Sukanya Randhawa

Orcid: 0009-0005-5068-3246

According to our database1, Sukanya Randhawa authored at least 10 papers between 2016 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
Paved or unpaved? A Deep Learning derived Road Surface Global Dataset from Mapillary Street-View Imagery.
CoRR, 2024

2023
Multiscale Multifeature Vision Learning for Scalable and Efficient Wastewater Treatment Plant Detection using Hi-Res Satellite Imagery and OSM.
Proceedings of the 1st ACM SIGSPATIAL International Workshop on Advances in Urban-AI, 2023

2020
Building an Open, Multi-Sensor, Dataset of Water Pollution of Ganga Basin and Application to Assess Impact of Large Religious Gatherings.
Proceedings of the 2020 IEEE International Conference on Pervasive Computing and Communications Workshops, 2020

Scope, Extent, and Challenges of an Automated Global Crop Classification Model.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2020

2019
Towards a ML based global crop identification model using limited SAR data - that is scalable across data-sparse geographies.
Proceedings of the 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019

Machine Learning Methodologies for Paddy Yield Estimation in India: a Case Study.
Proceedings of the 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019

2017
The GangaWatch Mobile App to Enable Usage of Water Data in Every Day Decisions Integrating Historical and Real-time Sensing Data.
CoRR, 2017

Photonic Energy Harvesting: Boosting Energy Yield of Commodity Solar Photovoltaic Systems via Software Defined IoT Controls.
Proceedings of the Eighth International Conference on Future Energy Systems, 2017

2016
An Open, Multi-Sensor, Dataset of Water Pollution of Ganga Basin and its Application to Understand Impact of Large Religious Gathering.
CoRR, 2016

A Multi-sensor Process for In-Situ Monitoring of Water Pollution in Rivers or Lakes for High-Resolution Quantitative and Qualitative Water Quality Data.
Proceedings of the 2016 IEEE Intl Conference on Computational Science and Engineering, 2016


  Loading...