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  • Open Access

    REVIEW

    Exploring Deep Learning Methods for Computer Vision Applications across Multiple Sectors: Challenges and Future Trends

    Narayanan Ganesh1, Rajendran Shankar2, Miroslav Mahdal3, Janakiraman Senthil Murugan4, Jasgurpreet Singh Chohan5, Kanak Kalita6,*

    CMES-Computer Modeling in Engineering & Sciences, Vol., , DOI:10.32604/cmes.2023.028018

    Abstract Computer vision (CV) was developed for computers and other systems to act or make recommendations based on visual inputs, such as digital photos, movies, and other media. Deep learning (DL) methods are more successful than other traditional machine learning (ML) methods in CV. DL techniques can produce state-of-the-art results for difficult CV problems like picture categorization, object detection, and face recognition. In this review, a structured discussion on the history, methods, and applications of DL methods to CV problems is presented. The sector-wise presentation of applications in this paper may be particularly useful for researchers in niche fields who have… More >

  • Open Access

    ARTICLE

    A Method of Integrating Length Constraints into Encoder-Decoder Transformer for Abstractive Text Summarization

    Ngoc-Khuong Nguyen1.2, Dac-Nhuong Le1, Viet-Ha Nguyen2, Anh-Cuong Le3,*

    Intelligent Automation & Soft Computing, Vol., , DOI:10.32604/iasc.2023.037083

    Abstract Text summarization aims to generate a concise version of the original text. The longer the summary text is, the more detailed it will be from the original text, and this depends on the intended use. Therefore, the problem of generating summary texts with desired lengths is a vital task to put the research into practice. To solve this problem, in this paper, we propose a new method to integrate the desired length of the summarized text into the encoder-decoder model for the abstractive text summarization problem. This length parameter is integrated into the encoding phase at each self-attention step and… More >

  • Open Access

    ARTICLE

    Optical Neural Networks: Analysis and Prospects for 5G Applications

    Doaa Sami Khafaga1, Zongming Lv2, Imran Khan3,4, Shebnam M. Sefat5, Amel Ali Alhussan1,*

    CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2023.039956

    Abstract With the capacities of self-learning, acquainted capacities, high-speed looking for ideal arrangements, solid nonlinear fitting, and mapping self-assertively complex nonlinear relations, neural systems have made incredible advances and accomplished broad application over the final half-century. As one of the foremost conspicuous methods for fake insights, neural systems are growing toward high computational speed and moo control utilization. Due to the inborn impediments of electronic gadgets, it may be troublesome for electronic-implemented neural systems to make the strides these two exhibitions encourage. Optical neural systems can combine optoelectronic procedures and neural organization models to provide ways to break the bottleneck. This… More >

  • Open Access

    ARTICLE

    Data Fusion Architecture Empowered with Deep Learning for Breast Cancer Classification

    Sahar Arooj1, Muhammad Farhan Khan2, Tariq Shahzad3, Muhammad Adnan Khan4,5,6, Muhammad Umar Nasir7, Muhammad Zubair1, Atta-ur-Rahman8, Khmaies Ouahada3,*

    CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2023.043013

    Abstract Breast cancer (BC) is the most widespread tumor in females worldwide and is a severe public health issue. BC is the leading reason of death affecting females between the ages of 20 to 59 around the world. Early detection and therapy can help women receive effective treatment and, as a result, decrease the rate of breast cancer disease. The cancer tumor develops when cells grow improperly and attack the healthy tissue in the human body. Tumors are classified as benign or malignant, and the absence of cancer in the breast is considered normal. Deep learning, machine learning, and transfer learning… More >

  • Open Access

    REVIEW

    Bone marrow mesenchymal stem cell-induced autophagy ameliorates TNBS-induced experimental colitis by downregulating the NLRP3 inflammasome

    JINJIN FU1,#, XIAOYUE FENG2,#, JUAN WEI2, XIANG GENG1, YU GONG1, FENGDONG LI1, SHAOHUA ZHUANG1, JIN HUANG1, FANGYU WANG2,*

    BIOCELL, Vol., , DOI:10.32604/biocell.2023.042586

    Abstract Background: This study aimed to elucidate the potential mechanisms through which bone marrow-derived mesenchymal stem cells (BM-MSCs) may be effective in alleviating experimental colitis induced by treatment with 2,4,6-trinitrobenzene-sulfonate acid (TNBS), specifically through autophagy modulation. Methods: BM-MSCs were collected from BALB/c mice for subsequent experiments. The study employed cell counting kits (CCK-8) to investigate the impact of the MSC-conditioned medium (M medium) on the proliferation of RAW264.7 macrophages. The GFP-mRFP-LC3 adenovirus was transfected into RAW264.7 to detect autophagic flux. The gene expression of cytokines was assessed through quantitative reverse transcription polymerase chain reaction (qRT-PCR). Western blot analysis was employed to… More >

  • Open Access

    ARTICLE

    A Transient-Pressure-Based Numerical Approach for Interlayer Identification in Sand Reservoirs

    Hao Luo1, Haibo Deng1, Honglin Xiao1, Shaoyang Geng2,*, Fu Hou1, Gang Luo1, Yaqi Li2

    FDMP-Fluid Dynamics & Materials Processing, Vol., , DOI:10.32604/fdmp.2023.043565

    Abstract Almost all sandstone reservoirs contain interlayers. The identification and characterization of these interlayers is critical for minimizing the uncertainty associated with oilfield development and improving oil and gas recovery. Identifying interlayers outside wells using identification methods based on logging data and machine learning is difficult and seismic-based identification techniques are expensive. Herein, a numerical model based on seepage and well-testing theories is introduced to identify interlayers using transient pressure data. The proposed model relies on the open-source MATLAB Reservoir Simulation Toolbox. The effects of the interlayer thickness, position, and width on the pressure response are thoroughly investigated. A procedure for… More >

  • Open Access

    ARTICLE

    Optimizing the Diameter of Plugging Balls in Deep Shale Gas Wells

    Yi Song1, Zheyu Hu2,*, Cheng Shen1, Lan Ren2, Xingwu Guo1, Ran Lin2, Kun Wang3, Zhiyong Zhao4

    FDMP-Fluid Dynamics & Materials Processing, Vol., , DOI:10.32604/fdmp.2023.030521

    Abstract Deep shale gas reserves that have been fractured typically have many relatively close perforation holes. Due to the proximity of each fracture during the formation of the fracture network, there is significant stress interference, which results in uneven fracture propagation. It is common practice to use “balls” to temporarily plug fracture openings in order to lessen liquid intake and achieve uniform propagation in each cluster. In this study, a diameter optimization model is introduced for these plugging balls based on a multi-cluster fracture propagation model and a perforation dynamic abrasion model. This approach relies on proper consideration of the multiphase… More >

  • Open Access

    ARTICLE

    Optimizing Fully Convolutional Encoder-Decoder Network for Segmentation of Diabetic Eye Disease

    Abdul Qadir Khan1, Guangmin Sun1,*, Yu Li1, Anas Bilal2, Malik Abdul Manan1

    CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2023.043239

    Abstract In the emerging field of image segmentation, Fully Convolutional Networks (FCNs) have recently become prominent. However, their effectiveness is intimately linked with the correct selection and fine-tuning of hyperparameters, which can often be a cumbersome manual task. The main aim of this study is to propose a more efficient, less labour-intensive approach to hyperparameter optimization in FCNs for segmenting fundus images. To this end, our research introduces a hyperparameter-optimized Fully Convolutional Encoder-Decoder Network (FCEDN). The optimization is handled by a novel Genetic Grey Wolf Optimization (G-GWO) algorithm. This algorithm employs the Genetic Algorithm (GA) to generate a diverse set of… More >

  • Open Access

    ARTICLE

    Gender Differences in the Incidence and Related Factors of Low Social Support among Adolescents with Subthreshold Depression

    Yi Shi, Fangfang Shangguan*, Jing Xiao*

    International Journal of Mental Health Promotion, Vol., , DOI:10.32604/ijmhp.2023.030516

    Abstract Background: Social support is related to depression, but the gender differences and related factors that contribute to low social support among adolescents with subthreshold depression remain to be elucidated. This study explores the relationship between social support and depression, in addition to the gender difference in the incidence of low social support among adolescents with subthreshold depression and its related factors. Methods: A total of 371 Chinese adolescents with subthreshold depression were recruited. All subjects were rated on the Social Support Scale for Adolescents, the Response Style Scale, the Self-Perception Profile for Children, the Individualism-collectivism scale. Results: Binary logistic regression… More >

  • Open Access

    ARTICLE

    Mathematical Study of MHD Micropolar Fluid Flow with Radiation and Dissipative Impacts over a Permeable Stretching Sheet: Slip Effects Phenomena

    Pudhari Srilatha1, Ahmed M. Hassan2, B. Shankar Goud3,*, E. Ranjit Kumar4

    Frontiers in Heat and Mass Transfer, Vol., , DOI:10.32604/fhmt.2023.043023

    Abstract The purpose of this research is to investigate the influence that slip boundary conditions have on the rate of heat and mass transfer by examining the behavior of micropolar MHD flow across a porous stretching sheet. In addition to this, the impacts of thermal radiation and viscous dissipation are taken into account. With the use of various computing strategies, numerical results have been produced. Similarity transformation was utilized in order to convert the partial differential equations (PDEs) that regulated energy, rotational momentum, concentration, and momentum into ordinary differential equations (ODEs). As compared to earlier published research, MATLAB inbuilt solver solution… More >

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