Can deep-learning computer vision solve visual problems?
DiCarlo and others previously found that when such deep-learning computer vision systems establish efficient ways to solve visual problems, they end up with artificial circuits that work similarly to the neural circuits that process visual information in our own brains.
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How sophisticated is a computer vision model?
The sophistication of computer vision models depends on the volume and quality of the data it is trained on.
Data annotation requires a human workforce, internally sourced or outsourced, manual annotation is a tedious and sometimes complicated task.
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Vision For NDT: Thermal Imaging Analysis
Thermal cameras were primarily developed for the military purpose, as a night vision tool for surveillance; nowadays with decreased prices, a broader field of applications are opening up.
One such application is augmented non-destructive testing Computer Vision.
The solution detects defects and marks the area of interest where there is a high proba.
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Vision For Quality Inspection: Automating Anomaly Detections
Production quality is of utmost importance and failure is not an option in a fast-paced induductial operating conditions.
Computer Vision-based visual inspectionsolutions have demonstrated clear advantages over conventional methods of human inspections and traditional rule-based machine vision applications.
One of India’s largest electronics manufa.
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Vision For Safety: Ensuring Public and Workplace Safety
Workplaces across the globe are facing challenges presented by COVID-19, cultivating safe organizational culture is more important than ever.
The US federal agency OSHA (Occupational Safety and Health Administration), requires that employers protect employees from workplace hazards that can cause any illness or injury.
New safety protocols and new .
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Vision in Real-Time: The Rise of Edge Computing
Edge computing refers to technology attached to physical machines, it allows for the data to be processed and analyzed where it is collected, as opposed to it being done in the cloud or at a data center.
This is highly useful for industries where network outages are expected.
The advancements in edge computingare solving the problems of network acc.
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Vision on Its Own: Closed Loop Solutions
A closed-loop control system is a system in which the performing action is dependent on the system generated output.
Where we have achieved to implement such systems with ML and IIot for data analytics, implementing a closed-loop on Computer Vision-based systems have been challenging because of model accuracy and reliability issues.
In the last dec.
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Vision on Steroids: Auto-Annotation and Training
The sophistication of computer vision models depends on the volume and quality of the data it is trained on.
Data annotation requires a human workforce, internally sourced or outsourced, manual annotation is a tedious and sometimes complicated task.
It needs specialized workforce training and annotation tools, and also needs to track annotation qua.
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Vision on The Go: Saas Video Analytics Solution
The usual bottleneck of implementing an industry-wide video analytics solution is the hardware upgrade which costs a ton in a conventional surveillance system.
We are witnessing a rise in Video Analytics softwares, which can seamlessly integrate with existing infrastructure and can provide insights on the go.
Softwares are being trained on over 300.
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Vision with Helping Hands: Triangulation with Sensor Data
New advancements are improving the integration of sensor and vision data, through intuitive control interfaces, powerful edge computing and efficient closed-loop information exchanges.
For instance, Video Analytics is unleashing new frontier for automated surveillance cases in Military and Defence.
The ability to automatically detect events and ale.
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What challenges do computer vision engineers face today?
Another challenge that computer vision engineers face nowadays is the sustainable integration of open-source computer vision tools into their applications.
In particular, computer vision solutions constantly rely on both software and hardware evolution, where integrating new technologies becomes a challenging task.
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What is computer vision & why is it important?
Computer vision (sometimes called machine vision) is one of the most exciting applications of artificial intelligence.
Here we look at the five biggest trends in this fast-developing area.
The IEEE International Symposium on Computer Arithmetic (ARITH) is a conference in the area of computer arithmetic.
The symposium was established in 1969, initially as three-year event, then as a
biennial event, and, finally, from 2015 as an annual symposium.
