Chest CT Scan Analysis with Deep Learning

By R. A. / 16/10/2018 / RSIP Vision Learns / No Comments

Chest radiography, with modalities such as X-Ray and CT, is now the common practice for the detection and analysis of the progression of lung tumors, tuberculosis and other pulmonary abnormalities. To date, most analysis are done by expert radiographers, who analyze resulting scans and estimate p...

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15Oct

Object Tracking at High fps

By R. A. / 15/10/2018 / RSIP Vision Learns / No Comments

Object tracking in video sequences is a classical challenge in computer vision, which finds applications in nearly all domains of the industry: from assembly line automation, security, traffic control, automatic driving assistance systems and agriculture. Presently state of the art algorithms per...

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17Jul

Extracting Features for Fingerprint Recognition and Matching

By R. A. / 17/07/2018 / RSIP Vision Learns / No Comments

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, whorls, and twists, enables to uniquely identify individuals (as far as we know): datasets of known fingerprints hav...

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14Jan

Machine Vision in industrial applications

By R. A. / 14/01/2018 / RSIP Vision Learns / No Comments

Robots working in industrial applications need visual feedback. This is used to navigate, identify parts, collaborate with humans and fuse visual information with other sensors to enhance their location information. This is the reason for the use of machine vision in industrial applications. Robo...

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13Jun

Cell Classification software

By R. A. / 13/06/2017 / RSIP Vision Learns / No Comments

One ml of human blood contains roughly 5 million red blood cells. This huge quantity is only a fraction of what is found in one ml of blood, which contains roughly 60% fluid (plasma) and the remaining white cells, red blood cells and platelets. The composition of blood is examined routinely in ho...

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5Jun

Three-dimensional reconstruction of a deformable object

By R. A. / 05/06/2017 / RSIP Vision Learns / No Comments

Reconstruction of the three-dimensional surface of an object based on single view 2-D sequence of images is a highly challenging task. Challenges stem in part from the construction of a template representing the object, or more formally, incorporating knowledge to restrict the shape space. The po...

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8Mar

ROP: Retinopathy of Prematurity

By R. A. / 08/03/2017 / RSIP Vision Learns / No Comments

Retinopathy of prematurity (ROP) is a leading cause of blindness in infants. ROP (or Terry syndrome) is a disease of the eye affecting prematurely-born, low birthweight infants having received intensive neonatal care which includes oxygen therapy. Oxygen toxicity causes abnormal growth of retinal...

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5Feb

OCR Check Scanner

By R. A. / 05/02/2017 / RSIP Vision Learns / No Comments

Digitalization of money transfer is a must in the current state of banking operations. Clients have various ways to perform transactions, such as credit, wiring money, and so forth. However, the banking systems and many businesses accepts checks as a formal means of money transfer. Checks still a...

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15Dec

Statistical pattern discovery in big data

By R. A. / 15/12/2016 / RSIP Vision Learns / No Comments

The explosion of data collection techniques and resources is a known phenomenon of the current day and age. Human analysis of such large datasets is largely infeasible and the vast amount of information can only be dealt systematically and efficiently by algorithmic means. The so called ‘big data...

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7Sep

Type 2 interval fuzzy sets in pattern classification

By R. A. / 07/09/2016 / RSIP Vision Learns / No Comments

In search for a pattern in an image, a video or a signal, one has to consider several sources of bias, noise and uncertainties. Such uncertainties are the result of acquisition of natural signals such as outdoors images in non-sterile and poorly lit conditions, possibly containing smear, blurs, a...

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22Aug

Image Categorization and Retrieval with Fisher Vectors

By R. A. / 22/08/2016 / RSIP Vision Learns / No Comments

Testing a set of images for similarity has long been a task of image processing computer vision and machine learning. The plethora of tools and techniques suggested to treat such task stems from the ever expanding definition of similarity. For some applications, similarity in color might suffice;...

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10Aug

Image Features for Classification

By R. A. / 10/08/2016 / RSIP Vision Learns / No Comments

Classification problems in image and signal analysis require, on the algorithmic side, to take into account complex information embedded in the data. Images might contain many thousands of pixel values in several color channels; their correlation and relationship characterizes the class and enabl...

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31Mar

Automatic semantic tagging of images

By R. A. / 31/03/2016 / RSIP Vision Learns / No Comments

Image and object recommender systems have been developed along with the Internet itself. The recommender systems are constructed to assist user’s navigation through the variety of content and products (videos, images or objects sold on a website) by correlating user preferences with the item’s ch...

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17Feb

Live cells tracking

By R. A. / 17/02/2016 / RSIP Vision Learns / No Comments

Studying the behavior of cells in-vitro is one of the most fundamental research tools in biology. Studies conducted under the microscope improve our understanding of cell-cell interaction, motility, and reaction to different biochemical conditions. In addition, cell counting and sorting, which ar...

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23Oct

Quantitative Coronary Analysis

By Felicity / 23/10/2015 / RSIP Vision Learns / No Comments

Quantitative Coronary Analysis Quantitative Coronary Analysis (QCA) refers to the set of methods used to measure the diameter of arteries. The set of tools and algorithms for QCA have been developed for the purpose of lesion and stenosis detection and analysis, and promote rational clinical decis...

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27Jul

Defining the Borders within Computer Vision

By Felicity / 27/07/2015 / RSIP Vision Learns / 2 Comments

What’s the Difference between Computer Vision, Image Processing and Machine Learning?   Computer vision, image processing, signal processing, machine learning – you’ve heard the terms but what’s the difference between them? Each of these fields is based on the input o...

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25Jan

Phenotyping

By Felicity / 25/01/2015 / / No Comments

RSIP Vision's high-throughput phenotyping systems can measure and analyze quantitative crop traits related to yield, growth and adaptation to the environment.

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