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Muhammad Saqib

FAST · 2023 · i19-0494

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Phone

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GitHub

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Academic

Program

BSCS

CGPA

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Year

2023

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

Tensorflow, Keras, Flask, Flutter, React, Firebase, Roboflow, PyTorch, Colab, OpenCV, NumPy, Computer Vision, Deep Learning

Verbatim text

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Muhammad Saqib (i19 - 0494)

Group Members:
Muhammad Saqib (i19 - 0494)
Vara Ali (i19 - 0502)

Supervisor Name:
Dr. Atif Jillani
Dr. Kashif Sagher (NESCOM Supervisor)

Technology Used:
Tensorflow , Keras , Flask , Flutter , React ,
Firebase , Roboflow , PyTorch , Colab

AUTO INSPECT
AUTOMATED INSPECTION OF SURGICAL INSTRUMENTS
GROUP MEMBERS
Vara Ali i190502
Muhammad Saqib i190494
SUPERVISOR
Dr. Atif Jillani
Dr. Kashif Sagher (NESCOM Supervisor)
Industrial Collaborator :- Dr. Frigz International

PROJECT FEATURES
Development of prototype machine for automated image acquisition
Classification of surgical instruments as faulty / non-Faulty
Indicating the type of fault i.e., cracks , pores , corrosion, tucks and scratches etc.
Web Interface for displaying quality related stats in form of dashboard

PROJECT ARCHITECTURE
Industrial Setup with Conveyor Belt Vision Unit
Computational Unit
Web Interfaces Stats Visualizations & Dashboards
Data Storage Business Decision & Analysis
Computer Vision based Algorithms
Image Processing & ML Models

PROJECT TIMELINE
JAN - FEB
- Dataset generation for other two type of surgical instruments
- Incorporating all the images captured to devise an algorithm capable of classification
MAR - APR
- Complete Web Interface with back-end & cloud storage integrated
- Development & deployment of prototype machine
MAY - JUN
- Dataset generation for scissor along with necessary pre-processing
- Applying computer vision algorithms to classify all the scissors correctly
JULY - AUG
- Applying computer vision algorithms to indicate the type , shape and size of the fault
- UI development for the web interfaces & cloud

TOOLS & TECHNOLOGIES
OpenCV
NumPy
React
YOLO

AI enrichment

Muhammad Saqib is a BSCS student who collaborated on an automated inspection system for surgical instruments using computer vision and machine learning. The project involved developing a prototype for image acquisition, classifying faults, and creating a web dashboard for data visualization.

Skills (AI)

["TensorFlow", "Keras", "Flask", "Flutter", "React", "Firebase", "Roboflow", "PyTorch", "OpenCV", "NumPy", "YOLO", "Computer Vision", "Machine Learning", "Image Processing"]

Status: ai_done

Provenance

Source file: FAST - School of Computing -Graduate Directory-2023.pdf
From job #14 page 335
Created: 1778140212