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Comentários e feedback de alunos de Visual Perception for Self-Driving Cars da instituição Universidade de Toronto

35 classificações
5 avaliações

Sobre o curso

Welcome to Visual Perception for Self-Driving Cars, the third course in University of Toronto’s Self-Driving Cars Specialization. This course will introduce you to the main perception tasks in autonomous driving, static and dynamic object detection, and will survey common computer vision methods for robotic perception. By the end of this course, you will be able to work with the pinhole camera model, perform intrinsic and extrinsic camera calibration, detect, describe and match image features and design your own convolutional neural networks. You'll apply these methods to visual odometry, object detection and tracking, and semantic segmentation for drivable surface estimation. These techniques represent the main building blocks of the perception system for self-driving cars. For the final project in this course, you will develop algorithms that identify bounding boxes for objects in the scene, and define the boundaries of the drivable surface. You'll work with synthetic and real image data, and evaluate your performance on a realistic dataset. This is an advanced course, intended for learners with a background in computer vision and deep learning. To succeed in this course, you should have programming experience in Python 3.0, and familiarity with Linear Algebra (matrices, vectors, matrix multiplication, rank, Eigenvalues and vectors and inverses)....
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1 — 7 de {totalReviews} Avaliações para o Visual Perception for Self-Driving Cars

por River L

Jun 23, 2019

I had a great time taking this course. Thank you!

por Joachim S

Jun 18, 2019

Like the previous two course I found this one well structured and presented. Basically my comments from course 1 and 2 still hold. I found the coding assignment for week 2 rather challenging but with the help of the discussion forum there should be no problem to pass it. In contrast the final coding project was less difficult. I really loved the content of the final assignment as it provided a detailed look under the hood of a perception stack guiding you through the various stages. The multiples pictures generated as part of your code are a great help to understand the various aspects.

por 刘宇轩

May 19, 2019

Though not dive into training neural net. But for me who have taken deep learning specialization, I fully respect this and find it amazing that this course introduces quite a lot of the application of deep learning output and provides programming exercises on them, which is great.

por Miguel

May 09, 2019

Excelent Course, extremely recommended.

por Camilo A A B

May 04, 2019

It is an amazing course. Really good information and projects related with Visual Perception

por Hao Z

Apr 24, 2019

I do not understand why this course just have 4.3 ratting. Personally I think this course is very very helpful. It provides many practical advice and makes feel that I have got a up-to-date understanding of this fiels. There is no doubt that this is one of the best courses on Coursera.

por Levente K

Mar 25, 2019

Good intro for those with not much experience w/ image processing/computer vision w.r.t. autonomous driving.