Khadija Bahsir · imagine-talent

Email

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Phone

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GitHub

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Academic

Program

BSCS

CGPA

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Year

2022

Education

SEECS

Address

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DOB

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Career

Current role

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Target role

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Skills

Flutter, Firebase, Tensorflow lite

Verbatim text

The exact text the LLM saw on the page (or the booklet text from the old import). This is what powers semantic search.

Hazri 

Hazri consists of a mobile application for teachers to mark attendance in classrooms using their 
phone cameras and facial recognition, and also web views for students and administrators. 
Students can upload individual pictures of their face while registering, and they can enroll for 
classes. Administrators can create classes, assign teachers to these classes, and download the 
attendance of classes. 
Hazri also provides improved results of facial recognition in low lighting conditions and in low 
resolution images. 
Features include: 
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Teachers marking attendance 
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Administrators creating classes 
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Administrators downloding class attendance 
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Students enrolling in classes  
Students uploading a picture of their face for reference comparison later on during each class 























Technology Used: 
Flutter, Firebase, Tensorflow lite 
Supervisor Name: 
Ms. Noor ul Ain 
Group Members:   
Rabbia Sajjad (I18-0422) 
Khadija Bahsir (I18-0718) 
Haider Zia (I17-0161)

AI enrichment

Khadija Bahsir is a Computer Science graduate who contributed to Hazri, a mobile application utilizing Flutter and Firebase for attendance management. The project incorporated TensorFlow Lite to implement facial recognition capabilities, including optimizations for low-light conditions.

Skills (AI)

["Flutter", "Firebase", "TensorFlow Lite", "Mobile Application Development", "Facial Recognition"]

Status: ai_done

Provenance

Source file: Graduate Directory FAST School of Computing 2022 Final Version (07-06-2022).pdf
From job #25 page 233
Created: 1778170933