Jeevan Bala

Jeevan Bala
Lovely Professional University | LPU · Discipline of Computer Science & Engineering

Ph.D. (Computer Science & Engineering)

About

9
Publications
1,431
Reads
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27
Citations
Citations since 2017
8 Research Items
27 Citations
201720182019202020212022202302468
201720182019202020212022202302468
201720182019202020212022202302468
201720182019202020212022202302468
Additional affiliations
June 2017 - present
Lovely Professional University
Position
  • Professor (Assistant)
Education
July 2016 - July 2020
Lovely Professional University
Field of study
  • Computer Science & Engineering

Publications

Publications (9)
Article
Full-text available
Abstract The recommended tool for assessing knee injury is magnetic resonance imaging (MRI). However, knee MRI interpretation takes time and is vulnerable to clinical errors and inconsistency. A deep learning automated technique for reading knee MRI might help physicians identify high-risk patients and make diagnosis easier. In this study, we have...
Article
Full-text available
An efficient estimation of transmission map for desmogging model is an ill-posed problem. The quality of restored image depends upon the accurate estimation of transmission map. However, transmission map obtained using various dehazing models is not accurate in case of images with large haze gradient, and fail while image desmogging. As a result, t...
Preprint
Self-driving vehicle is a hot issue in present time. A self-driving car is expected to drive with no human interaction even in dire situations. This paper aims to discuss the history and progress of self-driving vehicles.
Article
Full-text available
Objectives: To design a new framework to efficiently parallelize the steps of VLASPD algorithm using a hybridized apriori and fp-growth on GPU; to implement the existing and proposed framework in CUDA;to improve the performance factors like computational time, memory and CPU utilization.Methods/Statistical Analysis: This paper proposes the accelera...

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Projects

Projects (2)
Project
Involves the usage of machine learning techniques for restoration of illumination of color images.