Intrusion Detection with Deep Learning
Detecting physical and virtual intrusions is a key process in ensuring information and property security. Physical intrusion detection refers to all attempts at break-ins to a building, warehouse, or other perimeters by an unauthorized person, where access is granted to only limited personnel. Ba...
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Chest CT Scan Analysis with Deep Learning
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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Automated Defect Inspection Using Deep Learning
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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Deep Learning in Cardiology
1.1 Segmentation tasks [10] suggest a new fully convolutional network architecture for the task of cardiovascular MRI segmentation. The architecture is based on the idea of network blocks in which each layer is densely connected with auxiliary side paths (skip connections) to all the following la...
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Deep Learning in Pulmonology
Deep learning has been successfully applied in various applications in pulmonary imaging, including CT registration, airway mapping, real time catheter navigation, and pulmonary nodule detection. Some of these applications are still in ongoing development, and here we review few of the most recen...
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Deep Learning in Ophthalmology
Recent works suggest novel deep learning tools for detection, segmentation and characterization of eye disorders. Accurate segmentation of retinal fundus lesions and anomalies in imaging data is an important technical step for early detection and treatment of common eye disorders, and a central a...
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Deep Learning in Brain Imaging
In this article we discuss several recent leading works about Deep Learning in brain imaging and brain microscopy. We organize the works in subsections according to the general algorithmic tasks: segmentation, registration, classification, image enhancement or other tasks. The categories are not ...
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Wafer Macro Defects Detection and Classification
Defect detection is an integral part of wafer (chip) fabrication process. It enables defect detection and classification along the process to increase the fab yield (amount of good chips out of total wafers processed). Every detected defect is handled as an indicator of some process malfunction. ...
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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 exited hydrogen atoms are collected to form an image of an organ or their entire body. The size of MRI machines makes them practically im...
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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 large part, to the rapid development of non-destructive inspection vision systems and their integration in the manufacturing proces...
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Object Detection Methods for Robots
Object detection and classification are major challenges for robotic modules. Navigation, Pick and Place and additional robotics activities are based on the ability to recognize object. Recent years has provided a great progress in object detection mainly due to machine learning methods that beca...
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Machine Vision Robots for Semiconductors
Robots have been used in the semiconductor industry for a long time. The functions of robots for semiconductors manufacturing operations are spawn over a wide range of tasks, from mechanical tasks up to intelligent tasks. The latter use machine vision. Defect detection in semiconductors manufactu...
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Robots using Machine Vision in Agriculture
Robots are widely used today in agriculture tasks. Many of these tasks require machine vision algorithms to operate successfully. The robots and their machine vision algorithms change form to best suit their function, starting from fields plowing, seeds planting, weeds handling, growth monitoring...
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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, to minimize the use of resources while maximizing yield. Precision agriculture utilizes advanced hardwa...
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Biometric Detection and Measurement
Eyeglasses have been with us since the 13th century, although mass production and affordability to commoner (aside from clerics, scholars and wealthy people) has begun around the onset of the industrial revolution. Once symbolizing old age and degradation, eyeglasses have integrated our life and ...
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Video tracking of animal behavior
Animals display a diverse set of behavior, not always well interpreted by humans: some of these behavioral patterns disclose animals’ intensions, needs, and distresses. Thousands of years of animal farming have enabled us to interpret a subset of animal behavior; yet, a large spectrum still remai...
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Algorithms for Autonomous Driving
The transportation revolution coming with autonomous cars has already started, involving challenges that require proper handling of advanced technologies and algorithms: deep learning, to name one. . . Autonomous Driving is classified according to 5 Levels, all higher than Level Zero, where no au...
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Cell Classification software
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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Degenerative Diseases Detection in the Eye
Modern imaging knows how to capture an image to see through the eye tissue transparency and inspect retina, vasculature and neural tissue: this phenomenon is unique and it is made possible by the fact that the retina is an extension of the central nervous system (CNS), connected with the optic ne...
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Object tracking in videos
Object tracking in videos is a classical computer vision problem. It consists of not only detecting the object in a scene but also recognizing the object in each and every frame, so as to distinguish it from other objects, both static and dynamic. Many tracking algorithms have been proposed in th...
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