Junaid Younas

Orcid: 0000-0002-4697-0737

According to our database1, Junaid Younas authored at least 12 papers between 2016 and 2023.

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

Timeline

Legend:

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PhD thesis 
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Bibliography

2023
IAMonSense: multi-level handwriting classification using spatiotemporal information.
Int. J. Document Anal. Recognit., September, 2023

From Cognition 2 Applications: Bridging the Gap between Formal Education & AI.
PhD thesis, 2023

Air-Writing Segmentation using a single IMU-based system.
Proceedings of the 19th International Conference on Intelligent Environments, 2023

2022
FAirWrite - Movement Reconstruction and Recognition Using a Low-cost IMU.
Proceedings of the 2022 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, 2022

Cognitive Ability Classification using On-body Sensors.
Proceedings of the Adjunct Proceedings of the 2022 ACM International Joint Conference on Pervasive and Ubiquitous Computing and the 2022 ACM International Symposium on Wearable Computers, 2022

2021
Sense the pen: Classification of online handwritten sequences (text, mathematical expression, plot/graph).
Expert Syst. Appl., 2021

2020
Finger Air Writing - Movement Reconstruction with Low-cost IMU Sensor.
Proceedings of the MobiQuitous '20: Computing, 2020

2019
Wrist-Worn Capacitive Sensor for Activity and Physical Collaboration Recognition.
Proceedings of the IEEE International Conference on Pervasive Computing and Communications Workshops, 2019

FFD: Figure and Formula Detection from Document Images.
Proceedings of the 2019 Digital Image Computing: Techniques and Applications, 2019

2018
What Am I Writing: Classification of On-Line Handwritten Sequences.
Proceedings of the Intelligent Environments 2018, 2018

2017
D-StaR: A Generic Method for Stamp Segmentation from Document Images.
Proceedings of the 14th IAPR International Conference on Document Analysis and Recognition, 2017

2016
gPhysics - Using Smart Glasses for Head-Centered, Context-Aware Learning in Physics Experiments.
IEEE Trans. Learn. Technol., 2016


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