Human activity recognition using smartphone dataset


Assignment Task:

Projects: The aim of this final project is the usage of the elements of deep learning seen in this course to solve a real problem. This project can done by up to four students. Each group of students must provide a final report (up to eight pages) about the project they developed.

I. Instructions: The following instructions must be taken into consideration:

1. The final report must specify the contribution of each member of the group.

2. In addition, the report must contain the cost in time for each stage to development this project.

3. The used method must be justified and to explain why this method is well suited for this project.

4. Please mention the kind of problems that you faced this during the realization of this project, and how you solved them. The final report must be presented in a form a research paper. The project and the final report must be submitted and validated no later than the 5th of December, 2019.

II. Suggested tools

Please note that only the following tools are accepted to do the final project.

Deep Feedforward Networks;

Convolutional Neural Networks;

Sequence Modeling: Recurrent and Recursive Networks;

Dense prediction;

Generative adversarial networks;

Deep Q-learning.

III. List of projects:

Each of the following is a large project, which can be a semester-long project done by a group of students.

Project 1: Prediction of liver fibrosis

Project 2: Human Activity Recognition using Smartphone Dataset

Project 3: Heterogeneity Activity Recognition Data Set

Project 4: HEPMASS Data Set

Project 5: Predicting Customer Profitability Dynamically over Time: An Experimental Comparative Study

Project 6: 3D object recognition

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Attachment:- Semester Project.rar

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