Plant leaf classification and Segmentation
The Dataset was based on more than 10000+ irregular plant leaf images which were labelled,segmented and classified with tools like opencv, and ensembled pre trained models.
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I am an AI and Python engineer with hands-on experience designing and automating end-to-end data workflows, including large-scale data labeling and annotation pipelines for machine learning projects. My background includes building and deploying AI-driven solutions for medical datasets, where I worked with over 1,500 labeled samples to improve diagnostic consistency and reporting reliability. I have expertise in Python, PyTorch, TensorFlow, and data engineering tools like Pandas and NumPy, as well as experience with vector databases such as Pinecone and Milvus for efficient data retrieval and indexing. My work spans computer vision and NLP, with a strong focus on developing robust ETL processes, automating data ingestion, and ensuring high-quality training data for AI models. I am skilled in containerization (Docker), workflow orchestration, and cloud platforms (AWS, Azure), and I thrive in translating complex requirements into scalable, production-ready data solutions.
The Dataset was based on more than 10000+ irregular plant leaf images which were labelled,segmented and classified with tools like opencv, and ensembled pre trained models.
Master of Science, Intelligent Vision
Bachelor of Science, Computer Science
Python and Machine Learning Engineer
Full Stack Developer Intern