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Udacity Computer Vision Nanodegree

Projects completed under Udacity's Computer Vision nanodegree program.

PyTorch library is used to complete the projects 1 and 2.

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In this project, we'll build a Facial keypoint detection system. The system consists of a face detector that uses Haar cascades and a Convolutional Neural Network, that predicts the keypoints on the detected face.

_Original Repo: Link

Project-2: Image Captioning

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In this project, we'll design and train a ENCODER-DECODER(Convolutional Neural Network - Recurrent Neural Network) model for automatically generating image captions. The network is trained on the Microsoft Common Objects in COntext (MS COCO) dataset.

Original Repo: Link

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In this project, we'll implement SLAM (Simultaneous Localization and Mapping) for a 2-dimensional world. Sensor and motion data gathered by a simulated robot is used to create a map of an environment. SLAM gives us a way to track the location of a robot in the world in real-time and identify the locations of landmarks such as buildings, trees, rocks, etc.

Original Repo: Link

Images credits: Flaticon

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Projects completed under Udacity's Computer Vision nanodegree program.

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