Our AI Impact

 for the health of people

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 Our AI Impact

 for the health of planet

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 Our AI Impact

 for the health of business

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FOR THE HEALTH OF PEOPLE: EQUITY
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“The work [with Synaptiq] is unprecedented in its scale and potential impact,” Mortenson Center’s Managing Director Laura MacDonald MacDonald said. “It ties together our center’s strengths in impact evaluation and sensor deployment to generate evidence that informs development tools, policy, and practice.” 
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    ⇲ Implement & Scale
    DATA STRATEGY
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    A startup in digital health trained a risk model to open up a robust, precise, and scalable processing pipeline so providers could move faster, and patients could move with confidence after spinal surgery. 
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      PREDICTIVE ANALYTICS
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      Thwart errors, relieve in-take form exhaustion, and build a more accurate data picture for patients in chronic pain? Those who prefer the natural albeit comprehensive path to health and wellness said: sign me up. 
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        MACHINE VISION
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        Using a dynamic machine vision solution for detecting plaques in the carotid artery and providing care teams with rapid answers, saves lives with early disease detection and monitoring. 
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          INTELLIGENT AUTOMATION
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          This global law firm needed to be fast, adaptive, and provide unrivaled client service under pressure, intelligent automation did just that plus it made time for what matters most: meaningful human interactions. 
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            Mushrooms, Goats, and Machine Learning: What do they all have in common? You may never know unless you get started exploring the fundamentals of Machine Learning with Dr. Tim Oates, Synaptiq's Chief Data Scientist. You can read and visualize his new book in Python, tinker with inputs, and practice machine learning techniques for free. 

            Start Chapter 1 Now ⇢ 

             

              How Should My Company Prioritize AIQ™ Capabilities?

               

                 

                 

                 

                Start With Your AIQ Score

                  3 min read

                  Computer Vision vs. Machine Vision: What's the Difference?

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                  You’re likely to encounter “computer vision” (CV) and “machine vision” (MV) in relation to image processing. Although these terms are often used interchangeably, MV actually refers to the application of CV.

                  What You Need to Know

                  Computer vision refers to the automated extraction of data (information) from visual inputs. It’s a sub-discipline of artificial intelligence (AI): a sub-discipline of computer science concerned with developing artificial systems to perform tasks that would typically require human intelligence. Computer vision engineers use AI to derive insights from videos, images, et cetera. Applications include image classification, captioning, and enhancement; object detection and tracking; and text extraction.

                  Machine vision refers to the application of computer vision, especially in professional settings. An MV system combines CV software with hardware such as industrial equipment, allowing the latter to analyze and act on visual inputs. Applications include product inspection, quality management, predictive analytics, and facial recognition.

                  Frequently Asked Questions

                  What are real-world examples of machine vision and computer vision?

                  One well-known MV solution is Apple’s “Face ID,” which employs facial recognition. Facial recognition systems use CV software to identify individuals by extracting and analyzing their facial features. This enables “Face ID” and other methods of biometric authentication: “a cybersecurity process that verifies a user's identity using their unique biological characteristics.” [1] Another example is Tesla Vision, the complex CV software behind Tesla’s trademark self-driving technology. [2]

                  How much does computer vision software or a machine vision system cost?

                  It depends on the scope of your project. Synaptiq has helped dozens of organizations develop accurate AI budgets. Clients come to us because the stakes are high, and there is no one-size-fits-all answer. We offer a variety of consulting services in this area, including low-cost, low-commitment feasibility studies to help organizations like yours gauge the scope of their project.

                  Contact us to learn more and book your first call — free.

                  Where can I learn more about computer vision and machine vision?

                  If you’re interested in developing CV software yourself, we recommend PyImageSearch. They cover beginner to expert-level skills, from installing OpenCV (an open-source CV software library) to solving your own projects.

                  If you’re interested in real-world examples of CV and MV, see our case studies:

                   

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                  About Synaptiq

                  Synaptiq is an AI and data science consultancy based in Portland, Oregon. We collaborate with our clients to develop human-centered products and solutions. We uphold a strong commitment to ethics and innovation. 

                  Contact us if you have a problem to solve, a process to refine, or a question to ask.

                  You can learn more about our story through our past projects, blog, or podcast

                  Additional Reading:

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