About Me
My introduction
Tufail Hashmi is a lecturer and core member of iVision Lab at institute of space Technology (IST), Islamabad. He worked as a Computer Vision and DeepLearning Researcher at National University of Science and Technology (Nust), Islamabad, Pakistan. He has completed his Bachelors of Science in Software Engineering from Comsats University (Pakistan). He has completed his MS in Computer Science from NUST(Islamabad). His area of expertise are Deep Learning and Computer Vision.
Sep 2021 - Present
Islamabad, Pakistan
Qualification
My personal journeyLecturer
Institute of Space Technology (IST), Islamabad
Present
Researcher iVision Lab
Institute of Space Technology (IST), Islamabad
Present
Visiting Lecturer
Pakistan Institute of Engineering & Applied Sciences (PIEAS)
5 mos
Computer Vision Engineer
Apptrick, Islamabad-Full-Time
6 mos
Researcher
Machine Vision and Intelligent Systems Lab, Nust Islamabad
1 year
Andriod Developer
Vyro, NSTP, Nust, Islamabad-Full-Time
3 mos
Software Developer
Erudite Solutions-Full-time
6 mos
National University of Sciences and Technology (NUST)
MSCS,Computer Science
COMSATS University Islambad
Software Engineering, Computer Science
Research Work
Research-Paper
Application of Deep Learning for Weapons Detection in Surveillance Videos
Weapon detection is a very serious and intense issueas far as the security and safety of the public in general, nodoubt it’s a hard and difficult task furthermore, its troublesomewhen you need to do it automatically or with some of the AImodel.
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Rotation Aware Object Detection Model with Applications to Weapons Spotting in Surveillance Videos
Detection of weapons automatically is very important for improving the security and prosperity of people, in anycase, it is a troublesome undertaking due to huge assortmentof size, shape and presence of weapons. View point varietieswhat’s more, impediment likewise are the reasons which makesthis errand more troublesome.
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Orientation Aware Weapons Detection In Visual Data : A Benchmark Dataset
Automatic detection of weapons is significant for improving security and well being of individuals, nonetheless, it is a difficult task due to large variety of size, shape and appearance of weapons. View point variations and occlusion also are reasons which makes this task more difficult. Further, the current object detection algorithms process rectangular areas, however a slender and long rifle may really cover just a little portion of area and the rest may contain unessential details.
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Multiplatform Surveillance System for Weapon Detection using YOLOv5
In today’s modern world, safety and security arebig concerns. Daily, banks and shops are robbed, and the ratioof robberies is increasing eventually. So, there is a need forsuch a safety system that minimizes the chances of robberyand helps keep the peace and safety maintained. Mostly CCTV(Closed-circuit Television) surveillance system is used, which isquite inefficient due to the dependency on the human factor.Adding AI (Artificial Intelligence) i.e., Object Detection in thesystem will not only be efficient in discernment but will alsoidentify the potential threat in much less time
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