An MRI apparatus includes an imaging data acquiring unit and a blood flow information generating unit. The imaging data acquiring unit acquires imaging data from an imaging region including myocardium, without using a contrast medium, by applying a spatial selective excitation pulse to a region including at least a part of an ascending aorta for distinguishably displaying inflowing blood flowing into the imaging region. The blood flow information generating unit generates blood flow image data based on the imaging data.

Magnetic resonance imaging apparatus and magnetic resonance imaging method

Improved systems and methods for automated machine-learning, zero-day malware detection. Embodiments include a method for improved zero-day malware detection that receives a set of training files which are each known to be either malign or benign, partitions the set of training files into a plurality of categories, and trains category-specific classifiers that distinguish between malign and benign files in a category of files. The training may include selecting one of the plurality of categories of training files, identifying features present in the training files in the selected category of training files, evaluating the identified features to determine the identified features most effective at distinguishing between malign and benign files, and building a category-specific classifier based on the evaluated features. Embodiments also include by a system and computer-readable medium with instructions for executing the above method.

System and method for automated machine-learning, zero-day malware detection

An embodiment of the present invention includes a search technique for image query. A region of interest (ROI) containing an image in a scene of a displayed content is captured. The ROI is analyzed locally or remotely to search for related content associated with the image. The related content is received.

Content image search

A system and for providing reference documents as a suggestion for classifying uncoded documents is provided. A set of reference electronically stored information items, each associated with a classification code, is designated. One or more of the reference electronically stored information items is combined with a set of uncoded electronically stored information items. Clusters of the uncoded electronically stored information items and the one or more reference electronically stored information items are generated. Relationships between the uncoded electronically stored information items and the one or more reference electronically stored information items in at least one cluster are visually depicted as suggestions for classifying the uncoded electronically stored information items in that cluster.

System and method for displaying relationships between electronically stored information to provide classification suggestions via inclusion

A method is provided using a system mounted in a vehicle. The system includes a rear-viewing camera and a processor attached to the rear-viewing camera. When the driver shifts the vehicle into reverse gear, and while the vehicle is still stationary, image frames from the immediate vicinity behind the vehicle are captured. The immediate vicinity behind the vehicle is in a field of view of the rear-viewing camera. The image frames are processed and thereby the object is detected which if present in the immediate vicinity behind the vehicle would obstruct the motion of the vehicle. The processing is preferably performed in parallel for a plurality of classes of obstructing objects using a single image frame of the image frames.

Rear obstruction detection

A color-based imaging system and method for the detection and classification of insects and other arthropods are described, including devices for counting arthropods and providing taxonomic capabilities useful for pest-management. Some embodiments include an image sensor (for example, a digital color camera, scanner or a video camera) with optional illumination that communicates with a computer system. Some embodiments include a color scanner connected to a computer. Sampled arthropods are put on a scanner to be counted and identified. The computer captures images from the scanner, adjusts scanner settings, and processes the acquired images to detect and identify the arthropods. Other embodiments include a trapping device and a digital camera connected by cable or wireless communications to the computer. Some devices include a processor to do the detection and identification in the field, or the field system can send the images to a centralized host computer for detection and identification.

Fernando Agudelo-Silva

Papers

Method and system for detecting and classifying objects in images, such as insects and other arthropods

System and method for detecting and classifying objects in images, such as insects and other arthropods

System and method for identifying arthropods in color-digital image information

Method and system for identifying plant life parameters in color-digital image information