A Glimpse into My Creative Ventures and Technical Expertise
2024, IEEE
FTDUIQA, a fusion model that integrates traditional machine learning and deep learning for assessing underwater image quality. By combining CNNIQA, DBCNN, HyperIQA, MSAEQA, and a modified MAUIQA, our approach significantly improved evaluation accuracy on the UID2021 dataset, outperforming existing methods with a PLCC of 0.8654.
Aug 2023
An Institute of National Importance Website, where I re-innovated on completed frontend and some of old backend of the website, created a custom CMS for the admin to manage the content of the website, resulting in a remarkable 95% performance improvement in rendering, and achieving a flawless 100% SEO and best practice score
May 2023
Traffic Analyzer is a deep learning-based system for analyzing and predicting traffic patterns using historical data. It employs deep learning models such as LSTMs, GRUs, and CNNs to forecast traffic conditions, optimize signal timing, and enhance route planning.The project integrates data preprocessing, time-series forecasting, and visualization, achieving an RMSE of 0.271. Its insights contribute to intelligent traffic management, reducing congestion and improving urban mobility.
September 2023
This industry project focused on developing an image processing pipeline to detect and analyze gas burner holes using OpenCV and Hough Transform. It enhanced visibility through contrast stretching, applied segmentation for accurate detection, and extracted key measurements like hole count and size distribution. Masking and filtering refined the analysis, while automated CSV reports enabled efficient data evaluation.
Mar 2023
Designed and implemented an API and mobile application for an academic project focused on advanced image processing techniques. Integrated arithmetic operations, spatial domain transformations, and frequency domain filtering using convolution-based techniques.
April 2023
Developed a machine learning system for emotion recognition using ECG signals, extracting time-series features like HRV metrics (RMSSD, SDNN, NNx, CSI, CVI). Implemented and evaluated Decision Tree and Random Forest classifiers to predict emotions such as happiness, anger, and disgust.
Dec 2022
Developed facial recognition and traffic sign recognition systems using machine learning and deep learning techniques. For facial recognition, implemented Principal Component Analysis (PCA) for dimensionality reduction and used KNN, LDA, and Logistic Regression models. For traffic sign recognition, applied CNNs and utilized the GTRSB dataset for training. Leveraged OpenCV and PIL for image processing, gaining hands-on experience with real-world data collection and deep learning concepts.
April 2022
A database management system exploring project on ticketing system of railways, Innovated UI into a macOS clone with subtle animations using popmotion and winbox, learnt about using various ORMs like Prisma, Drizzle, etc., along with direct SQL query execution.
November 2021
A mobile social media chat application which includes features inspired from snapchat and whatsapp, where I learned about real time streaming data to update chat, worked with lottie files for animation and firebase for backend.
