| ISBN13: | 9781774911440 |
| ISBN10: | 1774911442 |
| Kötéstípus: | Keménykötés |
| Terjedelem: | 488 oldal |
| Méret: | 234x156 mm |
| Súly: | 1061 g |
| Nyelv: | angol |
| Illusztrációk: | 149 Illustrations, black & white; 2 Illustrations, color; 21 Halftones, black & white; 128 Line drawings, black & white; 2 Line drawings, color; 56 Tables, black & white |
| 636 |
A természettudományok általános kérdései, tudománytörténet, tudományfilozófia
A biológia általános kérdései
A számítástudomány elmélete, a számítástechnika általában
A számítástudomány matematikai elmélete
Adatkezelés a számítógépes rendszerekben
Számítógép architektúrák, logikai tervezés
Szuperszámítógépek
Operációs rendszerek és grafikus felhasználói felületek
Szoftverfejlesztés
Adatbázis kezelő szoftverek
Természettudományok
A természettudományok általános kérdései, tudománytörténet, tudományfilozófia (karitatív célú kampány)
A biológia általános kérdései (karitatív célú kampány)
A számítástudomány elmélete, a számítástechnika általában (karitatív célú kampány)
A számítástudomány matematikai elmélete (karitatív célú kampány)
Adatkezelés a számítógépes rendszerekben (karitatív célú kampány)
Számítógép architektúrák, logikai tervezés (karitatív célú kampány)
Szuperszámítógépek (karitatív célú kampány)
Operációs rendszerek és grafikus felhasználói felületek (karitatív célú kampány)
Szoftverfejlesztés (karitatív célú kampány)
Adatbázis kezelő szoftverek (karitatív célú kampány)
Természettudományok (karitatív célú kampány)
Computational Intelligence in Analytics and Information Systems
GBP 147.00
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A Prosperónál jelenleg nincsen raktáron.
Presents state-of-the-art technological advancements in AI and machine learning, highlighting the use of predictive analytics of data from various application domains to find timely solutions. It focuses on the research developments, limitations, and management of real-time problems using computational intelligence.
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 to real-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.
PART I: COMPUTATIONAL INTELLIGENCE IN IMAGE PROCESSING 1. A Study of Issues and Challenges with Digital Image Processing 2. A Methodical View on Prerequisites of Picture Combination, Strategies, Key Indicators with Usage in Real Life and Scientific Domains Facilitating Smart Ubiquitous Environment 3. A Study of Emerging Issues and Possibilities for Breast Cancer Diagnosis Using Image Modalities 4. Pap Smear Image Segmentation Using Chan
-Vese
-Based Adaptive Primal Dual Splitting Algorithm 5. Satellite Image Compression by Random Forest Optimization Techniques and Performance Comparison Using a Multispectral Image Compression Method 6. Learning Spatio
-Temporal Features for Movie Scene Retrieval Using a 3D Convolutional Autoencoder 7. Person Re
-Identification Using Deep Learning and Neural Networks PART II: COMPUTATIONAL INTELLIGENCE IN HEALTHCARE 8. A Systematic Literature Review in Health Informatics Using Data Mining Techniques 9. Utilization of Artificial Intelligence Based Methods for Preoperative Prediction in Shoulder Arthroplasty: Survey 10. Role of Computer
-Based Intelligence for Prognostication a Social Well
-Being and Identifying Frailty and Drawbacks 11. Health Informatics Support for Occurrence Administration Using Artificial Intelligence and Deep Learning: COVID
-19 Pandemic Response 12. Machine Learning Approach for Prediction Analysis of COVID
-19 13. Assessment of Generalized Anxiety Disorder and Mood Disorder in Undergraduate Students during the Coronavirus Disease (COVID
-19) Pandemic 14. Evaluation of Deep Learning Models for Medical Tools Classification 15. Cervical Cancer Diagnosis and Prediction: An Application of Machine Learning Techniques 16. The Working Analysis on Machine Learning Algorithms to Predict Diabetes and Breast Cancer 17. An Ensemble of AdaBoost with Multilayer Perceptron for Heart Disease Prediction PART III: TECHNIQUES FOR NATURAL LANGUAGE PROCESSING 18. An Empirical Study of Text Summarization Techniques Using Extractive Approaches 19. Design and Comparative Analysis of Inverted Indexing of Text Documents 20. Acoustic Musical Instrument Recognition 21. Classification of Accented Voice Using RNN and GAN 22. Speech Emotion Recognition Using LSTM 23. Interpretation of American Sign Language Using Convolutional Neural Networks 24. Emotional Intelligence: An Approach to Analyze Stress Using Speech and Face Recognition 25. Proposed Integrated Framework for Emotion Recognition: A Futuristic Approach PART IV: COMPUTATIONAL INTELLIGENCE IN SMART CITIES 26. A Review on Machine Learning Techniques for Human Actions Recognition 27. Fog
-Based Intelligent Traffic Phase Timing Regulation System 28. Deep Learning Classification Model for Detection of Traffic Signs 29. Understanding Road Scene Images Using CNN Features 30. Profitable Crop Prediction for the State of Odisha Using Machine Learning Algorithms 31. CapGAN: IoT
-Based Cropping Patterns Prediction and Recommendation for Crop Cultivation
