Most organisations that must maintain a physical network have similar challenges in keeping their networks safe and operational. Whether you run an energy distribution network, a telecommunications network, or a road, rail or canal network, you need to keep it clear of obstructions. And one of the biggest culprits tends
Tag: computer vision
In my previous post, I shared how I’ve been working on a fascinating project with one of the world's largest pharmaceutical companies. The company is applying SAS Viya computer vision capabilities to an advanced medical device to help identify potential quality issues on the production line. By providing 100% visual
Over the past few months, I’ve been working on a fascinating project with one of the world's largest pharmaceutical companies to apply SAS Viya computer vision to help identify potential quality issues on the production line as part of the validated inspection process. As I know the application of these
Computer vision can augment radiologists and make the image interpretation process cheaper, faster and more accurate. The ultimate goal is to achieve a better patient outcome facilitated by the use of computer vision.
How can a solar farm ensure peak energy production? And what factors can be adjusted to optimize production throughout the day, the week and season-by-season? These are just some of the questions that a team of data scientists have asked and answered about the SAS solar farm using data, drones
At the #AISummit early this summer, I was interested to see that one of the most popular demos on the SAS stand was of object detection. A camera was detecting the nature of an object waved in front of it and tracking it moving through the livestream. This was a
This series of videos spotlights a very powerful API that lets you use Python while also having access to the power of SAS Deep Learning.
Some people still associate artificial intelligence (AI) with robots taking over the world. There's a lot of hype around self-driving cars and personal robots. However, there are far more realistic and beneficial examples of AI in everyday life. AI is the science of training systems to emulate human tasks through
Everyone is talking about artificial intelligence. Unfortunately, a lot of what you hear about AI in the movies and on the TV is sensationalized for entertainment. Indeed, AI is overhyped. But AI is also real and powerful. Consider this: engineers worked for years on hand-crafted models for object detection, facial
I just spent four inspiring days talking to customers about the many ways they are putting analytics into action in their organizations. From computer vision models that interpret medical images to natural language processing models that analyze supply chain records, SAS users are doing ground-breaking work with analytics and AI.
Artificial intelligence is the attention-grabbing, overhyped, shiny object that every organization is searching to make use of. Yes, it is overhyped, but it’s also very real and very powerful. “We do not want to add to the hype. We do not want to add to the confusion. We want to
According to the World Cancer Research Fund, Breast cancer is one of the most common cancers worldwide, with 12.3% of new cancer patients in 2018 suffering from breast cancer. Early detection can significantly improve treatment value, however, the interpretation of cancer images heavily depends on the experience of doctors and technicians. The
Computer vision is one of the most sought-after artificial intelligence (AI) applications today, finding a wide variety of use cases in image recognition, object detection, biomedical assessment, and more. SAS supports a diverse set of AI and deep learning capabilities that can be used in many of these applications. One
Artificial intelligence (AI) is a natural evolution of analytics. Over the years, we have seen AI add learning and automation capabilities to the predictive and prescriptive jobs of analytics. We have been building AI systems for decades, but a few things have changed to make today’s AI systems more powerful.
This is the fifth and final post in my series of posts about the deep learning model I developed to detect tumors in 3D CT scans of livers. My last post talked about visualizing the results of the computer vision project. This post will cover model accuracy and the final
I look forward to Pi Day every year at SAS because it's a day of celebration including yummy pies and challenging games that challenge you to recall the digits after the decimal point in Pi. Plus you get to wear Pi t-shirts (I have about seven). Today, though we are going to talk about DLPy which sounds like Pi and
This is the fourth post in my series about a computer vision project I worked on to identify liver tumors in CT scans. In my previous post, I had taken a break from my deep learning model to work on data management and data labeling. Now, I’ll return to the
This is the third post describing a computer vision project I worked on at SAS to identify liver tumors in CT scans. In my previous post I talked about testing different models and hyperparameters for the models. Today, I’ll talk about data processing for image data. If you need to
This is the second post in my series about a computer vision project I worked on at SAS. In my previous post, I talked about my initial research and excitement for the project. In this post, I’ll talk about how I refined my goals and got started with the project
As one of SAS' newest systems engineers, recently joining the Americas Artificial Intelligence Team, I’m incredibly excited to gain expertise in artificial intelligence and machine learning. I also look forward to applying my knowledge to enable others to leverage the advanced technologies that SAS offers. However, as a recent graduate
Recently, I was given an amazing opportunity to work on a project in biomedical image analytics in collaboration with a large university medical center. The goal of the project was to develop a computer vision system that identifies tumors in CT scans of livers. I have always loved applying technology
It suddenly seems as if artificial intelligence (AI) is all around us. It is already having a huge impact in a wide range of sectors, including health care. We are now starting to see it move into the manufacturing sector as an important part of Industry 4.0, the digitisation of
A picture paints a thousand words – to humans, at least. Traditionally, however, images have made little sense to computers, which have no conception of the meaning behind the strings of code that make up a digital image. Of course, some computers have long had the ability to identify and
What is object detection? Object detection, a subset of computer vision, is an automated method for locating interesting objects in an image with respect to the background. For example, Figure 1 shows two images with objects in the foreground. There is a bird in the left image, while there is a dog
Deep learning has taken off because organizations of all sizes are capturing a greater variety of data and can mine bigger data, including unstructured data. It’s not just large companies like Amazon, SAS and Google that have access to big data. It’s everywhere. Deep learning needs big data, and now
Like most men in the world, shopping (especially shopping for clothes) is an unpleasant experience for me, as I really feel like my time could be much better utilised. I make it a personal mission to get in and out in minimal time. So, I wonder to myself, “Could AI
Image recognition is a hot and hyped topic in machine learning, artificial intelligence and other technology circles. Computer vision technology is essential for realizing advancements like driverless cars, face recognition, medical outcomes predictions, and a host of other breakthrough innovations. Amidst the hype, organizations large and small are trying to understand the