Mohamed El-Sharkawy

This page is a disambiguation page, it actually contains multiple papers from persons of the same or a similar name.

Bibliography

2024
Re-configurable parallel Feed-Forward Neural Network implementation using FPGA.
Integr., 2024

2023
Deployment of Proposed EfficientNeXt on NXP i.MX 8M Mini.
Proceedings of the 6th International Conference on Information and Computer Technologies, 2023

2021
Image Classification with A-MnasNet and R-MnasNet on NXP Bluebox 2.0.
Proceedings of the Intelligent Computing, 2021

2020
A-MnasNet: Augmented MnasNet for Computer Vision.
Proceedings of the 63rd IEEE International Midwest Symposium on Circuits and Systems, 2020

3-Level Residual Capsule Network for Complex Datasets.
Proceedings of the 11th IEEE Latin American Symposium on Circuits & Systems, 2020

A Multi Sensor Real-time Tracking with LiDAR and Camera.
Proceedings of the 10th Annual Computing and Communication Workshop and Conference, 2020

Squeeze-and-Excitation SqueezeNext: An Efficient DNN for Hardware Deployment.
Proceedings of the 10th Annual Computing and Communication Workshop and Conference, 2020

RMNv2: Reduced Mobilenet V2 for CIFAR10.
Proceedings of the 10th Annual Computing and Communication Workshop and Conference, 2020

2019
Residual Capsule Network.
Proceedings of the 10th IEEE Annual Ubiquitous Computing, 2019

Forward Collision Prediction with Online Visual Tracking.
Proceedings of the IEEE International Conference of Vehicular Electronics and Safety, 2019

Autonomous Embedded System Enabled 3-D Object Detector: (with Point Cloud and Camera).
Proceedings of the IEEE International Conference of Vehicular Electronics and Safety, 2019

Shallow SqueezeNext: An Efficient & Shallow DNN.
Proceedings of the IEEE International Conference of Vehicular Electronics and Safety, 2019

Architecturally Compressed CNN: An Embedded Realtime Classifier (NXP Bluebox2.0 with RTMaps).
Proceedings of the IEEE 9th Annual Computing and Communication Workshop and Conference, 2019

Embedded System Enabled Vehicle Collision Detection: An ANN Classifier.
Proceedings of the IEEE 9th Annual Computing and Communication Workshop and Conference, 2019

Pruning the Convolution Neural Network (SqueezeNet) based on L2 Normalization of Activation Maps.
Proceedings of the IEEE 9th Annual Computing and Communication Workshop and Conference, 2019

2018
Collision warning system: embedded enabled (RTMaps with NXP BLBX2).
Proceedings of the 2018 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT), 2018

Pruning convolution neural network (squeezenet) using taylor expansion-based criterion.
Proceedings of the 2018 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT), 2018

Interoperability Enhancement in Health Care at Remote Locations using Thread Protocol in UAVs.
Proceedings of the IECON 2018, 2018

Sensor Fusion to Detect Scale and Direction of Gravity in Monocular Slam Systems.
Proceedings of the IECON 2018, 2018

2008
Fast Implementation of VC-1 Video Codec Standard.
Proceedings of the ISCA 23rd International Conference on Computers and Their Applications, 2008

Fast H.264 Video Codec Standard.
Proceedings of the ISCA 23rd International Conference on Computers and Their Applications, 2008

Motion Vector Search Modified to Reduce Encoding Time in H.264 and VC-1.
Proceedings of the ISCA 23rd International Conference on Computers and Their Applications, 2008

2003
Quantized DCT on H26L Test Model.
Proceedings of the ISCA 18th International Conference Computers and Their Applications, 2003

2002
Low-Complexity, Low-Memory Entropy Coder for Image Compression on MSC8102 DSP.
Proceedings of the 15th International Conference on Computer Applications in Industry and Engineering, 2002

1999
Development with Motorola's DSP56800 Processors.
Proceedings of the Signal and Image Processing (SIP), 1999

1996
Compression of Stereoscopic Images Using Pyramid and Prune DCT Encoding.
Multim. Tools Appl., 1996

A Fast 8 × 8 Pruned DCT Algorithm.
Digit. Signal Process., 1996


  Loading...