S
Srimal Jayawardena
Researcher at Australian National University
Publications - 16
Citations - 1463
Srimal Jayawardena is an academic researcher from Australian National University. The author has contributed to research in topics: 3D pose estimation & The Internet. The author has an hindex of 6, co-authored 16 publications receiving 1225 citations. Previous affiliations of Srimal Jayawardena include Institute of Robotics and Intelligent Systems & Commonwealth Scientific and Industrial Research Organisation.
Papers
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Journal ArticleDOI
A Survey on Internet of Things From Industrial Market Perspective
TL;DR: This survey is intended to serve as a guideline and a conceptual framework for context-aware product development and research in the IoT paradigm and provides a systematic exploration of existing IoT products in the marketplace and highlights a number of potentially significant research directions and trends.
Journal ArticleDOI
The Emerging Internet of Things Marketplace From an Industrial Perspective: A Survey
TL;DR: This paper surveys over one hundred IoT smart solutions in the marketplace and examines them closely in order to identify the technologies used, functionalities, and applications, and suggests a number of potentially significant research directions.
Journal ArticleDOI
The Emerging Internet of Things Marketplace From an Industrial Perspective: A Survey
TL;DR: In this article, the authors present a survey of IoT smart solutions in the marketplace and examine them closely in order to identify the technologies used, functionalities, and applications, and identify the trends, opportunities and open challenges in the industry-based IoT solutions.
Proceedings ArticleDOI
Plant Disease Detection Using Hyperspectral Imaging
TL;DR: This paper proposes the use of hyperspectral imaging (VNIR and SWIR) and machine learning techniques for the detection of the Tomato Spotted Wilt Virus in capsicum plants and shows excellent discrimination based on the full spectrum and comparable results based on data-driven probabilistic topic models and the domain vegetation indices.
DissertationDOI
Image based automatic vehicle damage detection
TL;DR: In this paper, a 3D pose estimation method using image gradient information of the photograph and the 3D model projection is proposed to detect image edges caused by inter-object reflection, and a robust method to obtain reliable point correspondences across the photographs which are dominated by large reflective and mostly homogeneous regions.