Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (1,767)
  • Open Access

    ARTICLE

    Research on Viewpoint Extraction in Microblog

    Yabin Xu1,2,*, Shujuan Chen2, Xiaowei Xu3

    Intelligent Automation & Soft Computing, Vol.30, No.2, pp. 495-511, 2021, DOI:10.32604/iasc.2021.018896

    Abstract In order to quickly get the viewpoint of key opinion leaders(KOL) on public events, a method of opinion mining in Weibo is put forward. Firstly, according to the characteristics of Weibo language, the non-viewpoint sentence recognition rule is formulated, and some non-viewpoint sentence is eliminated accordingly. Secondly, based on the constructed FastText-XGBoost viewpoint sentence recognition model, the second classification is carried out to identify the opinion sentence according to the dominant and recessive features of Weibo. Finally, the group of evaluation object and evaluation word is extracted from the opinion sentence, according to our proposed multi-task learning BiLSTM-CRFs model. In… More >

  • Open Access

    ARTICLE

    Modeling Habit Patterns Using Conditional Reflexes in Agency

    Qura-Tul-Ain Khan1, Taher M. Ghazal2,3, Sagheer Abbas1, Wasim Ahmad Khan1, Muhammad Adnan Khan5,6, Raed A. Said4, Munir Ahmad1, Muhammad Asif1,*

    Intelligent Automation & Soft Computing, Vol.30, No.2, pp. 539-552, 2021, DOI:10.32604/iasc.2021.018888

    Abstract For decision-making and behavior dynamics in humans, the principal focus is on cognition. Cognition can be described using cognitive behavior, which has multiple states. This cognitive behavior can be incorporated with one of the internal mental states’ help, which includes desires, beliefs, emotions, intentions, different levels of knowledge, goals, skills, etc. That leads to habit development. Habits are highly refined patterns formed in the unconscious that evolve from conscious skill patterns in the human, and the same process can be implemented in the agency. These habit patterns are the outcomes of many internal values that may vary due to variations… More >

  • Open Access

    ARTICLE

    Intelligent Model Of Ecosystem For Smart Cities Using Artificial Neural Networks

    Tooba Batool1, Sagheer Abbas1, Yousef Alhwaiti2, Muhammad Saleem1, Munir Ahmad1, Muhammad Asif1,*, Nouh Sabri Elmitwally2,3

    Intelligent Automation & Soft Computing, Vol.30, No.2, pp. 513-525, 2021, DOI:10.32604/iasc.2021.018770

    Abstract A Smart City understands the infrastructure, facilities, and schemes open to its citizens. According to the UN report, at the end of 2050, more than half of the rural population will be moved to urban areas. With such an increase, urban areas will face new health, education, Transport, and ecological issues. To overcome such kinds of issues, the world is moving towards smart cities. Cities cannot be smart without using Cloud computing platforms, the Internet of Things (IoT). The world has seen such incredible and brilliant ideas for rural areas and smart cities. While considering the Ecosystem in Smart Cities,… More >

  • Open Access

    ARTICLE

    Visual Saliency Prediction Using Attention-based Cross-modal Integration Network in RGB-D Images

    Xinyue Zhang1, Ting Jin1,*, Mingjie Han1, Jingsheng Lei2, Zhichao Cao3

    Intelligent Automation & Soft Computing, Vol.30, No.2, pp. 439-452, 2021, DOI:10.32604/iasc.2021.018643

    Abstract Saliency prediction has recently gained a large number of attention for the sake of the rapid development of deep neural networks in computer vision tasks. However, there are still dilemmas that need to be addressed. In this paper, we design a visual saliency prediction model using attention-based cross-model integration strategies in RGB-D images. Unlike other symmetric feature extraction networks, we exploit asymmetric networks to effectively extract depth features as the complementary information of RGB information. Then we propose attention modules to integrate cross-modal feature information and emphasize the feature representation of salient regions, meanwhile neglect the surrounding unimportant pixels, so… More >

  • Open Access

    ARTICLE

    Color Contrast Enhancement on Pap Smear Images Using Statistical Analysis

    Nadzirah Nahrawi1, Wan Azani Mustafa2,3,*, Siti Nurul Aqmariah Mohd Kanafiah1, Mohd Yusoff Mashor1

    Intelligent Automation & Soft Computing, Vol.30, No.2, pp. 431-438, 2021, DOI:10.32604/iasc.2021.018635

    Abstract In the conventional cervix cancer diagnosis, the Pap smear sample images are taken by using a microscope,causing the cells to be hazy and afflicted by unwanted noise. The captured microscopic images of Pap smear may suffer from some defects such as blurring or low contrasts. These problems can hide and obscure the important cervical cell morphologies, leading to the risk of false diagnosis. The quality and contrast of the Pap smear images are the primary keys that could affect the diagnosis’ accuracy. The paper's main objective is to propose the best contrast enhancement to eliminate contrast problems in images and… More >

  • Open Access

    ARTICLE

    Security Empowered System-on-Chip Selection for Internet of Things

    Ramesh Krishnamoorthy*, Kalimuthu Krishnan

    Intelligent Automation & Soft Computing, Vol.30, No.2, pp. 403-418, 2021, DOI:10.32604/iasc.2021.018560

    Abstract Due to the rapid growth of embedded devices, the selection of System-on-Chip (SoC) has a stronger influence to enable hardware security in embedded system design. System-on-chip (SoC) devices consist of one or more CPUs through wide-ranging inbuilt peripherals for designing a system with less cost. The selection of SoC is more significant to determine the suitability for secured application development. The design space analysis of symmetric key approaches including rivest cipher (RC5), advanced encryption standard (AES), data encryption standard (DES), international data encryption algorithm (IDEA), elliptic curve cryptography (ECC), MX algorithm, and the secure hash algorithm (SHA-256) are compared to… More >

  • Open Access

    ARTICLE

    Binaural Speech Separation Algorithm Based on Deep Clustering

    Lin Zhou1,*, Kun Feng1, Tianyi Wang1, Yue Xu1, Jingang Shi2

    Intelligent Automation & Soft Computing, Vol.30, No.2, pp. 527-537, 2021, DOI:10.32604/iasc.2021.018414

    Abstract Neutral network (NN) and clustering are the two commonly used methods for speech separation based on supervised learning. Recently, deep clustering methods have shown promising performance. In our study, considering that the spectrum of the sound source has time correlation, and the spatial position of the sound source has short-term stability, we combine the spectral and spatial features for deep clustering. In this work, the logarithmic amplitude spectrum (LPS) and the interaural phase difference (IPD) function of each time frequency (TF) unit for the binaural speech signal are extracted as feature. Then, these features of consecutive frames construct feature map,… More >

  • Open Access

    ARTICLE

    Conveyor Belt Detection Based on Deep Convolution GANs

    Xiaoli Hao1,*, Xiaojuan Meng1, Yueqin Zhang1, Jindong Xue2, Jinyue Xia3

    Intelligent Automation & Soft Computing, Vol.30, No.2, pp. 601-613, 2021, DOI:10.32604/iasc.2021.017963

    Abstract The belt conveyor is essential in coal mine underground transportation. The belt properties directly affect the safety of the conveyor. It is essential to monitor that the belt works well. Traditional non-contact detection methods are usually time-consuming, and they only identify a single instance of damage. In this paper, a new belt-tear detection method is developed, characterized by two time-scale update rules for a multi-class deep convolution generative adversarial network. To use this method, only a small amount of image data needs to be labeled, and batch normalization in the generator must be removed to avoid artifacts in the generated… More >

  • Open Access

    ARTICLE

    Person Re-Identification Based on Joint Loss and Multiple Attention Mechanism

    Yong Li, Xipeng Wang*

    Intelligent Automation & Soft Computing, Vol.30, No.2, pp. 563-573, 2021, DOI:10.32604/iasc.2021.017926

    Abstract Person re-identification (ReID) is the use of computer vision and machine learning techniques to determine whether the pedestrians in the two images under different cameras are the same person. It can also be regarded as a matching retrieval task for person targets in different scenes. The research focuses on how to obtain effective person features from images with occlusion, angle change, and target attitude change. Based on the present difficulties and challenges in ReID, the paper proposes a ReID method based on joint loss and multi-attention network. It improves the person re-identification algorithm based on global characteristics, introduces spatial attention… More >

  • Open Access

    ARTICLE

    Game-Theory Based Graded Diagnosis Strategies of Craniocerebral Injury

    Yiming Liu1, Ke Chen1, Lanzhen Bian2, Lei Ren3, Jing Hu4,*, Jinyue Xia5

    Intelligent Automation & Soft Computing, Vol.30, No.2, pp. 553-561, 2021, DOI:10.32604/iasc.2021.017391

    Abstract Craniocerebral injury is a common surgical emergency in children. It has the highest mortality and disability rate, and the second highest incidence rate. Accidental injuries due to falls, sports and traffic accidents are the main causes of craniocerebral injury. In recent years, the incidence rate of craniocerebral injury in children has continued to rise, which injury stretches out the limited medical resources. Moreover, it is very difficult to deal with complex craniocerebral trauma in the hospital of county town, in which is not rich in medical resources because of the lack of experienced doctors and nurses. In addition, some children… More >

Displaying 1241-1250 on page 125 of 1767. Per Page