My research focuses on enhancing land image classification by leveraging specialized PolSAR imagery from Sentinel 1 & 2 in conjunction with Convolutional Neural Networks (CNN). Using powerful tools such as TensorFlow and Keras, the CNN accurately categorizes land into distinct types, including Grassland, Agriculture, Barren land, and Urban areas. The computational intensity is effectively managed through Google Colab, ensuring optimal performance and speed.
To enhance accessibility, I developed a user-friendly Graphical User Interface (GUI) using Tkinter, allowing intuitive interaction with the system and better understanding of the classification process. Extensive testing and validation confirm the system's effectiveness in real-world applications, such as city planning and environmental monitoring.
This research highlights the importance of interdisciplinary collaboration and innovative approaches to remote sensing and image analysis, contributing to advancements in land classification methodologies and setting a foundation for future developments in the field.
Tech Stack: React.js, Redux Toolkit, Node.js, Express.js, MongoDB (Mongoose), Stripe, Admin Panel Developing a robust e-commerce platform with a responsive React.js frontend and efficient state management via Redux Toolkit. The backend, built with Node.js, Express, and MongoDB (Mongoose), enables secure, scalable operations, while Stripe integration supports seamless payments. An admin panel offers streamlined management of products and orders.
Tech Stack: React, Node.js, Express, MongoDB, Google Gemini API, Clerk, ImageKit Developed an intelligent chat application leveraging modern web technologies and AI for a seamless user experience. React provides a responsive UI, Clerk handles secure authentication, and React Query ensures efficient data management. The backend uses Node.js, Express, and Google Gemini for AI-driven responses, while MongoDB with Mongoose handles scalable data storage. Features include real-time chat, image upload via ImageKit, and dynamic updates..
Developed a responsive real estate platform with React, Tailwind CSS, Node.js, Express.js, MongoDB, and Prisma. Nonregistered users can view and search listings, while registered users can create listings, chat with property owners, and get live notifications. Features secure authentication with bcrypt and an interactive map with real-time property locations using Leaflet.
Developed a social media platform using HTML, CSS, and JavaScript with a visually appealing UI. Features customizable themes, including font size adjustments and light, dim, and dark modes.
Created a landing page and UI for a social media marketing website using Bootstrap. Features include sections for Home, About, Features, Pricing, Reviews, Clients, and FAQs.
