Computer Vision from Scratch | New course launch | By MIT PhD | Foundations and practical CV скачать в хорошем качестве

Computer Vision from Scratch | New course launch | By MIT PhD | Foundations and practical CV

Miro notes: https://miro.com/app/board/uXjVIZB96f... 10 years ago, I worked on an interesting problem during my undergrad at IITM. It was to build a traditional (non-ML) algorithm for detecting rice grain varieties from images. This was my first deep dive into machine vision. I used no ML, just pure math and logic + traditional image filters. Our paper got accepted to the competitive International Conference for Machine Vision (ICMV) held in Nice, France. While presenting at ICMV, one thing was clear: the field was swiftly evolving. More and more researchers were abandoning purely rule-based techniques and moving to deep neural networks. In the decade since deep learning has radically reshaped computer vision. Techniques that were once considered advanced (like hand-engineered features and classical algorithms) have given way to neural networks capable of learning generalized representations of images. During my PhD at MIT for implementing computer vision for my projects, I had no doubt that I should use Deep Learning. Watching deep learning transform industries over the past 10-15 years, I realize there is a pressing need for a structured curriculum that covers computer vision, fully from scratch. 1) You should be able to learn the foundations 2) You should be able to also learn practical computer vision skills With this vision, I am launching the first-ever computer vision course on Vizuara's YouTube channel. I will be releasing my lectures for free in a new playlist “Computer Vision from Scratch”. There will be ~35 lectures totaling 200+ hours. No fluff, just deep learning with purpose and time commitment. 1) I will cover the foundations of computer vision (starting from the very basics) in the first part of the course. 2) In the second part of the course, I will cover practical aspects of CV, for anyone who wishes to transition their career to the domain of CV. Elon Musk has long been an advocate for camera-based vision in Tesla. Humans rely on their eyes to perceive depth and motion. Musk has often described LIDAR as unnecessary. When I recently finished Musk's biography by Walter Isaacson it was fascinating to learn this. From an industry perspective, there could not be a better time to take a deep dive into computer vision. If you have been planning to learn computer vision using ML, but never managed to do so, consider this as the opportunity. So let us start. Here is the 1st lecture:    • Computer Vision from Scratch | New course ...