About Me
I'm a passionate software engineer with a focus on machine learning and web development. I have completed my B.E. in Information Technology from University of Mumbai, I have experience in implementing advanced machine learning algorithms and developing innovative projects.
Featured Projects
Hybrid GAN for Image Enhancement and Preservation
Designed and developed a hybrid GAN model integrating SRGAN and DCGAN for superior image enhancement capabilities. Achieved a PSNR of 25-30 over 3001 epochs, significantly improving feature propagation.
AI-driven Sign Language Detection Glove
Developed a sign language glove using ESP-32, Node MCU, flex sensor, and TensorFlow lite CNN model for on-device detection. Recognized as a top innovation in the Smart India Hackathon Grand Finale.
PEAR - Personalized Evaluation of Allergens and Recipes.
Github LinkPEAR is an AI-driven solution designed to provide personalized insights into food allergens, nutritional values, and recipe alternatives tailored to individual dietary preferences and health requirements. The project combines machine learning and use of GEN-AI API (llama3.2) to evaluate food ingredients, detect potential allergens, and suggest safe and nutritious recipes, helping users make informed choices. This application was created at Mumbai HackFest'24.
Published Research
A Survey on Facial Emotion Recognition and Fake Emotion Detection Techniques
Published in the Journal of Electrical Systems. DOI: doi.org/10.52783/jes.3284
Co-authors: Husna Shaikh, Er. Sanam Kazi, Wasim Jasani, Viraj Sawant, Naser Shaikh, Pranav Jintunkar.
A Novel CNN-ANN Fusion Approach for Improved Facial Emotion Detection
in-preview: Indonesian Journal of Electrical Engineering and Computer Science (IJEECS)Co-authors:Viraj Sawant, Husna Shaikh, Er. Sanam Kazi, Wasim Jasani, Naser Shaikh, Lamiya Rampurwala.
Patent
A System for Detection of Fake and Genuine Emotions from Facial Images and a method Thereof
Application Number: 202421040795 | Publication Date (U/S 11A): 28-06-2024
Developed advanced models for distinguishing genuine and fake emotions in digital interactions using facial expression analysis.