プロフィール詳細

プロジェクトを作成

★★★★★

☆☆☆☆☆

★★★★★

☆☆☆☆☆

Dr. Ramesh K.に依頼

India

Artificial Intelligence| Computer Vision| Machine Learning| Deep Learning

プロフィール概要

A unique and unusual blend of a software engineer, product engineer, project manager and a researcher packaged in a single profile. Expertise in software development, product engineering, software project management, software business management and research. Mid career metamorphosis from a software professional to an Artificial Intelligence (AI) scientist by pursuing a full time Ph.D. The evolution to an AI scientist demonstrates the perseverance and the versatility to learn and adapt. The diversity in expertise and roles provides a distinctive edge in solving real world problems through AI products and solutions.

専門分野

• ★ Machine Learning
• ☆ Artificial Intelligence
• ☆ Deep Learning
• ☆ Computer Vision
• ☆ Python

サービス

• Writing
• Research
• Data & AI

Writing Technical Writing

Research Gray Literature Search, Systematic Literature Review

Data & AI Statistical Analysis, Algorithm Design-Non ML, Data Visualization

職務経験

Senior Research Fellow

International Institute of Information Technology

2月 2020 - 現在

Group Project Manager

Infosys Technologies Ltd

1月 1996 - 10月 2012

学歴

Ph.D (Electronics and Instrumentation)

Visvesvaraya Technological University

6月 2015 - 8月 2019

ME (Electronics and Communication)

University Visvesvaraya College of Engineering

1月 2013 - 12月 2015

BE (Electronics)

BMS College of Engineering

6月 1991 - 6月 1995

認定資格

• 認定資格の詳細は未入力です。

出版物

PREPRINT

(2019). Mango Tree Net -- A fully convolutional network for semantic segmentation and individual crown detection of mango trees.

JOURNAL ARTICLE

(2019). MangoNet: A deep semantic segmentation architecture for a method to detect and count mangoes in an open orchard . Engineering Applications of Artificial Intelligence.

Ramesh Kestur, Akanksha Angural, Bazila Bashir, S. N. Omkar, Gautham Anand, M. B. Meenavathi(2018). Tree Crown Detection, Delineation and Counting in {UAV} Remote Sensed Images: A Neural Network Based Spectral{\textendash}Spatial Method . Journal of the Indian Society of Remote Sensing. 46. (6). Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 991--1004. Springer Science and Business Media {LLC}

(2018). Tree Crown Detection, Delineation and Counting in UAV Remote Sensed Images: A Neural Network Based Spectral–Spatial Method . Journal of the Indian Society of Remote Sensing.

(2018). UFCN: a fully convolutional neural network for road extraction in RGB imagery acquired by remote sensing from an unmanned aerial vehicle . Journal of Applied Remote Sensing.

(2018). Detection of the power lines in UAV remote sensed images using spectral-spatial methods . Journal of Environmental Management.

(2017). Application of UAV imaging platform for vegetation analysis based on spectral-spatial methods . Computers and Electronics in Agriculture.

(2017). SIFT-FANN: An efficient framework for spatio-spectral fusion of satellite images . Journal of the Indian Society of Remote Sensing.

(2016). Detection of Rows in Agricultural Crop Images Acquired by Remote Sensing from a UAV . International Journal of Image, Graphics and Signal Processing.

(2016). Detection of tomatoes using spectral-spatial methods in remotely sensed RGB images captured by UAV . Biosystems Engineering.

CONFERENCE PAPER

(2015). Automatic detection of powerlines in UAV remote sensed images . 2015 International Conference on Condition Assessment Techniques in Electrical Systems (CATCON).