Machine Intelligence
Auerbach (Verlag)
978-1-032-20199-3 (ISBN)
Machines are being systematically empowered to be interactive and intelligent in their operations, offerings. and outputs. There are pioneering Artificial Intelligence (AI) technologies and tools. Machine and Deep Learning (ML/DL) algorithms, along with their enabling frameworks, libraries, and specialized accelerators, find particularly useful applications in computer and machine vision, human machine interfaces (HMIs), and intelligent machines. Machines that can see and perceive can bring forth deeper and decisive acceleration, automation, and augmentation capabilities to businesses as well as people in their everyday assignments. Machine vision is becoming a reality because of advancements in the computer vision and device instrumentation spaces. Machines are increasingly software-defined. That is, vision-enabling software and hardware modules are being embedded in new-generation machines to be self-, surroundings, and situation-aware.
Machine Intelligence: Computer Vision and Natural Language Processing emphasizes computer vision and natural language processing as drivers of advances in machine intelligence. The book examines these technologies from the algorithmic level to the applications level. It also examines the integrative technologies enabling intelligent applications in business and industry.
Features:
Motion images object detection over voice using deep learning algorithms
Ubiquitous computing and augmented reality in HCI
Learning and reasoning in Artificial Intelligence
Economic sustainability, mindfulness, and diversity in the age of artificial intelligence and machine learning
Streaming analytics for healthcare and retail domains
Covering established and emerging technologies in machine vision, the book focuses on recent and novel applications and discusses state-of-the-art technologies and tools.
Pethuru Raj has been working as the chief architect in the Site Reliability Engineering (SRE) division of Reliance Jio Platforms Ltd., Bangalore. He previously worked as a cloud infrastructure architect in the IBM Global Cloud Center of Excellence (CoE), a TOGAF-certified enterprise architecture (EA) consultant in Wipro Consulting Services (WCS) Division and as a lead architect in the corporate research (CR) division of Robert Bosch. In total, he has gained more than 19 years of IT industry experience and 8 years of research experience. P Beaulah Soundarabai is an associate professor in the Department of Computer Science, Christ University, Bangalore, having 20 years of teaching experience. She is been associated with Christ University for the past 14 year. Prior to this, she has teaching experience in SFR College for Women, Sivakasi, and AGCS, Kolkata lecturer, and in for 3 years respectively. She has 10 years of research experience in the areas of Distributed Computing, Computer Networks, IoT, Edge and Cloud computing, and Data Analytics. Peter Augustine has been working as an Associate Professor in the Department of Computer Science, CHRIST (Deemed to be University), Bangalore. Peter Augustine has a PhD in Medical Image Processing in Cloud Environment, with over 8 years in cloud computing and 5 years in Big Data Analytics. He has authored various research papers published in peer-reviewed journals. He has been involved in a Major Research Project using Cloud Computing which costs more than 18 lakhs. He has also collaborated with St. John’s Medical Research Institute for the research project to diagnose Lung Diseases using cutting-edge AI and Machine Learning.
1. A New Frontier in Machine Intelligence: Creativity 2. Overview of Human-Computer Interaction 3. Edge/Fog Computing: An Overview and Insight into Research Directions 4. Reduce Overfitting and Improve Deep Learning Models' Performance in Medical Image Classification 5. Motion Images Object Detection Over Voice Using Deep Learning Algorithms 6. Diabetic Retinopathy Detection Using Various Machine Learning Algorithms 7. IIoT Applications and Services 8. Design of Machine Learning Model for Healthcare Index during COVID-19 9. Ubiquitous Computing and Augmented Reality in HCI 10. A Machine Learning-Based Driving Assistance System for Lane and Drowsiness Monitoring 11. Prediction of Gastric Cancer from Gene Expression Dataset using Supervised Machine Learning Models 12. Sewer Pipe Defect Detection of CCTV Images Using Deep Learning Techniques 13. Learning and Reasoning on Artificial Intelligence 14. A Novel Auto Encoder-Network-Based Ensemble Technique for Sentiment Analysis of Tweets on COVID-19 Data 15. Economic Sustainability, Mindfulness, and Diversity in the Age of Artificial Intelligence and Machine Learning 16. Adopting Streaming Analytics for Healthcare and Retail Domains
| Erscheinungsdatum | 05.10.2023 |
|---|---|
| Zusatzinfo | 110 Line drawings, black and white; 110 Illustrations, black and white |
| Verlagsort | London |
| Sprache | englisch |
| Maße | 156 x 234 mm |
| Gewicht | 660 g |
| Themenwelt | Geisteswissenschaften ► Sprach- / Literaturwissenschaft ► Sprachwissenschaft |
| Informatik ► Grafik / Design ► Digitale Bildverarbeitung | |
| Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
| Technik ► Elektrotechnik / Energietechnik | |
| Technik ► Umwelttechnik / Biotechnologie | |
| ISBN-10 | 1-032-20199-1 / 1032201991 |
| ISBN-13 | 978-1-032-20199-3 / 9781032201993 |
| Zustand | Neuware |
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