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Ahmed Bassiouny Online Offline
- 98%Jobs Completed
- 100%On Budget
- 74%On Time
- 14%Repeat Hire Rate
Finding Eye gaze with regular web camera - open to bidding
“Ahmed is such a talented freelancer,very humble and friendly in his best to solve any query if you hire him without any will never disappoint you.”Sloopysafe 3 weeks ago.
create a software with rabbitmq, mysql and c#
“Just hire him, you will never be disappointed,”mehdisne 2 months ago.
Write some Software that will take certain information from racingpost.com and compile odds for horses based on that information.
“Excellent programmers. Had a tricky program to write and did extremely well, understood exactly what I was after!! Thanks!!”hiflyer007 2 months ago.
DeepWalk algorithm on NVIDA GPU
“I liked Ahmed's communication and willingness to fix bugs. We were disappointed in the documentation. We also believe we need to improve our requirements description to avoid confusion.”mecollado 3 months ago.
“Excellent Programmer ! I would go with him for my next project too !”rahmcalumet 3 months ago.
Seat map creator, seat selector and json generator -- 2
“Ahmed is a nice combination of technical skills and excellent communication. It did not take much of an effort explaining the requirement to him.”ogive 4 months ago.
Research AssistantSep 2013 - Jul 2014 (10 months)
Part of the computer vision team
Bachelor of science2009 - 2013 (4 years)
IbTIECar Best Graduation Project award (2014)IbTIECar
Won 1st position in TIEC Graduation Projects Competition for virtual realitygraduation thesis "DreamOn".
Semantic Segmentation as Image Representation for Scene Recognition using
We introduce a novel approach towards scene recognition using semantic segmentation maps as image representation. Given a set of images and a list of possible categories for each image, our goal is to assign a category from that list to each image.
Facial Expression Recognition in the Wild Using Rich Deep Features
In this paper we present a novel approach towards facial expression recognition. We fuse rich deep features with domain knowledge through encoding discriminant facial patches. We conduct experiments on two of the most popular benchmark datasets; CK and TFE. Moreover, we present a novel dataset that, unlike its precedents, consists of natural - not acted - expression images.
UK English 188%
Python Level 185%