― Andrew Ng
Humans use their eyes and their brains to see and visually sense the world around them. Computer vision is the science that aims to give a similar, if not better, capability to a machine or computer.
Computer vision is concerned with the automatic extraction, analysis and understanding of useful information from a single image or a sequence of images.
The second component of Computer Vision is the low-level processing of images. Algorithms are applied to the binary data acquired in the first step to infer low-level information on parts of the image. This type of information is characterized by image edges, point features or segments, for example. They are all the basic geometric elements that build objects in images.
These days, why have we been hearing so much about deep learning? Traditional Machine Learning approaches worked like the top half of the picture above. You would have to design a feature extraction algorithm which generally involved a lot of mathematics (complex design), wasn’t very efficient, and didn’t perform too well at all. After doing all of that you would also have to design a whole classification model to classify your input given the extracted features.
What will we do?
We would like to share our experience and teach the complex algortihms to all student! In the future, we will share instructions for using open source libraries such as Tensorflow and explain deep learning algortihms in a simple way.
We’ll give presentations about deep learning. In these presentations, we will make an introduction to deep learning. Students will know how to train and predict their models and use NVIDIA Jetson TX1. They will be able to easily install high-level deep learning libraries.
We are using NVIDIA JETSON TX1 to train and predict our models. Our training videos and papers will be shared!
We build robot which contains STEAM concept and create teams to teach mechinical design, math, art, software and electronic systems. ParsRobotics has founded in 2016 and It became 2nd place in Turkish Off-season 2016.
Borsa İstanbul Başakşehir Mesleki ve Teknik Anadolu Lisesi
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