Krishneel Chaudhary

Orcid: 0000-0001-6173-9800

According to our database1, Krishneel Chaudhary authored at least 10 papers between 2014 and 2018.

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

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2018
Learning to Segment Generic Handheld Objects Using Class-Agnostic Deep Comparison and Segmentation Network.
IEEE Robotics Autom. Lett., 2018

Flight Motion of Passing Through Small Opening by DRAGON: Transformable Multilinked Aerial Robot.
Proceedings of the 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2018

Predicting Part Affordances of Objects Using Two-Stream Fully Convolutional Network with Multimodal Inputs.
Proceedings of the 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2018

2017
Robust real-time visual tracking using dual-frame deep comparison network integrated with correlation filters.
Proceedings of the 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2017

STAIR3D: Simultaneous tracking and incremental registration for modeling 3D handheld objects.
Proceedings of the IEEE International Conference on Advanced Intelligent Mechatronics, 2017

2016
Development of task-oriented high power field robot platform with humanoid upper body and mobile wheeled base.
Proceedings of the 2016 IEEE/SICE International Symposium on System Integration, 2016

Retrieving unknown objects using robot in-the-loop based interactive segmentation.
Proceedings of the 2016 IEEE/SICE International Symposium on System Integration, 2016

2015
Reasoning-based vision recognition for agricultural humanoid robot toward tomato harvesting.
Proceedings of the 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2015

Tracking handheld object using three layer RGB-D image space.
Proceedings of the IEEE International Conference on Robotics and Automation, 2015

2014
Autonomous acquisition of generic handheld objects in unstructured environments via sequential back-tracking for object recognition.
Proceedings of the 2014 IEEE International Conference on Robotics and Automation, 2014


  Loading...