Waste image classification into organic or recyclable ones with CNN algorithm.
Image augumentation for deep learning
This project aims to develop a high-precision legal expert system for contract Q&A using Retrieval-Augmented Generation (RAG). The system leverages advanced natural language processing (NLP) techniques to provide accurate and context-aware answers to questions about legal contracts and integrates a powerful language model with a custom retrieval
Kaggle Competition: The recognition diseases on apple leaves based on their photos by using CNN and MobileNet V2 model.
Project aims to create a face mask detection system using Convolutional Neural Networks (CNNs)
Distinguish bees from wasps
It is tensorflow 2.0 implementation on Eurosat Dataset. IT classfies different types of satelite images. Used transfer learning in end to reduce overfitting and increase accuracy.
U-Net with ResNet backbone for multi-class segmentation. Includes advanced data augmentation, mixed-precision training (AMP), custom loss functions (Tversky, Dice, BCE), threshold tuning, and evaluation with IoU/Dice metrics. Built in PyTorch with Albumentations, optimized for GPU acceleration and scalable on Vertex AI / GCP.
augmenting object detection dataset along with bounding box annotations
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