Classification and Segmentation of Dendritic Cells
Dry eye disease (DED) is one of the most common ophthalmic disorders. Inflammation of the ocular surface is controlled by corneal antigen-presenting cells called dendritic
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Extracting Features for Fingerprint Recognition and Matching
Fingerprint matching is used extensively in biometric identity verification for purposes ranging from forensic to recreational. The set of geometrical patterns, such as the ridges,
Fingerprint Segmentation Using Deep Learning
Automatic fingerprint recognition systems are based on the extraction of features from scanned fingerprint image. A successful preprocessing of the scan is an important first
Magnetic Resonance Imaging software
Magnetic resonance imaging is a ubiquitous clinical imaging modality, in which patients are placed in a device inducing a magnetic field, and the relaxation of
Industrial Vision Systems
During the past few decades, industrial automation of manufacturing processes has taken a great leap forward. Specifically, the increased quality of yield is due, in
Intracranial Hemorrhage and Edema Segmentation
An intracranial hemorrhage (ICH) is a condition in which a blood vessel erupts inside the brain, causing internal bleeding. If not treated correctly and immediately,
3D surface reconstruction from single depth view
The advances in the manufacturing of depth sensors and camera technologies, such as LIDAR and RealSense cameras, have brought three-dimensional (3D) applications to the front
3D Cardiac MRI automatic segmentation
3D cardiac segmentation from MRI is a precious tool in the hand of the physician to assess pathologies and treatment. RSIP Vision employ Artificial Intelligence techniques for cardiology in order to perform 3D automatic cardiac segmentation. Deep Learning and Convolutional Neural Networks are called in to achieve state-of-the-art accuracy in the fastest time. This article and the accompanying video explain the challenges presented by this task and the way our algorithms provide a world-class solution.
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Computer-Assisted Joint Replacement (hip and knee)
Pathologies in the joint regions are common especially among elderly patients. They are caused, in many cases, by wear and tear of the cartilage layer
Robots in Medical Applications
Machine Vision and AI for orthopedic surgery are extensively used in solutions enabling robotic surgical procedures and other medical applications. The robot’s hand being more precise than the surgeon, more and more surgeries are performed by properly equipped surgical robots. Besides the details of medical robotics applications, this article discusses also other medical systems, in particular Virtual Reality in medicine, by which RSIP Vision makes it possible to develop a simulator for complex and risky surgeries like brain surgeries.
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Robots in Medical Applications
Machine Vision and AI for orthopedic surgery are extensively used in solutions enabling robotic surgical procedures and other medical applications. The robot’s hand being more precise than the surgeon, more and more surgeries are performed by properly equipped surgical robots. Besides the details of medical robotics applications, this article discusses also other medical systems, in particular Virtual Reality in medicine, by which RSIP Vision makes it possible to develop a simulator for complex and risky surgeries like brain surgeries.
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OCR for robots
Robotic tasks may involve reading and understanding written text. When conditions are optimal, camera mounted on robots allow them to interpret text without major obstacles: but oftentimes, this OCR task for robots needs to overcome difficulties, be these due to the position and type of the camera, lighting conditions, the quality of written characters, the shape of the object bearing the text or else. RSIP Vision engineers are experts also in this branch of OCR and can recommend the best solution for your project.
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Robots Using Machine Vision in Retail
Here are practical examples of robots using Machine Vision techniques in retail applications and tasks, going from picking, sorting and packaging activities within a distribution warehouse to store inventory management, customer service and other robotic automation tasks. This articles by RSIP Vision hints also at future version of robots, directly servicing customers in retail shops.
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Machine Vision in industrial applications
Robots working in industrial applications perform many valuable tasks: from inspection to quality control, from assembling to locating/transporting parts. These tasks need highly accurate visual feedback: the robot is conveniently equipped with a camera as needed by the application. Machine vision systems operating in the industry can be of different kinds and must find solution to different challenges.
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Machine Vision for Robotics
This article explains how different types of cameras provide mechanical support to robots by helping them navigate in the real world. Besides that, robots serving in different fields of activity require different skills. As a result, you will read here the different ways by which Machine Vision algorithms power robots in the main industries and markets, each according to their desired tasks.
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Object Detection Methods for Robots
Robots need to recognize objects, if we want them to perform their activity. To solve this challenge, they take advantage of object detection and classification algorithms which give them the ability to be efficient and practical in the recognition tasks. Machine learning software enable robots to detect all instances of an object. This article details the different classes of object detection methods for robots, including the most sophisticated ones, based on Convolutional Neural Networks.
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Machine Vision Robots for Semiconductors
Machine vision algorithms are also used to operate robots in the high-precision semiconductor industry. Robots perform these intelligent tasks supported by machine vision software: several methods are currently used to detect defects and classify them, with important economies in both time and money. Robots in the semiconductor industry too can take advantage of deep learning techniques: their main benefit is the dramatic improvement in the defect classification abilities of the robotic devices.
Robots using Machine Vision in Agriculture
Among the many tasks performed by robots in agriculture, a large part is activated by machine vision algorithms. A very partial list of these tasks would include fields plowing, seeds planting, weeds handling, monitoring of produce growth (be it via ground-based robots or by flying robotic UAVs), fruits and vegetables picking, as well as sorting and grading of produce. This article gives a panoramic view of what our algorithms for robotics can do for your project in agriculture, including robots using Deep Learning in agriculture.
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Image processing for Precision Agriculture
Precision agriculture describes a collection of engineering methods aimed at providing a rationale and operative management plan for farms, forests, vineyards, and other agricultural endeavors,
Automatic Object Recognition Algorithm
Automatic object recognition is a highly challenging task in computer vision. These challenges can be caused by many factors reducing the recognition rate of a
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