Traditionally, computer vision applications have relied on highly specialized algorithms painstakingly designed for each specific application and use case. This meant that designing for computer vision was hard, and this significantly slowed the adoption of vision-based applications. Additionally, this made new applications very expensive and time consuming.However, there has been a democratization of computer vision. By that we mean it’s becoming much easier to develop computer vision-based algorithms, systems and applications, as well as to deploy these solutions at scale – enabling many more developers and organizations to incorporate vision into their systems.Deep learning is one of the drivers of this trend. Because of the generality of deep learning algorithms, there’s less of a need to develop specialized algorithms. Instead, developer focus can shift to selecting among available algorithms, and then to obtaining the necessary quantities of training data.Deep neural networks (DNNs) have transformed computer vision, delivering superior results on tasks such as recognizing objects, localizing objects within a frame and determining which pixels belong to which object. Even problems previously considered solved with conventional techniques are now finding better solutions using deep learning techniques.As a result, computer vision developers are increasingly adopting deep learning techniques. In the Alliance’s most recent survey, 59% of vision system developers are already using DNNs (an increase from 34% two years ago). Another 28% are planning to use DNNs for visual intelligence in the near future.Another critical factor in simplifying computer vision development and deployment is the rise of cloud computing and much better development tools. For example, rather than spending days or weeks installing and configuring development tools, today engineers can get instant access to pre-configured development environments in the cloud. Likewise, when large amounts of compute power are required to train or validate a neural network algorithm, this compute power can be quickly and economically obtained in the cloud.Cloud computing offers an easy path for initial deployment of many vision-based systems, even in cases where ultimately developers will switch to edge-based computing to reduce costs. Our most recent survey found that 75% of respondents using deep neural networks for visual understanding in their products deploy those neural networks at the edge, while 42% use the cloud. These figures total to more than 100% because some survey respondents use both approaches.The world of practical computer vision is changing very fast – opening up many exciting technical and business opportunities. You can learn about the latest developments in computer vision at the Embedded Vision Summit, May 20-23, 2019, in Santa Clara, California. The event attracts a global audience of more than one thousand people who are developing and using computer vision technology. — Jeff Bier is the founder if the Embedded Vision Alliance. >> This article was originally published on our sister site, EE Times: “Tools, Algorithms Drive Embedded Vision.” For more articles related to embedded vision, see: – Embedded vision builds on specialized co-processors – Open-source software meets broad needs of robot-vision developers – Computer vision for the masses: bringing computer vision to the open web platform Can be deployed at low cost and with low power consumption Is usable by non-specialists Since we started the Embedded Vision Alliance in 2011, there has been an unprecedented growth in investment, innovation, and use of practical vision technology across a broad range of markets. To help understand technology choices and trends, the Embedded Vision Alliance conducts an annual survey of product developers.In the most recent iteration of this survey, completed in November 2018, 93% of respondents reported that they expect an increase in their organization’s vision-related activity over the coming year (61% expect a large increase). This increase would not be possible without extensive work on new algorithms and development tools to speed adoption of vision-based systems.Three fundamental factors are driving the proliferation of visual perception. It increasingly Share this:TwitterFacebookLinkedInMoreRedditTumblrPinterestWhatsAppSkypePocketTelegram Leave a Reply Cancel reply You must Register or Login to post a comment. This site uses Akismet to reduce spam. Learn how your comment data is processed. Continue Reading Previous Syslogic: rugged computers and HMI systems for construction machineryNext How smart sensors enhance ADAS designs Works well enough for diverse, real-world applications
zoom Shanghai-based Wison Offshore & Marine has received Approval in Principle (AIP) from Bureau Veritas for its newly-developed large-scale Floating LNG Storage and Regasification Terminal.Featuring scalable storage capacity up to equivalent size of a Q-Max, this is the first large-scale FSRU barge design that has been granted AIP by a classification society, according to Wison.The company added that the full-size floating LNG terminal solution offers an economical alternative to the conventional LNG regasification vessels (LNG RV) especially for markets with long-term demand.Furthermore, the barge design lowers initial capital investments, up to 20 percent compared with LNG RV of equivalent size, as well as O&M costs, while enabling uninterrupted service throughout project lifecycle.“Wison large-scale FSRU is a fit-for-purpose facility designed with practical operation considerations. It features scalable storage capacity from 150,000 m³ to 265,000 m³ and a base case design of 750 mmscfd regasification capacity expandable to fit project needs,” David W. Chen, Senior Solution Manager at Wison Offshore & Marine, said.“Designed for near-shore/at shore application, the FSRU can also be deployed offshore with a single point mooring system,” Chen added.
zoom Port operator Associated British Ports expects 2018 to be another record-breaking year at the Port of Southampton, following on from the success of 2017.Last year saw the largest vessels in the world coming to Southampton — such as the 20,568 TEU Milan Maersk — and more than one million containers handled by the port.This year will see even larger mega-ships visiting, according to the port operator. “This is set to be another important year for the port. Across automotive, cruise, containers and bulks we are anticipating another record-breaking year,” Alastair Welch, ABP Southampton Director, commented, adding that the port operator will be spending an average of GBP 75,000 (USD 101,000) a day on the port’s infrastructure.The Port of Southampton is the UK’s number one export port, handling GBP 40 billion of exports every year. The total trade handled by the port is worth some GBP 75 billion.The port is also home to the UK’s second largest container terminal and each year handles around one million containers.Over the past five years, GBP 280 million was invested in port facilities, including more than GBP 50 million in new vehicle export facilities. The port recently opened its newest vehicle terminal.In addition, the port has over 500 cruise calls each year bringing 2 million passengers. It also hosts some 3 million ferry passengers travelling to and from the Isle of Wight.