Detection and classification of road and objects in panoramic images on board the ATLASCAR2 using Deep Learning

Week 1 & 2

Getting Started.

On these weeks I started by installing the ROS environment and doing the tutorials present in this link to prepare a workshop given by Professor Miguel Oliveira.

In the workshop he showed us the ROS environment and we played a team hunting game where each person had a player and belonged to a team. During the game, players from the blue team had to hunt those from the red team, red team had to hunt the members of green team and green team had to catch up the blue ones.
In this workshop we used Python2 for programming our players, and used GitHub to work in a corporative environment. After we had fun playing some games, Professor Miguel Oliveira showed us some projects where he used ROS.

I also have been writing a preliminary report for my dissertation, where I read about the work that had been done by previous students and also started to explore a litle bit more about Deep Learning. At the end of the week I had a meeting with Professor Vítor Santos, where we discussed some points about the preliminary report and the first steps to take.

• Date: 23 February 2020

Week 3

First Researches.

On this week I kept researching more about the past projects at LAR and other projects that use neural networks on panoramic images. I just wrote the preliminary report where I defined the main requirements in terms of hardware for classifying images in real time and also mentioned some networks that I might try for the classification process.

I ended up developing some stands for the positioning of the cameras as you can see on the image bellow.

• Date: 27 February 2020

Week 4

LAR Meeting.

This week I've been making the last adjustments to the stands for positioning of the cameras, and it ended up as shown on the picture bellow.

I also tried to pass the images from the cameras through ROS topics at the same time as I prepared the LAR Meeting, where I and some colleagues had to present our thesis subjects and the work that we have been doing.

• Date: 5 March 2020

Week 5

Fast.ai

My main focus for this week was to explore more about Deep Learning. For it, I used Google Colab to keep doing the Fast.ai pratical Deep Learning course and trained a model with a simple dataset that I create with internet images.

With the training of this dataset I was able to learn more about terms such as learning rate and its influence on the training of a model, and I also became more familiar with some interpretation techniques, like using confusion matrices to find were the model performance was lower.

• Date: 12 March 2020

Project Name

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• Date: January 2017
• Client: Southwest
• Category: Website Design

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• Date: January 2017
• Client: Window
• Category: Photography