Sweekar Dahal

Sweekar Dahal

About Me

My name is Sweekar Dahal. I graduated with a Bachelor’s in Computer Engineering from Kantipur Engineering College (affiliated with Tribhuvan University). I enjoy using programming to address practical problems, and many of my projects are inspired by challenges I see in everyday life. I have solid experience with Python, C#, TypeScript, and SQL. My long-term goal is to contribute to research and development in meaningful technological areas.

Projects

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GuffGaff

Welcome to GuffGaff – Your Space to Think, Speak, and Connect!
(small scale production)

GuffGaff is not just a social app — it’s a living, breathing community. Here, we believe that: Everyone has something valuable to say Listening is just as powerful as speaking A question can be the start of a revolution Constructive disagreement makes us smarter Empathy builds bridges

  • Got something on your mind? 👉 Create a post
  • Want advice or perspectives? 👉 Ask a question
  • Feel inspired or intrigued? 👉 Comment, upvote, or share your views
  • ✍️ Create. Share. Engage.

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WBpro

WBpro is a modern web application designed to help you track, manage, and optimize your daily tasks—both individually and collaboratively.
(Use 'demo' as username and password for preview.)

WBpro goes beyond simple task management. Its goal is to promote holistic well-being by integrating personal goals, work objectives, and collaboration features into a single, streamlined platform. Key features include:

  • Daily Task Management: Plan your day with smart to-do lists, set reminders, due dates, and recurring tasks.
  • Collaborative Workspaces: Share tasks and projects with your team, assign roles, and track contributions.
  • Progress & Well-Being Tracking: Monitor your daily, weekly, and monthly progress with built-in mood and focus check-ins.
  • Sync Across Devices: Access your tasks anywhere with a responsive design.
WBpro is ideal for professionals, students, teams, and individuals aiming for productivity and life balance.

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Log my Expense

Log my Expense is a mobile application designed to help you track, manage, and optimize your finances with an intuitive interface.

Log my Expense provides a user-friendly platform to monitor your financial activities. Key features include:

  • Expense Tracking: Categorize and log expenses in real-time.
  • Budget Planning: Set monthly budgets and receive alerts for overspending.
  • Financial Insights: Generate reports to analyze spending patterns.
This app is perfect for individuals looking to gain control over their finances.

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Brain Tumor Detection

A research project using semantic segmentation to detect brain tumors in MRI scans.

This project focuses on detecting brain tumors using MRI scans trained on semantic segmentation models like U-Net and DeepLabv3. The dataset was curated from various sources and labeled using LabelImg. Key aspects include:

  • Dataset: Curated from multiple sources with precise annotations.
  • Models: Trained on U-Net, DeepLabv3, and other architectures.
  • Evaluation: Results based on k-fold cross-validation for robustness.
The project aims to contribute to medical imaging advancements.

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NHD Dataset - Text detection and recognition

A benchmark dataset for Nepali handwriting detection, providing baseline models for text localization and recognition.

The NHD dataset is designed to advance research in Nepali handwriting recognition. Contributions include:

  • Dataset: A comprehensive collection of Nepali handwritten texts.
  • Baseline Models: Models for text localization and recognition using established frameworks.
  • Applications: Supports development of accurate handwriting recognition systems.
This dataset serves as a valuable resource for researchers in text recognition.

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Weed Detection Using UAV

A comparative study using segmentation networks for weed detection in UAV images. This study is performed in six different segmentation models, utilizing image processing for lowering overfitting and increasing accuracy.

This study leverages UAV imagery to detect weeds in agricultural fields, improving crop yields. Key points:

  • Models: UNet combined with EfficientNetB0 for high accuracy.
  • Application: Enables early weed detection for farmers.
  • Impact: Increases crop yields by targeting weed removal.
The project supports precision agriculture for sustainable farming.

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BigNum

A JavaScript library inspired by BigDecimal for precise number rounding. This is a few lines of code to adjust number after it has been processed using standard approach.

BigNum is a JavaScript library addressing precise number rounding issues. Features include:

  • Algorithm: Uses recursive functions to sum digits after the decimal point.
  • Precision: Mimics Round Ceil approach (e.g., 45.66045 rounds to 45.661 for 3 decimal places).
  • Use Case: Solves rounding problems seen in standard approaches like BigDecimal.
This passion project enhances numerical precision in JavaScript applications.