Description |
1 online resource (xxxiv, 454 pages) |
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text/computer/online resource/ |
Subject |
Computational intelligence -- Congresses.
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Information technology -- Congresses.
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Contents |
PART I: COMPUTATIONAL INTELLIGENCE IN IMAGE PROCESSING1. A Study of Issues and Challenges with Digital Image ProcessingUrmila Pilania, Ankit Dagar, Sagar Aggarwal, and Aditya Pathak2. A Methodical View of Prerequisites of Picture Combination, Strategies, Key Indicators with Usage in Real Life and Scientific Domains Facilitating Smart Ubiquitous EnvironmentVineeta Singh and Vandana Dixit Kaushik3. A Study of Emerging Issues and Possibilities for Breast Cancer Diagnosis Using Image ModalitiesAnkur Kumar Aggarwal and Mrinal Pandey4. Pap Smear Image Segmentation Using Chan-Vese Based Adaptive Primal Dual Splitting AlgorithmB. Chitra and S. S.Kumar5. Satellite Image Compression by Random Forest Optimization Techniques and Performance Comparison Using Multispectral Image Compression MethodSrikanth Bethu, Sanjana Vasireddy, D. Ushasree, Md Asrar Ahmed, and P. Vara Prasad6. Learning Spatio-Temporal Features for Movie Scene Retrieval Using a 3D Convolutional AutoencoderVidit Kumar, Vikas Tripathi, and Bhaskar Pant7. Person Reidentification Using Deep Learning and Neural NetworksParneeta Dhaliwal, Riya Sapr, Rishabh Dhiman, and Abhyuday GuptaPART II: COMPUTATIONAL INTELLIGENCE IN HEALTHCARE8. A Systematic Literature Review in Health Informatics Using Data Mining TechniquesAnjali Mehta and Dr. Deepa Bura9. Utilization of Artificial Intelligence Based Methods for Preoperative Prediction in Shoulder Arthroplasty: SurveyMilind Tote and Dr. Shrikant V. Sonekar10. Role of Computer-Based Intelligence for Prognostication a Social Well-Being and Identifying Frailty and DrawbacksSandeep Gupta, Nitin Tyagi, Manjula Jain, Shekhar Singh, and Krishan Kumar Saraswat11. Health Informatics Support for Occurrence Administration Using Artificial Intelligence and Deep Learning: COVID-19 Pandemic ResponseAkshat Jain, Ritu Pal, and Jagdish Chandra Patni12. Machine Learning Approach for Prediction Analysis of COVID-19Vaishali Garg, Khushboo Tripathi, and Deepthi Sehrawat13. Assessment of Generalized Anxiety Disorder and Mood Disorder in Undergraduate Students during the Coronavirus Disease (COVID-19) PandemicDevesh Kumar Upadhyay, Subrajeet Mohapatra, and Niraj Kumar Singh14. Evaluation of Deep Learning Models for Medical Tools ClassificationShweta Bali and S. S Tyagi15. Cervical Cancer Diagnosis and Prediction: An Application of Machine Learning TechniquesMamta Arora, Sanjeev Dhawan, and Kulvinder Singh16. The Working Analysis on Machine Learning Algorithms to Predict Diabetes and Breast CancerSrikanth Bethu, Vempati Krishna, Boda Sindhuja, Damarla Lakshmi Rohita, and P Gopala Krishna17. An Ensemble of AdaBoost with Multilayer Perceptron for Heart Disease PredictionSyed Heena Andrabi, Mrinal Pandey, and Ram ChatterjeePART III: TECHNIQUES FOR NATURAL LANGUAGE PROCESSING18. An Empirical Study of Text Summarization Techniques Using Extractive ApproachesSumita Gupta and Mohit Gambhir19. Design and Comparative Analysis of Inverted Indexing of Text DocumentsGunjan Chandwani, Sarika Narender, and Meena Chaudhary20. Acoustic Musical Instrument RecognitionUsha Mittal, Pooja Rana, Dilpreet Singh, and Priyanka Chawla21. Classification of Accented Voice Using RNN and GANArchit Prashant Patil, Parikansh Ahluwalia, Siddharth Yadav, and Preeti Kaur22. Speech Emotion Recognition Using LSTMSarika Gaind, Shubham Budhiraja, Deepak Gauba, and Ms. Manpreet Kaur23. Interpretation of American Sign Language Using Convolutional Neural NetworksVikas Thada, Utpal Shrivastava, and Apresh Agrawal24. Emotional Intelligence: An Approach to Analyze Stress Using Speech and Face RecognitionShambhavi Mishra, Seeripi Naga Surya, and Sumita Gupta25. Proposed Integrated Framework for Emotion Recognition: A Futuristic ApproachRamesh Narwal and Dr. Himanshu AggarwalPART IV: COMPUTATIONAL INTELLIGENCE IN SMART CITIES26. A Review on Machine Learning Techniques for Human Actions RecognitionDiana Nagpall and Dr. Rajiv Kumar27. Fog-Based Intelligent Traffic Phase Timing Regulation SystemSahil and Sandeep Kumar Sood28. Deep Learning Classification Model for Detection of Traffic SignsVikas Thada, Utpal Shrivastava, Gitika, and Garima29. Understanding Road Scene Images Using CNN FeaturesAnamika Maurya and Satish Chand30. Profitable Crop Prediction for the State of Odisha Using Machine Learning AlgorithmsVaibhav Sinha, Preeti Mishra, and Junali Jasmine Jena31. CapGAN: IoT-Based Cropping Patterns Prediction and Recommendation for Crop CultivationSathya K.and Rajalakshmi M. |
Summary |
The new book presents a valuable selection of state-of-the-art technological advancements using the concepts of AI and machine learning, highlighting the use of predictive analytics of data to find timely solutions toreal-time problems. It helps to identify applicable approaches in order to enhance, automate, and develop effective solutions to challenges in data science and artificial intelligence. The various novel approaches include applications in healthcare, natural language processing, and smart cities. As such, the book is divided into sections that address: Computational Intelligence in Image Processing Computational Intelligence in Healthcare Techniques for Natural Language Processing Computational Intelligence in Smart Cities The very diverse range of topics include AI and machine learning applications for In security: For using digital image processing for image fusion (face recognition, feature extraction, object detection as well tracking, moving object identification), for person re-identification for security purposes. In healthcare and medicine: For diagnosis and prediction of breast cancer, other cancers, diabetes, heart disease; for predicting susceptibility to COVID-19; for prediction of mood and anxiety disorders. In agriculture: For prediction of crop profit; for prediction of cropping patterns and recommendation for crop cultivation. In traffic science/smart cities: For understanding road scene images, for detection of traffic signs, for devising a fog-based intelligent traffic phase timing regulation system In language/speech/text: For automatic text summarization, for document indexing for unstructured data, for speech/accent recognition, for sound separation, for American Sign Language interpretation for nonsigners, for emotional recognition and analysis through speech, body postures with facial expressions, and other body movements (to improve the performance of virtual personal assistants / emotion recognition using speech, body postures with facial expressions and other body movements. This volume offers valuable information for researchers working in interdisciplinary or multidisciplinary areas of healthcare, image analysis, natural language processing, and smart cities. This includes academicians, people in industry, and students with engineering background with research interest in these areas. These peer-review chapters were selected from the International Conference on Computational Intelligence in Analytics and Information Systems (CIAIS- 2021), held in April 2021 at Manav Rachna University, India. Together with Volume 2: Advances in Digital Transformation, this 2-volume set offers an abundacne of valuable information on emerging technologies in computational intelligence in information systems focusing on data science and artificial intelliegence. |
Note |
Hardeo Kumar Thakur, PhD, is working as an Associate Professor in the Department of Computer Science and Technology of Manav Rachna University, Faridabad, India.With over 10 years of teaching and research experience, he focuses on data mining, dynamic graph mining, machine learning and big data analytics. Manpreet Kaur, PhD, is an Associate Professor in the Department of Computer Science and Technology, Manav Rachna University, India. She has more than 14 years of teaching and research experience.Her current research ison machine learning, deep learning, and natural language processing. Parneeta Dhaliwal, PhD, has over 16 years of experience in teaching and research. Presently, she is an Associate Professor in the Department of Computer Science and Technology, Manav Rachna University, India. She is also Head of the Research Cluster of Computing (RCC) to facilitate students in their research projects. Rajeev Kumar Arya, PhD, is an Assistant Professor with the Department of Electronics and Communication Engineering at National Institute of Technology, Patna, India. His current research interests are in wireless communication, soft computing techniques, cognitive radio, signal processing, communication systems, and circuit design. Joan Lu, PhD, is a Professor in the Department of Computer Science and the Research Group Leader of Information and System Engineering in the Centre of High Intelligent Computing at the University of Huddersfield, UK, having previously been team leader in the IT Department of the Charlesworth Group. |
Add Author |
Thakur, Hardeo Kumar, editor.
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Kaur, Manpreet (Lecturer in computer science), editor.
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Dhaliwal, Parneeta, editor.
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Arya, Rajeev Kumar, editor.
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Lu, Zhongyu, 1955- editor.
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Other Title |
Data science and AI, selected papers from CIAIS-2021 |
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CIAIS 2021 |
LC # |
Q3424 |
Dewey # |
006.3 |
ISBN |
9781003332312 |
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1003332315 |
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9781000772234 |
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1000772233 |
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9781774911440 |
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9781000772197 |
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1000772195 |
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9781774911457 |
Other # |
9781003332312 |
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10.1201/9781003332312 doi |
Isn/Std # |
9781003332312 Taylor & Francis |
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