https://github.com/philferriere/aind-projects
Phil Ferriere's Artificial Intelligence Nanodegree Projects (reports and code)
https://github.com/philferriere/aind-projects
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Phil Ferriere's Artificial Intelligence Nanodegree Projects (reports and code)
- Host: GitHub
- URL: https://github.com/philferriere/aind-projects
- Owner: philferriere
- Created: 2017-01-27T01:51:48.000Z (over 8 years ago)
- Default Branch: master
- Last Pushed: 2017-09-26T21:37:46.000Z (about 8 years ago)
- Last Synced: 2025-03-30T01:37:04.433Z (7 months ago)
- Language: HTML
- Homepage:
- Size: 82.2 MB
- Stars: 27
- Watchers: 8
- Forks: 30
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
Artificial Intelligence Nanodegree Projects
===========================================
This repo contains our work on Udacity's [Artificial Intelligence Nanodegree](https://www.udacity.com/course/artificial-intelligence-nanodegree--nd889) Projects.
# Facial Keypoint Detection + Real-time Filtering [Capstone Project]
This exciting and fun capstone project required **combining traditional computer vision techniques and deep learning** to build and end-to-end facial keypoint recognition system. Fisrt, we used OpenCV to build a **face detector** and pre-process video input data. Second, we **trained a CNN to detect facial keypoints** in the face area of the video frame. Third, we used OpenCV again to apply a template (sunglasses) on top of the facial keypoints in real-time.
[](./cv-facialkeypoints/CV_project.ipynb)
[](./cv-facialkeypoints/CV_project.ipynb)
Our capstone project can be reviewed [here](./cv-facialkeypoints/CV_project.ipynb).
# CNN-based Dog Breed Classifier
For this computer vision problem, we experimented with two different **CNN (Convolutional Neural Network) architectures**. In our first approach, we built a CNN **from scratch**. Second, we used **transfer learning** to leverage pre-trained models (VGG-16, VGG-19, ResNet-50, Inception, Xception), only training the head of the network (the fully connected classification layer) for our specific application (84.8% test accuracy w. ResNet-50)
[](./dog-project/dog_app.ipynb)
The notebook for this project can be found [here](./dog-project/dog_app.ipynb).
# Facial Expressions Identification
In this project, we use [Affectiva’s Emotion-as-a-Service API](https://developer.affectiva.com) to **track faces** in a video and **identify facial expressions**. We tag each face with an appropriate emoji next to it. If you own a webcam, you may also play a simple game: mimic a random emoji we display and we will automatically recognize if your expression matches our random selection!
[](./cv-mimic/README.md)
Our implementation is available [here](./cv-mimic/README.md).
# Sign Language Recognition
Here, we use **HMMs (Hidden Markov Models)** to recognize gestures in American Sign Language, from individual words to complete sentences. We train our system on a dataset of videos that have been pre-processed and annotated, and test on novel sequences.
[](https://drive.google.com/open?id=0B_5qGuFe-wbhUXRuVnNZVnMtam8)
Click [here](./recognizer/asl_recognizer.ipynb) to review the IPython notebook for this project.
# Planning Search
For this project, we implement a planning search agent to solve deterministic logistics planning problems for an Air Cargo transport system. We use a **planning graph** and **automatic domain-independent heuristics with A* search** and compare their results/performance against several **uninformed non-heuristic search methods** (breadth-first, depth-first, etc.).
Additional details can be found [here](./planning/README.md).
# Game-Playing Agent
This game-playing agent uses techniques such as **iterative deepening**, **Minimax**, and **Alpha-Beta Pruning** to beat its opponent in a game of *Isolation* (a two-ply discrete competitive game with perfect information).
[](./isolation/README.md)
For details about our implementation, please visit this [link](./isolation/README.md).
# Diagonal Sudoku Solver
In this introductory project, we use **constraint propagation** to find solutions to Sudoku puzzles, repeatedly applying game rules (constraints) until the Sudoku puzzle stops changing.
[](./cv-mimic/README.md)
For more information about this project, go [here](./sudoku/README.md).
# Contact Info
If you have any questions about this work, please feel free to contact us here:
[](https://www.linkedin.com/in/philferriere)