CS231n: Convolutional Neural Networks for Visual Recognition by Fei-Fei Li, Andrej Karpathy, Stanford.  This course is a deep dive into details of the deep learning architectures with a focus on learning end-to-end models for these tasks, particularly image classification.

Convolutional Neural Networks for Visual Recognition, Fei-Fei Li, Andrej Karpathy, Stanford

Enter the world of signal processing: analyze and extract meaning from the signals around us! About this Course Technological innovations have revolutionized the way we view and interact with the world around us. Editing a photo, re-mixing a song, automatically measuring and adjusting chemical concentrations in a tank: each of these tasks requires real-world data to be captured by a computer and then manipulated digitally to extract the salient information. Ever wonder how signals from the…

Discrete Time Signals and Systems, Part Time Domain, Richard G.

The course will consider how what we see is generated by the visual system, and what visual perception indicates about how the brain works. The evidence will be drawn from neuroscience, psychology, science history and philosophy. Although the discussions will be informed by visual system anatomy and physiology, the focus is on perception. The purpose of the course is to consider how what we see is generated by the visual system.In the 1960s and for the following few decades, it seemed all…

Believe it or not, but the pieces A/B/C all have the same color. Use any color picker, graphic program or simply cover the remainder with your hand to see for yourself.

Learn the fundamentals of digital signal processing theory and discover the myriad ways DSP makes everyday life more productive and fun. The goal of the course is to develop a complete working set of digital signal processing notions from the ground up. DSP is arguably at the heart of the “digital revolution” that, in the space of just a few decades, has enabled unprecedented levels of interpersonal communication and of information availability. In the class, starting from the basic ...

Digital Signal Processing from École Polytechnique Fédérale de Lausanne. Digital Signal Processing is the branch of engineering that, in the space of just a few decades, has enabled unprecedented levels of interpersonal communication and of .

In this class you will learn the basic principles and tools used to process images and videos, and how to apply them in solving practical problems of commercial and scientific interests. Digital images and videos are everywhere these days – in thousands of scientific (e.g., astronomical, bio-medical), consumer, industrial, and artistic applications. Moreover they come in a wide range of the electromagnetic spectrum - from visible light and infrared to gamma rays and beyond. The ability to…

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In this class you will look behind the scenes of image and video processing, from the basic and classical tools to the most modern and advanced algorithms. What is image and video processing? Images and videos are everywhere, from those we take with our mobile devices and share with our friends to those that we receive from Mars and the ones we see in the movie theatre, without forgetting the whole ensemble of images of our bodies that are taken in hospital visits. Image and video processing…

Image and video processing: From Mars to Hollywood with a stop at the hospital, Duke University

Einführung in Computer Vision. Dieser Kurs vermittelt einen Überblick über die Grundlagen des Maschinellen Sehens an Hand der Extraktion von 3D-Information aus dem Stereokamerabild einer Szene. Räumliches Sehen stellt für die meisten Menschen eine Selbstverständlichkeit dar. Maschinen mit einem gleichwertigen Sehvermögen auszustatten, ist hingegen eine sehr komplizierte Angelegenheit. Seit den 1960-er Jahren hat sich dieser als Computer Vision bezeichnete Forschungsbereich kontinuierlich…

Einführung in Computer Vision. Dieser Kurs vermittelt einen Überblick über die Grundlagen des Maschinellen Sehens an Hand der Extraktion von 3D-Information aus dem Stereokamerabild einer Szene. Räumliches Sehen stellt für die meisten Menschen eine Selbstverständlichkeit dar. Maschinen mit einem gleichwertigen Sehvermögen auszustatten, ist hingegen eine sehr komplizierte Angelegenheit. Seit den 1960-er Jahren hat sich dieser als Computer Vision bezeichnete Forschungsbereich kontinuierlich…

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