads to the motor and non-motor symptoms. Among motor symptoms, one of the major disabling symptom is Freezing of Gait (FoG) that affects the daily standard of living of PD patients. Available treatments target to improve the symptoms of PD. Detection of PD at the early stages is an arduous task due to being indistinguishable from a healthy individual. This work proposed a novel attention-based model for the detection of FoG events and PD, and measuring the… More >

  • Open Access

    ARTICLE

    Image Dehazing Based on Pixel Guided CNN with PAM via Graph Cut

    Fayadh Alenezi*

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3425-3443, 2022, DOI:10.32604/cmc.2022.023339

    Abstract Image dehazing is still an open research topic that has been undergoing a lot of development, especially with the renewed interest in machine learning-based methods. A major challenge of the existing dehazing methods is the estimation of transmittance, which is the key element of haze-affected imaging models. Conventional methods are based on a set of assumptions that reduce the solution search space. However, the multiplication of these assumptions tends to restrict the solutions to particular cases that cannot account for the reality of the observed image. In this paper we reduce the number of simplified… More >

  • Open Access

    ARTICLE

    Attention-Based Bi-LSTM Model for Arabic Depression Classification

    Abdulqader M. Almars*

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3091-3106, 2022, DOI:10.32604/cmc.2022.022609

    Abstract Depression is a common mental health issue that affects a large percentage of people all around the world. Usually, people who suffer from this mood disorder have issues such as low concentration, dementia, mood swings, and even suicide. A social media platform like Twitter allows people to communicate as well as share photos and videos that reflect their moods. Therefore, the analysis of social media content provides insight into individual moods, including depression. Several studies have been conducted on depression detection in English and less in Arabic. The detection of depression from Arabic social media… More >

  • Open Access

    ARTICLE

    A Prediction Method of Fracture Toughness of Nickel-Based Superalloys

    Yabin Xu1,*, Lulu Cui1, Xiaowei Xu2

    Computer Systems Science and Engineering, Vol.42, No.1, pp. 121-132, 2022, DOI:10.32604/csse.2022.022758

    Abstract Fracture toughness plays a vital role in damage tolerance design of materials and assessment of structural integrity. To solve these problems of complexity, time-consuming, and low accuracy in obtaining the fracture toughness value of nickel-based superalloys through experiments. A combination prediction model is proposed based on the principle of materials genome engineering, the fracture toughness values of nickel-based superalloys at different temperatures, and different compositions can be predicted based on the existing experimental data. First, to solve the problem of insufficient feature extraction based on manual experience, the Deep Belief Network (DBN) is used to… More >

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