Delsey M J

Assistant Professor 
Email: [email protected]

Education

  • B.Tech., Anna University, 2009
  • M.E Computer Science and Engineering., Anna University, 2013
  • Pursuing Ph.D, Indian Institute of Information and Technology Kottayam

Area of Specialization

  • Machine Learning and Deep Learning
  • Awarded as BEST FACULTY for the year 2012-2013 at Karpagam College of Engineering.
  • IBM RAD, DB2 9.7, LOTUS, RTC Certified.

Data Mining

Data is considered as the most valuable one in the present world and everyone needs the refined cum beneficial information from the available data. This led to the deluge of Data Mining. It is used to excerpt knowledge from the massive amount of data. As the rate of growth of data is increasing day by day, there is a critical need to analyze huge and complex data sets to obtain the hidden patterns, trends and information. Data Mining is widely used in many applications such as identifying potential customers in marketing, product analysis, demand and supply analysis, e-commerce, medical field and so many. DM has vital importance in today’s competitive business situation. Various forms of data mining is available like text mining, web mining, image mining, social networks data mining, audio and video mining.

Machine Learning

Machine learning is a subset of Artificial Intelligence (AI). It is the field of computational science that is centered on studying and understanding patterns in the data to enable learning, reasoning and making decision without human interaction. A huge sample of data is fed to the algorithm and makes the system learn and come up with the data driven recommendations and judgment. Machine learning has applications in fields like Manufacturing. Healthcare, Travel and hospitality, Financial services, Energy demand and Optimization of supply, Fraud detection etc., The emergence of self-driving Google car, cyber fraud detection, online recommendation engines from Facebook, Netflix and Amazon are some of the good examples of machine learning applications.

Computer Vision

Computer Vision is an area of Artificial Intelligence that trains the computers to understand and identify the objects in the world. Identification and Classification of objects is made possible through deep learning models using digital images from cameras and videos. This enables machines to react to what they identify from the scene. Recently the computer vision is gaining more importance as it could automate the inspection and robot guidance in industrial applications. It could enable drones to perform certain action where human intervention is impossible. One of the most outstanding application fields is the medical computer vision, or medical image processing, represented by the mining of information from image data to diagnose a patient. Identification of tumors and cancers accurately are some of the examples.

  • CA1813109 Data Structures using C++
  • CA1813603 Software Lab III
  • CA1815116 Java Programming using Linux
  • CA1815605 Software Lab V
  • CA1814113 Web Programming using PHP
  • CA1814604 Software Lab IV
  • CA1815801 Software Development Lab I ( Mini Project)
  • Published paper titled “UWI-EnhaNet: Underwater Image Enhancement Network using Convolutional Neural Network” in International Conference on Recent Trends in Computing & Information Technology – RTCIT’22, ISBN: 979-8-88525-143-3, at Sarah Tucker College.
  • Published paper titled “GAN based Image Enhancement of Underwater Images: A Review” in International Conference on Recent Trends in Materials, Renewable Energy, Information & Technology (ICRTMREICT-2022), ISBN: 978-81-955848-0-2, at PSN Institute of Technology and Science.
  • Awarded as BEST FACULTY for the year 2012-2013 at Karpagam College of Engineering.
  • IBM RAD, DB2 9.7, LOTUS, RTC Certified.

Computer Science (SF)
Department