PreDisM: Pre-Disaster Modelling With CNN Ensembles for At-Risk Communities

no code implementations • 26 Dec 2021 • Vishal Anand, Yuki Miura

The machine learning community has recently had increased interest in the climate and disaster damage domain due to a marked increased occurrences of natural hazards (e. g., hurricanes, forest fires, floods, earthquakes).

Customized video filtering on YouTube

no code implementations • 11 Nov 2019 • Vishal Anand, Ravi Shukla, Ashwani Gupta, Abhishek Kumar

But with a huge surge in content being posted online it becomes seemingly difficult to filter out related videos on which they can run their ads without compromising brand name.

An automated approach for task evaluation using EEG signals

no code implementations • 7 Nov 2019 • Vishal Anand, S. R. Sreeja, Debasis Samanta

Understanding the complexity of a particular task can only be done on user level and we propose to do this by understanding the mental workload (MWL) generated on an operator while performing a task which requires processing a lot of information to get the task done.

Dimensionality Reduction Electroencephalogram (EEG) +1

On Optimizing Human-Machine Task Assignments

no code implementations • 24 Sep 2015 • Andreas Veit, Michael Wilber, Rajan Vaish, Serge Belongie, James Davis, Vishal Anand, Anshu Aviral, Prithvijit Chakrabarty, Yash Chandak, Sidharth Chaturvedi, Chinmaya Devaraj, Ankit Dhall, Utkarsh Dwivedi, Sanket Gupte, Sharath N. Sridhar, Karthik Paga, Anuj Pahuja, Aditya Raisinghani, Ayush Sharma, Shweta Sharma, Darpana Sinha, Nisarg Thakkar, K. Bala Vignesh, Utkarsh Verma, Kanniganti Abhishek, Amod Agrawal, Arya Aishwarya, Aurgho Bhattacharjee, Sarveshwaran Dhanasekar, Venkata Karthik Gullapalli, Shuchita Gupta, Chandana G, Kinjal Jain, Simran Kapur, Meghana Kasula, Shashi Kumar, Parth Kundaliya, Utkarsh Mathur, Alankrit Mishra, Aayush Mudgal, Aditya Nadimpalli, Munakala Sree Nihit, Akanksha Periwal, Ayush Sagar, Ayush Shah, Vikas Sharma, Yashovardhan Sharma, Faizal Siddiqui, Virender Singh, Abhinav S., Anurag. D. Yadav

When crowdsourcing systems are used in combination with machine inference systems in the real world, they benefit the most when the machine system is deeply integrated with the crowd workers.