6Dec

Catheter Navigation System with RL

By R. A. / 06/12/2018 / RSIP Vision Learns / No Comments

The typical catheter navigation system relies on fluoroscopy, which exposes patients to dangerous irradiation. To limit the dose throughout the operation, endoscopic cameras are used to guide catheter near the target site of the procedure. When vessel diameter becomes too small to insert an endos...

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16Oct

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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3Sep

Temporal point process sampling in video

By R. A. / 03/09/2018 / RSIP Vision Learns / No Comments

Object identification and tracking in a sequence of frames (video) consists of sampling of the scene, by e.g raster or uniform scatter, to extract features and compute their descriptors for target objects identification. This raster scanning procedure can by resource intensive, especially if ever...

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20Aug

Automated Defect Inspection Using Deep Learning

By R. A. / 20/08/2018 / RSIP Vision Learns / No Comments

Defect detection during production is a necessary step to ensure product quality. Although manual human inspections are still being employed, automated visual inspection has practically replaced manual labor in almost all major production lines and is ubiquitous in mechanical parts manufacturing,...

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22Jul

Pattern Matching Algorithms

By R. A. / 22/07/2018 / RSIP Vision Learns / No Comments

Pattern matching in computer vision refers to a set of computational techniques which enable the localization of a template pattern in a sample image or signal. Such template pattern can be a specific facial feature, an object of known characteristics or a speech pattern such as a word. Many of t...

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15Jul

Fingerprint Segmentation Using Deep Learning

By R. A. / 15/07/2018 / RSIP Vision Learns / No Comments

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 step towards a successful recognition, that is, comparison against a known database or the extraction of information chara...

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17May

3D surface reconstruction from single depth view

By R. A. / 17/05/2018 / RSIP Vision Learns / No Comments

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 stage in nearly all domains of the industry. Reconstructed 3D surfaces from multiple images appear in applications ranging...

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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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19Feb

Defect Detection in Ceramics

By R. A. / 19/02/2017 / RSIP Vision Learns / No Comments

Quality control in the ceramic industry has lately started to reap the benefits of automation. However, quality control is still performed manually in many factories around the world, as a subset of the production batch is inspected by trained personnel for various visual defects such as cracks, ...

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21Nov

Lanes Detection System

By R. A. / 21/11/2016 / RSIP Vision Learns / No Comments

One of the theoretically simplest applications in automatic driving technologies is traffic lanes detection: however, due to the need of a very robust solution to insure the safety of travelers under any road, weather and light condition, even a simple application presents challenges which need t...

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17Nov

Machine fault detection and classification

By R. A. / 17/11/2016 / RSIP Vision Learns / No Comments

Automatic detection and diagnosis of various types of machine failure is a very interesting precess in industrial applications. With the advancement of sensors and machine intelligence, the reliability of automatic product inspection and fault detection is ever increasing. Monitoring the health o...

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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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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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7Aug

Segmentation and tracking of kidney stones

By R. A. / 07/08/2016 / RSIP Vision Learns / No Comments

An affected anatomical region can be treated in a selective and non-invasive manner by localized and contact-free methods such as high-intensity focused ultrasound. Treatment by selective use of focused beams offers higher patients benefit than non-selective therapy since they spare the healthy t...

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19Jul

Lesion segmentation by random-forest classifiers

By R. A. / 19/07/2016 / RSIP Vision Learns / No Comments

Segmentation of lesions in images, such as those obtained from MRI, ultrasound, CT etc, can be viewed as classifying pixels (or voxels, in the 3-D case) of the image into one or more classes. In the general case, several classes are used, indicating the membership, or probability of each pixel to...

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18Jul

Gastrointestinal lesion detection with machine learning

By R. A. / 18/07/2016 / RSIP Vision Learns / No Comments

Detection of cysts, polyps, or solid tumors is an important first step in diagnosis and clinical decision making. Cancerous gastric lesions and solid tumors now rank as the number 5 for most common cancers worldwide. Endoscopic examination is performed to disclose the lesion’s biophysical p...

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7Mar

Vehicle Localization with Lane Tracking

By R. A. / 07/03/2016 / RSIP Vision Learns / No Comments

Traffic accidents are a major cause of fatalities worldwide. It is estimated that more than 1 million people are killed and 50 million are injured in the world every year as a result of road crashes. These accidents bear heavy economic burden, including hospitalization expenses and loss due to pr...

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6Mar

Pedestrian Detection with Machine Learning

By R. A. / 06/03/2016 / RSIP Vision Learns / No Comments

Safety control and accident prevention systems in cars have gain significant development over the past decade. Advanced Driver Assistance Systems (ADAS) are now commercially available, and quite frequently found pre-installed by car manufactures. The goal of these system is to provide vehicles wi...

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28Feb

3D inspection and crack detection

By R. A. / 28/02/2016 / RSIP Vision Learns / No Comments

Most of the world’s steel is manufactured in a process of continuous (stand) casting, a process introduced in the late 1950s. In this highly efficient process, metal is solidified into a semi-finished product, which is subsequently sent to the finishing mills. The semi-finished product is prone t...

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25Feb

Road signs detection with machine learning

By R. A. / 25/02/2016 / RSIP Vision Learns / No Comments

Precise maps in real time of all the speed sign alerts to be met on the road are very popular today. RSIP Vision is one of the companies driving the use of image processing technologies in this field. Accordingly, we have developed a traffic signs detection and classification software, the main g...

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