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Junaid's Projects

cv-11-attendancesytsem_antispoofing icon cv-11-attendancesytsem_antispoofing

Anti-Spoof Face Recognition Attendance System. The system uses computer vision techniques to prevent spoofing attempts during face recognition, ensuring the accuracy and security of attendance records.

cv-13-brats2020_semantic_segmentaion icon cv-13-brats2020_semantic_segmentaion

3D segmentation of brain tumors from the BraTS2020 dataset using TensorFlow, 3D-UNET architecture, and the segmentation-model-3D package. The BraTS2020 dataset is approximately 40 GB in size, comprising both training (~30 GB) and validation sets (~10 GB).

dl-coccidiosis_disease_detection icon dl-coccidiosis_disease_detection

Detect the presence of coccidiosis, a common parasitic disease in Poultry Chickens), using deep learning techniques. The app utilizes a transfer learning approach with the VGG16 architecture to classify input images as either indicative of coccidiosis or not.

ml-03-forestfireprediction icon ml-03-forestfireprediction

A machine learning-based web app for forest fire and Fire Weather Index prediction. Performed Feature Selection, Feature Engineering, and voting classifier/Regressor based ensemble techniques. Implemented MongoDB and deployed it on Render

nlp-llm-13-sqlpalm icon nlp-llm-13-sqlpalm

SQLPaLM, allow user to query into SQL DB using Natural Language. Google PaLM, Chroma, LangChain, MySQL, Streamlit.

py-01-amazonscraper icon py-01-amazonscraper

Implemented MongoDB, Beautiful Soup, and Flask and Deployed on Render. Product ID, titles, ratings, price, discount, discounted price, and reviews can be extracted from a user-defined range of Amazon page numbers.

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