# 学生对 纽约州立大学布法罗分校 提供的 Image Processing, Features & Segmentation 的评价和反馈

## 课程概述

This course empowers learners to develop image processing programs and leverage MATLAB functionalities to implement sophisticated image applications. It provides a rich explanation of the fundamentals of computer vision’s lower- and mid-level tasks by examining several principle approaches and their historical roots. By the end of the course, learners are prepared to analyze images in frequency domain. Topics include image filters, image features and matching, and image segmentation. This course is ideal for anyone curious about or interested in exploring the concepts of computer vision. It is also useful for those who desire a refresher course in mathematical concepts of computer vision. Learners should have basic programming skills and experience (understanding of for loops, if/else statements), specifically in MATLAB (Mathworks provides the basics here: https://www.mathworks.com/learn/tutorials/matlab-onramp.html). Learners should also be familiar with the following: basic linear algebra (matrix vector operations and notation), 3D co-ordinate systems and transformations, basic calculus (derivatives and integration) and basic probability (random variables). Material includes online lectures, videos, demos, hands-on exercises, project work, readings and discussions. Learners gain experience writing computer vision programs through online labs using MATLAB* and supporting toolboxes. This is the second course in the Computer Vision specialization that lays the groundwork necessary for designing sophisticated vision applications. To learn more about the specialization, check out a video overview at https://youtu.be/OfxVUSCPXd0. * A free license to install MATLAB for the duration of the course is available from MathWorks....

## 1 - Image Processing, Features & Segmentation 的 20 个评论（共 20 个）

Aug 21, 2019

I put 2 because the course exists and covers important foundations for anyone who wants to learn computer vision.

However I cannot put more because it looks like the class has been done in a hurry. For example, the videos are not complet so it is very hard to understand some concepts. Moreover the videos cover large subjects and the graduated exercises are on very specific functions so you will need to spend a lot of time on Google to figure them out. And finally don't count on the trainers to help you a lot in the forum (they go there maybe once a week...).

Sep 18, 2019

Sadly there is not much examples shown, you only see the lecturers talking and not an image or a presentation which visualizes what they are explaining.

No graphs or formulas were written out or shown while they were explained, and not that many example images either.

This is an course on images and their processing it should be easy to integrate that into this course and visualize what you are trying to teach!

Aug 14, 2019

Aug 18, 2019

Some parts of the video lectures are missing and the coding exercises don't match what we learn so it's very hard to complete them.

Jul 03, 2019

The course is missing a lot of slides that are referenced in the lectures.

Sep 13, 2019

Very less slides and there is lot of grading problems

Sep 12, 2019

This course is far more worse than the first one in the specialization. The MATLAB tool doesn't work. Plain awful.

May 31, 2019

Very Bad

Sep 22, 2019

Video lectures are missing slides that might illustrate what the Indian bloke is talking about. As such, the video lectures are mostly useless. Most topics are covered in a very brief fashion, if at all. Some of the Week 4 lectures are a huge 58 seconds long! There is little to nothing in the lectures to help with the quizzes and MatLab exercises. Reading the resources can help, but why pay Coursera so that you can be told to read Wikipedia? The Week 4 resources included videos from Khan Academy and Udemy (or was it Udacity), so what exactly are we paying Coursera for? The final straw for me was the Week 4 Image Segmentation MatLab exercise - the code we got to start with seemed complete, so I ran it as-is, and scored 100% without even editing a single line of code. What is the point of that? SUNY and Coursera should be ashamed of themselves.

Sep 22, 2019

No proper content or explanation.

Aug 17, 2019

This meant to be a great course.

However, it was delivered in an extremely poor quality. Slides are missing in each video, a number of links to the addition material for reading are either broken or refer to the papers one should pay to be able to download.

No connection between videos and quizzes.

Videos without slide are useless.

Coursera should require to verify the context of the course. I took a couple of courses on Coursera in the past. This one is the lowest quality I experienced.

Jun 14, 2019

Lectures are incomplete, exercises are not well written. Staff is not helpful. Don't go with Computer Vision Specialization By University of Buffalo it is complete waste of time and money.

Aug 03, 2019

Poor content. Poor quality of video lectures. Poor study material.

Jul 31, 2019

The material is incomplete as are the lectures. Multiple topics are mentioned as "let us see in the following example about k-means...." from which the lesson just ends or the lecturer jumps to another aspect with no explanation of the material. From initial suspect I would hold the editing team at fault for not adding (what I hope) is material that the professors submitted. I had already paid for a month and as such did not withdraw from this course. Only aspect I learned is names of procedures used and my skills at googling them.

Jul 28, 2019

This course is a fraud ! Coursera should audit the quality of their content to maintain high standards !

Jun 19, 2019

I have not completed the course yet but the lectures are incomplete. It's really difficult to understand the missing parts of the lectures. Please look in to the ambiguity. Thank you.

Sep 18, 2019

Served its purpose even though it's a bit short. Many subjects were not covered in enough depth.

Jul 06, 2019

Overall is a very steep learning curve, mostly on discussion among students to figure out the solutions of the assignments. Not much example in the lecture videos.

Sep 24, 2019

The assignments are to good. But the contents in the video are way to prescribed. There to be more explanation and the algorithm are not at all explained.

Sep 24, 2019

Incomplete content