← Back to cohort

Hamza Azam

FAST · 2020 · i16 - 0163
Email
Phone
LinkedIn
GitHub

Academic

Program
BSCS
CGPA
Year
2020
Education
SEECS
Address
DOB

Career

Current role
Target role
Skills
Java, Python, PyTesseract, TensorFlow, Keras, Firebase, Android Studio, Flask Server, Image Classification, Image Localization, Image Processing, OCR

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.
Smart Bill Manager 
 
 Smart Bill Manager or as we call it ‘BillMan’, is a solution which uses AI to digitize the process of 
 traditional Bill Management. The aim of BillMan is to get rid of the hassle of manually storing and 
 saving bill information, and provide a way to scan, extract information, store and manage bills. 
 BillMan android app is being made, whilst keeping perspective of everyday users who come across 
 bills in their daily lives. These users are either general public or employees of a business who deal 
 with bills. The users will be able to securely authenticate into the app after which they will 
 capture/upload bill images of pre-defined categories (PTCL, IESCO (Wapda), Sui Gas). The 
 subsequent bill image is passed onto the backend AI Server which uses different techniques to 
 extract important text from the image, and sends it back to the app to display it to the user. The 
 text along with the image is saved into database which the users can later view, update or delete as 
 they wish. The app also allows the users to analyze past bill by viewing different kind of stats 
 related to it, and also compare the bills. 
 Features include: 
  Capturing/Uploading certain bill image to app and sending that image to AI server which uses 
 Image Classification, Image Localization, Image Processing and OCR to extract text from image. 
  Correcting/Verifying the extracted text and storing it along with the image to cloud database. 
  
 Viewing, updating, deleting, and sharing the bill information. 
  
 Viewing, analyzing and comparing saved bills. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 Technology Used: 
 Java, Python, PyTesseract, TensorFlow, Keras, 
  Firebase, Android Studio, Flask Server (PyCharm) 
 Supervisor Name: 
 Dr. Muhammad Adnan Tariq 
 Group Members:   
 Hamza Azam (i16 - 0163)
Provenance
Source file: Graduate Directory FAST School of Computing 2020 (Final Complete) (1).pdf
From job #23 page 220
Created: 1778226103