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Hybrid Deep Learning Architecture

Project type

Deep learning course final project

Date

December 2022

Location

Worcester, MA, USA

Link

Github

The Hybrid Deep Learning Architecture project is a recent endeavor that showcases a collaboration between two individuals who constructed a hybrid deep learning architecture for lane detection using SegNet. This project integrated both CNN and RNN structures via PyTorch, deploying SCNN-SegNet-ConvLSTM2 for lane detection. The project secured the top F1-score of 0.910 and a report was drafted and presented highlighting the methodologies and achievements.

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