Amr Suleiman

Orcid: 0000-0003-3669-4318

According to our database1, Amr Suleiman authored at least 16 papers between 2014 and 2021.

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

2021
HWTool: Fully Automatic Mapping of an Extensible C++ Image Processing Language to Hardware.
CoRR, 2021

2019
Navion: A 2-mW Fully Integrated Real-Time Visual-Inertial Odometry Accelerator for Autonomous Navigation of Nano Drones.
IEEE J. Solid State Circuits, 2019

2018
Energy efficient accelerators for autonomous navigation in miniaturized robots.
PhD thesis, 2018

Navion: A 2mW Fully Integrated Real-Time Visual-Inertial Odometry Accelerator for Autonomous Navigation of Nano Drones.
CoRR, 2018

Navion: A Fully Integrated Energy-Efficient Visual-Inertial Odometry Accelerator for Autonomous Navigation of Nano Drones.
Proceedings of the 2018 IEEE Symposium on VLSI Circuits, 2018

Hardware for machine learning: Challenges and opportunities.
Proceedings of the 2018 IEEE Custom Integrated Circuits Conference, 2018

2017
A 58.6 mW 30 Frames/s Real-Time Programmable Multiobject Detection Accelerator With Deformable Parts Models on Full HD 1920×1080 Videos.
IEEE J. Solid State Circuits, 2017

Towards Closing the Energy Gap Between HOG and CNN Features for Embedded Vision.
CoRR, 2017

Visual-Inertial Odometry on Chip: An Algorithm-and-Hardware Co-design Approach.
Proceedings of the Robotics: Science and Systems XIII, 2017

Towards closing the energy gap between HOG and CNN features for embedded vision (Invited paper).
Proceedings of the IEEE International Symposium on Circuits and Systems, 2017

Hardware for machine learning: Challenges and opportunities.
Proceedings of the 2017 IEEE Custom Integrated Circuits Conference, 2017

2016
An Energy-Efficient Hardware Implementation of HOG-Based Object Detection at 1080HD 60 fps with Multi-Scale Support.
J. Signal Process. Syst., 2016

A 58.6mW Real-Time Programmable Object Detector with Multi-Scale Multi-Object Support Using Deformable Parts Model on 1920x1080 Video at 30fps.
CoRR, 2016

A 58.6mW real-time programmable object detector with multi-scale multi-object support using deformable parts model on 1920×1080 video at 30fps.
Proceedings of the 2016 IEEE Symposium on VLSI Circuits, 2016

2014
Model Predictive Control Equalization for High-Speed I/O Links.
IEEE Trans. Circuits Syst. I Regul. Pap., 2014

Energy-efficient HOG-based object detection at 1080HD 60 fps with multi-scale support.
Proceedings of the 2014 IEEE Workshop on Signal Processing Systems, 2014


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