Description
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 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.
Table of Contents
1. A New Frontier in Machine Intelligence: Creativity
Ardhendu G. Pathak
2. Overview of Human Computer Interaction
Nancy Jasmine Goldena
3. Edge/Fog Computing: An Overview and Insight into Research Directives
Priya Thomas and Deepa V. Jose
4. Reduce Overfitting and Improve Deep Learning Models' Performance in Medical Image Classification
Nidhin Raju and D. Peter Augustine
5. Motion Images Object Detection Over Voice Using Deep Learning Algorithms
P.L. Chithra and J. Yasmin Banu
6. Diabetic Retinopathy Detection Using Various Machine Learning Algorithms
P. K. Nizar Banu and Yadukrishna Sreekumar
7. IIoT Applications and Services
P.Shanmugavadivu, T. Kalaiselvi, M. Mary Shanthi Rani, and P. Haritha
8. Design of Machine Learning Model for Healthcare Index during COVID-19
Nishu Gupta, Soumya Chuabey, Ity Patni, Vaibhav Bhatnagar, and Ramesh Chandra Poonia
9. Ubiquitous Computing and Augmented Reality in HCI
Nancy Jasmine Goldena and Thangapriya
10. A Machine Learning-Based Driving Assistance System for Lane and Drowsiness Monitoring
Sanjay A. and Gobi Ramasamy
11. Prediction of Gastric Cancer from Gene Expression Dataset using Supervised Machine Learning Models
Manikandan P, Ruban Christopher D, and Luthuful Haq
12. Sewer Pipe Defect Detection of CCTV Images Using Deep Learning Techniques
P.L. Chithra and P. Bhavani
13. Learning and Reasoning on Artificial Intelligence
Merjula Roby
14. A Novel Auto Encoder-Network-Based Ensemble Technique for Sentiment Analysis of Tweets on COVID-19 Data
R. Jyothsna, V. Rohini, and Joy Paulose
15. Economic Sustainability, Mindfulness, and Diversity in the Age of Artificial Intelligence and Machine Learning
Ranjit Singha and Surjit Singha
16. Adopting Streaming Analytics for Healthcare and Retail Domains
G. Nagarajan, Kiran Singh, T. Poongodi, and Suman Avdhesh Yadav
