Data driven applications for industry 4.0 and beyond / edited by Nazmul Siddique, Mohammad Shamsul Arefin, K. M. Azharul Hasan, M Shamim Kaiser.

Format Electronic
Publication InfoBoca Raton, FL : CRC Press, 2025.
Descriptionpages cm
Supplemental ContentFull text available from eBooks on EBSCOhost
Subjects

Other author/creatorSiddique, N. H. http://id.loc.gov/authorities/names/nb2004309347 http://id.loc.gov/rwo/agents/nb2004309347.
Other author/creatorArefin, Mohammad Shamsul http://id.loc.gov/authorities/names/n2022055217 http://id.loc.gov/rwo/agents/n2022055217.
Other author/creatorHasan, K. M. Azharul http://id.loc.gov/authorities/names/n2025030849 http://id.loc.gov/rwo/agents/n2025030849.
Other author/creatorKaiser, M. Shamim http://id.loc.gov/authorities/names/no2023020143 http://id.loc.gov/rwo/agents/no2023020143.
Contents A system that analyzes Bengali text on facebook posts using machine learning to spot suspicious content / Meherun Nesa Shraboni and Mohammad Shamsul Arefin -- A reversible transformer based Bangla conversational agent / Md Fatin Ishrak, Shakila Zaman, Jannatun Nahar, and Zarin Tasnim Promi -- URL based website classification using deep learning and word based multiple N-gram models / Sultan Mahmud and Sayad Ahmed Chowdhury -- BN-HTRd : a benchmark dataset for document level offline Bangla handwritten text recognition (HTR) and line segmentation / Md. Ataur Rahman, Nazifa Tabassum, Mitu Paul, Riya Pal, and Mohammad Khairul Islam -- RiceNe t: accurate classification of rice varieties using convolutional neural networks / Contents Nusrat Jahan Shammey, Adit Ishraq, Sayefa Arafah, Sadiya Akter Mim, Dr. Firoz Mridha, and Md. Abdul Hamid -- Vehicle name plate detection and blurring from social media images using image processing and deep learning / Ismail Hossain, Sultana Umme Habiba, Sayeda Fatiha Maya, and Kausar Alam -- DCNN-SMD : a deep convolutional neural network model to diagnosis, prognosis, and characterise sperm morphology / Abdullah Al Nomaan Nafi, Md Imran Hasan, Nosin Ibna Mahbub, Md. Alamgir Hossain, and Md Zahidul Islam -- Muslim Salat gesture recognition framework : integrating deep transfer learning and machine learning / Md. Moradul Siddique, Md Nasim Adnan, Mohammad Farhad Bulbul, Hazrat Ali, Sk. Shalauddin Kabir, and Syed Md. Galib -- BHSGR-Net : a light-weight convolutional neural architecture for recognition of Bengali hand sign gestures / Md. Barhanul Karim, Md. Safaiat Hossain, Rahul Reza Roky, and Azmain Yakin Srizon -- Can machine learning help identify suicidal Tweets? An ensemble classifier approach /Sabiha Firdaus, Md Nahid Hasan, Ashfia Jannat Keya, Md. Mohsin Kabir, and M. F. Mridha -- An interpretable systematic review of machine learning models for predictive maintenance of aircraft engine / Abdullah Al Hasib, Ashikur Rahman (Corresponding Author), Mahpara Khabir, and Md. Tanvir Rouf Shawon -- Multichannel attention networks with ensembled transfer learning to recognize Bangla handwritten character -- Development of a deep learning classification model for improved rainfall prediction in Ireland / Md. Badiuzzaman Biplob and Md. Mokammel Haque -- Defect detection of casting products using deep learning : a method based on convolutional neural networks / Mumtahina Alam, Monowar Wadud Hridoy, Kazi Riad Uddin, Kazi Naimur Rahman, and Md. Asifur Rahman -- OLD-TL : offensive language detection in gaming live stream using transfer learning / Ferdousi Haque and Atanu Shome -- Predicting stress in Bangladeshi University students : a LIMEInterpretable machine learning approach / Md. Hamid Hosen, Mohammad Tanvirul Islam, Kahakashan Ashraf, and Promila Haque -- Early detection of system failure using machine learning techniques / Hasibul Islam, Md Shahzamal, Md. Dulal Haque, and Md. Selim Hossain -- Churn prediction using machine learning in the tours and travel industry / Syed Mominin Islam Tamim, Md. Nadim Hasan, And Md.Tafsimul Islam Tanzid.
Abstract "The increasing reliance on automation and data-driven decision-making is transforming industries. As technology advances, the need for more intelligent and efficient systems is growing. This book explores how data-driven approaches are being applied in various fields to solve real-world challenges. With contributions from researchers and professional, the chapters discuss practical applications of modern computational techniques. Topics range from optimizing industrial processes to improving predictive systems in different sectors. The book also emphasizes the importance of responsible and interpretable technology to ensure fairness and transparency. This book is a valuable resource for students, researchers, and professionals looking to understand the evolving role of data in industry. It provides insights into emerging trends and encourages further exploration in the field of intelligent systems and automation"-- Provided by publisher.
Bibliography noteIncludes bibliographical references and index.
Access restrictionAvailable only to authorized users.
Technical detailsMode of access: World Wide Web
Genre/formElectronic books.
LCCN 2025018487
ISBN9781032643366 hardback
ISBN9781032648699 paperback
ISBNebook

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