LK
Lakshmi Kalyani
VNR Vignana Jyothi College of Engineering and Technology, X Design Ventures pvt Ltd, Vijaya Engineering college, Sri Raja Rajeswari Engineering College
Research areas: Agricultural and Biological Sciences · Plant Science · Smart Agriculture and AI · Advanced Neural Network Applications · Semantic Web and Ontologies
0000-0002-5503-2849
Employment
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VNR Vignana Jyothi College of Engineering and Technology Assistant Professor2015 - Present
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X Design Ventures pvt Ltd R & D Engineer2006 - 2011
Education
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Vijaya Engineering college M.Tech2011 - 2013
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Sri Raja Rajeswari Engineering College B.Tech2002 - 2006
Projects & Funding
Projects & funding information is unavailable.
Publications (19)
- Machine Learning-Based Crop Recommendation System for Sustainable Agriculture Save
- Interactive Book Covers using Augmented Reality: A New Paradigm in Reader Engagement Save
- Obstacle Detection and Notification Using Stereo Vision Technology Save
- Real-Time Vegetable Classification for Smart Retail and Agriculture using Edge Impulse Save
- Design and Optimization of Universal Shift Registers Using Novel Reversible Logic Gates Save
- Exploration of Pesticide Residue Detection Methods Save
- IoT-Based Earthworm Cultivation System for Enhanced Soil Fertility and Sustainable Agriculture Save
- FLIP60-AR based Application for Elders Save
- Soil Color as a Measurement for Estimation of Fertility using Deep Learning Techniques Save
- Soil Color as a Measurement for Estimation of Fertility using Deep Learning Techniques Save
- Analysis of mammography for identifying cancer cells using convolution neural networks Save
- Chatterbot implementation using transfer learning and LSTM encoder-decoder architecture Save
- Machine learning model - Based prediction of flight delay Save
- Nature inspired binary grey wolf optimizer for feature selection in the detection of neurodegenerative (Parkinson) disease Save
- Querying the dataset from the developed ontology for Swineflu disease Save
- Soil synthesis and identification of nitrogen percentage in soil using machine learning algorithms and augmented reality – a typical review Save
- Querying the dataset from the developed ontology for swineflu disease Save
- Representation of knowledge through ontology for swine flu disease in semiarid tropical regions Save
- Efficient Water Quality Monitoring System Save