User:Tt1887/Evaluate an Article

Evaluate an article

This is where you will complete your article evaluation. Please use the template below to evaluate your selected article.

Name of article: Machine vision
Briefly describe why you have chosen this article to evaluate. I choose this article because this is related to my research topic and my company's current product. I am familiar with this area.

Lead

Guiding questions

Machine vision (MV) is the technology and methods used to provide imaging-based automatic inspection and analysis for such applications as automatic inspection, process control, and robot guidance, usually in industry. Machine vision refers to many technologies, software and hardware products, integrated systems, actions, methods and expertise. Machine vision as a systems engineering discipline can be considered distinct from computer vision, a form of computer science. It attempts to integrate existing technologies in new ways and apply them to solve real world problems. The term is the prevalent one for these functions in industrial automation environments but is also used for these functions in other environments such as security and vehicle guidance.

The overall machine vision process includes planning the details of the requirements and project, and then creating a solution. During run-time, the process starts with imaging, followed by automated analysis of the image and extraction of the required information.

Does the Lead include an introductory sentence that concisely and clearly describes the article's topic?
Does the Lead include a brief description of the article's major sections?
Does the Lead include information that is not present in the article?
Is the Lead concise or is it overly detailed?

Lead evaluation

This article gives a concisely and clearly describes of the topic and match the major sections. The lead gives some details about the differences between machine vision and computer vision which is easily get confused by people. Overall, the lead is concise.

Content

Guiding questions

Is the article's content relevant to the topic?
Is the content up-to-date?
Is there content that is missing or content that does not belong?

Content evaluation

The content is pretty much relate to the topic. Based on the view history, many people has updated this article which means the content is up-to-date. There is no content is not belong. However, in my point of view, I think the topic could include more about the applications of the machine vision and main companies that focus on the machine vision products. Also, I think it can put more information on equipment.

Tone and Balance

Guiding questions

Is the article neutral?
Are there any claims that appear heavily biased toward a particular position?
Are there viewpoints that are overrepresented, or underrepresented?
Does the article attempt to persuade the reader in favor of one position or away from another?

Tone and balance evaluation

The article is very neutral. No claims are heavily biased. Most of contents are talking about in technology aspects which is very professional. This article is meant to give readers an overview of the machine vision which is did a very good job.

Sources and References

Guiding questions

Are all facts in the article backed up by a reliable secondary source of information?
Are the sources thorough - i.e. Do they reflect the available literature on the topic?
Are the sources current?
Check a few links. Do they work?

Sources and references evaluation

Based on the references, their sources are very reliable. Most of references are from the authority academic paper. Many authors of those academic papers are well known in machine visions.

Organization

Guiding questions

This field encompasses a large number of technologies, software and hardware products, integrated systems, actions, methods and expertise. Machine vision is practically the only term used for these functions in industrial automation applications; the term is less universal for these functions in other environments such as security and vehicle guidance. Machine vision as a systems engineering discipline can be considered distinct from computer vision, a form of basic computer science; machine vision attempts to integrate existing technologies in new ways and apply them to solve real world problems in a way that meets the requirements of industrial automation and similar application areas. The term is also used in a broader sense by trade shows and trade groups such as the Automated Imaging Association and the European Machine Vision Association. This broader definition also encompasses products and applications most often associated with image processing. The primary uses for machine vision are automatic inspection and industrial robot/process guidance. See glossary of machine vision.

Is the article well-written - i.e. Is it concise, clear, and easy to read?
Does the article have any grammatical or spelling errors?
Is the article well-organized - i.e. broken down into sections that reflect the major points of the topic?

Organization evaluation

It is a concise article. However, I think there is still a space to revise the definition. I think the definition is easy to get confused. The article seems want to give Machine Vision different broad definition based on different applications. However, it did not show very clearly in this definition. Other parts I think is organized.

Images and Media

Guiding questions

Does the article include images that enhance understanding of the topic?
Are images well-captioned?
Do all images adhere to Wikipedia's copyright regulations?
Are the images laid out in a visually appealing way?

Images and media evaluation

There is only one picture in this topic. I think if people is new for machine vision, probably will not get the sense of the picture. The image adheres to Wikipedia's copyright regulations. The image did not real appeal people in this case.

Checking the talk page

Guiding questions

This article is about both a term and a widely-varying set of endeavors which often go by that term It is the term most commonly used to try to assemble and refer to a set of endeavors in that field, although other terms are often used for subsets, supersets and partially overlapping sets of those endeavors.

So, the article needs to both describe the meaning of the term "machine vision", and then provide coverage of the field defined by that term. On the latter the article keeps getting nuked to the point where, 13 years after it's inception, this article about a large and important field looks like little more than a stub. While this may sometimes be an issue with the nukers, it also may also be vulnerable due to using too much etymology type wording in the coverage of the field, and generally organizing the whole article along entomology lines.

For example, let's say there's a common term "Native American History" and an article titled "Native American history" (which there isn't by that name) which opens with a definition of that term. As with machine vision, other groupings and titles may apply to that general topical area. Then, someone builds a section on the Puebloan Culture of the 13th century. That section should probably not be explicitly saying / repeating "Native American history includes the Pueblo Culture of the 13th century". Conversely, somebody should not be nuking that whole section because the sources don't explicitly say that Native American History includes Pueblo Culture of the 13th century. I think that we've had both of these issues here. I plan to try to work on the wording and organizational side. North8000 (talk) 15:50, 26 February 2017 (UTC)

What kinds of conversations, if any, are going on behind the scenes about how to represent this topic?
How is the article rated? Is it a part of any WikiProjects?
How does the way Wikipedia discusses this topic differ from the way we've talked about it in class?

Talk page evaluation

There are not many conversations in this topics. However, the author started a conversation with others. Based on his written, I think he is a modest and pragmatic person. He keep updating this topic and people who read this article is appreciate his effort since machine vision is a really hard and blocking region for most of people.

Overall impressions

Guiding questions

What is the article's overall status?
What are the article's strengths?
How can the article be improved?
How would you assess the article's completeness - i.e. Is the article well-developed? Is it underdeveloped or poorly developed?

Overall evaluation

Overall, this is a very professional article for machine vision. The author worked really hard to give people a broad idea what machine vision is. The job he did is amazing. One thing I think the article can be improved is to relate machine vision more in real applications, give readers some actual examples. The article is well-developed in my point of view.

Optional activity

Choose at least 1 question relevant to the article you're evaluating and leave your evaluation on the article's Talk page. Be sure to sign your feedback

with four tildes — ~~~~

Link to feedback: Talk:Machine vision#New thought that might help this bruised-and-abused article