5 Industries Being Revolutionized by Computer Vision
Because of all the confusion around the technology, it’s easy to miss all the positive impact artificial intelligence (AI) is already having on our world. In reality, many aspects of AI like computer vision (CV),have already changed multiple industries for the better, helping businesses and organizations to improve the lives of people worldwide. Below, I’ll outline 5 industries that have seen computer vision optimize and revolutionize the way they serve humans.
1. Automotive
With self-driving cars attracting so much attention, no industry has become more well-known for its application of AI than the car industry. Many controversies still surround the innovation, but thanks to computer vision cars on the whole are getting safer.
Many driver assistance systems utilize CV to detect traffic signs or road lanes, potentially preventing drivers from having accidents caused by drifting. Similarly, parking assistance systems use CV to help drivers as they drive or back into parking spaces by detecting the objects behind or in front of the vehicle and warning them if the driver is too close.
And computer vision isn’t just being used in the cars themselves. Now, the technology is even helping manufacturers to better and more quickly identify defective parts, reducing the risk of them going on the road, making things even safer.
2. Agriculture
Agriculture has changed a lot in the thousands of years since humans began to cultivate the land, and farmers continue to innovate -- now with computer vision. Cattle rearers, for instance, are looking at using facial recognition to identify individual animals within a herd, allowing for better herd monitoring with less human intervention. It’s making for better food as well. Produce growers for some of the leading grocers around the world, including Walmart,
3. Food & Beverage
Quality assurance inspectors have one of the most crucial jobs in the food and beverage manufacturing industry. However, relying on manual checks increases the chances of them missing things like bugs or shards of glass as products move along the conveyor belt. With computer vision, these dangerous foreign objects can be identified before products are sent to a distributor. Manufacturers also use computer vision to estimate the freshness of their products, so everything that leaves their facilities is at the most optimal quality.
4. Sports
With drivers travelling at upwards of 200 miles per hour, fatalities in motorsports like car racing seem inevitable. Nascar has implemented many safety measures to protect drivers since the untimely death of world-famous race car driver Dale Earnhardt in 2001 and no further fatalities have occurred.
Still, crashes continue, resulting in significant costs and potential death, so Nascar remains vigilant. Using computer vision, they’re now trying to address the danger associated with malfunctioning cars. Utilizing its extensive data set, the company was able to train a deep learning neural network to identify specific race cars. Even with blurry images of speeding cars, the model worked faster and better than humans.
This proficiency is expected to allow the trained network to quickly identify and access whether a race car is having a problem, which could be fateful in being able to quickly diffuse potential hazards and save drivers’ lives.
5. Healthcare
As many parts of the world are so isolated, that their populaces have no access to basic healthcare or the internet. Since CV utilizes the internet, one might assume its usefulness in healthcare is limited to more centralized or “developed” locations. Companies like i-Nside challenge this notion. A world leader in endoscopic technology, i-Nside’s mission is to use AI to develop tools “that will fundamentally increase the access to diagnostics in remote areas.”
Using Clarifai’s CV technology and mobile software development kit (SDK), i-Nside was able to leverage CV’s capabilities to build an app that could help doctors diagnose ear diseases found in patients.
When combined with their affordable smartphone attachment, doctors in even the most remote places can take medical-grade pictures of the inner ear with any smartphone and use the app to identify diseases with almost 100% accuracy or diagnose them with almost 90% accuracy, even without the internet.
Due to CV AI being used to build solutions that have made companies more efficient and profitable, we may forget the ways the technology has opened up our world. From the above, however, we can see that thanks to CV AI, the world is becoming a safer, better place.
相關推薦
5 Industries Being Revolutionized by Computer Vision
Because of all the confusion around the technology, it’s easy to miss all the positive impact artificial intelligence (AI) is already having on our world.
5 Ways Computer Vision can Increase E
From discounts to free shipping, businesses are always looking for ways to encourage their customers to buy more. Now, they can add computer vision to that
5 Ways To Remove In-Store Friction With Computer Vision
The retail landscape is rapidly changing as consumers expect more convenience and better service across the entire retail customer journey. Research shows
Solr 6.6.0 ERROR: Port 8983 is already being used by another process.
proc 命令 port img another com other log -a 在目錄D:\work\Solr\solr-6.6.0\bin下打開命令框: 輸入:solr -e dih報錯:ERROR: Port 8983 is already being u
Docker問題: Layer already being pulled by another client. Waiting.什麽原因
mce stack 問題解決 docker targe lan 問題分析 flow stop 問題描述:Layer already being pulled by another client. Waiting. 問題分析:這是 1.8版本的一個bug,會在1.9版本中修復
[學習筆記] CS131 Computer Vision: Foundations and Applications:Lecture 1 課程介紹
rac git mea under https bridge cau found cts 課程大綱:http://vision.stanford.edu/teaching/cs131_fall1718/syllabus.html 課程定位: 課程交叉:
[學習筆記] CS131 Computer Vision: Foundations and Applications:Lecture 2 顏色和數學基礎
rgb 數學 histogram val 顏色 models hist nor 學習 大綱 what is color? The result of interaction between physical light in the environment
[學習筆記] CS131 Computer Vision: Foundations and Applications:Lecture 9 深度學習2
math found deep als fin regress ural nsf -m 深度學習 So far this week Edge detection RANSAC SIFT K-Means Linear classifier Mean-shift PCA/Ei
【Network architecture】Rethinking the Inception Architecture for Computer Vision(inception-v3)論文解析
傳統 tps 聚合 更遠 瓶頸 orm -o 分類 每一個 0. paper link inception-v3 1. Overview ??這篇文章很多“經驗”性的東西,因此會寫的比較細,把文章裏的一些話摘取出來,多學習一下,希望對以後自己設計網絡有幫助。 2. Four
《Inception V3-Rethinking the Inception Architecture for Computer Vision》論文筆記
1. 論文思想 在其它條件都滿足的(資料充足且足夠好)的情況下,增加模型的尺寸以及計算量會帶來實質上的優勢,但是可供計算的資源總是有限的,特別是在移動裝置上,並不能無節制的增加模型的尺寸。例如,在VggNet模型中使用的引數量是AlexNet引數量的三倍,實際取得的效果也是好於Ale
Python計算機視覺深度學習三合一Deep learning for computer vision with Python高清pdf
Deep Learning for Computer Vision with Python Starter Bundle pdf Deep Learning for Computer Vision with Python Practitioner Bundle pdf Deep Learning for
Computer Vision Libraries
libCVD OpenGL Suits Windows Ubuntu 安裝編譯器與基本的函式庫 O
微軟認知服務-Computer Vision API呼叫合集
import java.io.File; import java.io.InputStream; import java.math.BigDecimal; import java.net.URI; import org.apache.http.HttpEntity; import org.apac
computer vision: background
1. computer vision: trying to inverse what we see in one or more images and to reconstruct its properties, such as shape, illumination, and color dist
「Computer Vision」Notes on Hypercolumns
QQ Group: 428014259 Sina Weibo:小鋒子Shawn Tencent E-mail:[email protected] http://blog.csdn.net/dgyuanshaofeng/article/details/83904764 閱讀的
「Computer Vision」Notes on Label Correction
QQ Group: 428014259 Sina Weibo:小鋒子Shawn Tencent E-mail:[email protected] http://blog.csdn.net/dgyuanshaofeng/article/details/83904036 [1]
「Computer Vision」Notes on Deep Feature Pyramid Reconfiguration
QQ Group: 428014259 Sina Weibo:小鋒子Shawn Tencent E-mail:[email protected] http://blog.csdn.net/dgyuanshaofeng/article/details/83834348 [1]
「Computer Vision」Notes on Scale Normalization for Image Pyramids
QQ Group: 428014259 Sina Weibo:小鋒子Shawn Tencent E-mail:[email protected] http://blog.csdn.net/dgyuanshaofeng/article/details/83834327 [1]
「Computer Vision」Notes on Multi-Region CNN
QQ Group: 428014259 Sina Weibo:小鋒子Shawn Tencent E-mail:[email protected] http://blog.csdn.net/dgyuanshaofeng/article/details/83834303 [1]
「Computer Vision」Notes on DeepMultiBox
QQ Group: 428014259 Sina Weibo:小鋒子Shawn Tencent E-mail:[email protected] http://blog.csdn.net/dgyuanshaofeng/article/details/83834290 [1]