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Transformations in Industry Using Artificial Intelligence, Machine Learning, Deep Learning and Transfer Learning
Submission DeadlineJul. 15, 2020

Submission Guidelines: http://www.sciencepublishinggroup.com/journal/guideforauthors?journalid=604

Lead Guest Editor
Dr. Sandhya P
School of Computing Science and Engineering, Vellore Institute of Technology, Chennai, Tamil Nadu, India
Guest Editors
  • Dr. Malathi G
    School of Computing Science and Engineering, Vellore Institute of Technology, Chennai, Tamil Nadu, India
  • Dr. Neduncheliyan S
    School of Computer Science and Engineering, Bharath Institute of Higher Education and Research, Chennai, Tamil Nadu, India
  • Dr. Balasubramanian M
    Department of Computer Science and Engineering, Annamalai University, Chidhambaram, India
  • Dr. Dinesh M
    Department of Information Technology, College of Computing and Informatics, Saudi Electronic University, Abha, Saudi Arabia
  • Dr. Asha P
    Department of Computer Science and Engineering, Sathyabama University, Chennai, Tamil Nadu, India
  • Dr. Andrews J
    Department of Computer Science and Engineering, Presidency University, Bengaluru, India
  • Dr. Kavitha Esther
    Department of Computer Science and Engineering, KCG College of Technology affiliated to Anna University, Chennai, India
Introduction
Artificial Intelligence (AI) has been in existence decades ago. Currently with the increase in computational power and storage capacities, AI is reborn. The Industry 4.0 disrupts every vertical through the emergence of AI. It mimics the cognitive skills of humans such as learning and problem solving. Machine Learning is a subset of AI that learns from historic data to predict outcomes and uncovers patterns. ML has practical implications across all the industrial sectors including healthcare, insurance, energy consumption, marketing, manufacturing, financial technology, etc. Data deluge from digital devices supports AI solutions to manage, analyze and gain insight. Data science extracts meaningful acumens from data by amalgamating domain expertise, programming skills, mathematical and statistical knowledge. A data scientist applies ML algorithms on multimedia and multi-dimensional data to construct AI systems. Deep Learning is a subset of ML that has the ability to process large number of features. Deep Learning is more powerful to explore unstructured data. It is estimated that in 2019, the AI empowerment entity economy industry scale is close to $570 billion. AI has been incorporated in topnotch applications from Siri the pseudo-intelligent personal digital assistant to Alexa; Tesla the car with self-driving features; Boxever that delivers micro-moments for travellers; Netflix using predictive technology to suggest films to customers; Nest the learning thermostat; Pandora that recommends songs, etc. This issue aims to bring out the transformations in various sectors through disruptions using AI.
Artificial Intelligence (AI) is the brain behind Industry 4.0 which is driven by Cyber Physical Systems and Internet of Things. The connected machines collect tremendous volume of data that can be analyzed to identify patterns and insights. Currently there are several disruptions in different fields using Artificial Intelligence. It is used in analyzing agricultural farm data such as weather conditions, temperature, water usage, soil conditions etc. AI is used in health-care for clinical decision support, computer-aided diagnosis, computer-aided simple triage, medical image computing etc. In banking sector AI is used to enhance customer experience; predict fraud, detect anti-money laundering pattern and make customer recommendations; provide cognitive process automation; robotic automation of processes, etc. In education sector AI provides personalized learning, smart content, voice assistants, etc. This special issue invites unpublished prospective works on Artificial Intelligence, Machine Learning and Deep Learning that disrupts traditional business models.
Scope:
  1. Disruptive Solutions using Artificial Intelligence
  2. AI in Agriculture
  3. Deep Learning in Imaging Science
  4. Big Data and Data Analytics
  5. AI in Health care
  6. AI in retail and marketing
  7. AI in Education
  8. Predictive Analytics
  9. AI for Natural Language Processing
  10. AI in scheduling and optimization
  11. AI in modeling and simulation
  12. Collective Intelligence
  13. Speech Understanding
  14. Web Intelligence
  15. Artificial Immune Systems
  16. Knowledge Engineering
  17. Machine Learning
  18. Human-Computer Interaction
Aims and Scope:
  1. Artificial Intelligence
  2. Machine Learning
  3. Deep learning
  4. Big Data and Data Analytics
  5. Data Science
  6. Industry 4.0
Guidelines for Submission
Manuscripts should be formatted according to the guidelines for authors
(see: http://www.sciencepublishinggroup.com/journal/guideforauthors?journalid=604).

Please download the template to format your manuscript.

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