Huawei Technologies Co., Limited

Ikomed Technologies, Inc.

Kevin Cannons

Daniel Gelbart

Samuel Victor Lichtenstein

Eran Elizur

Zhan Xu

Mohammad Asiful Hossain

Tahmid Z Chowdhury

Minlong Lu

The invention may be applied to selectively heat a diseased area in the lung while minimizing heating to the healthy area and surrounding tissue. This can be done by exposing the lung to an electromagnetic field causing dielectric or eddy current heating. The invention is particularly useful for treating emphysema as the diseased areas in emphysema patients have reduced blood flow. The diseased area will heat up rapidly while the healthy tissue will be cooled by the blood flow. This is particularly effective for treating emphysema because of the low mass of the lungs and the high blood flow. To avoid heating of surrounding organs the direction of the electromagnetic energy may be switched in a way it always passes through lungs but only intermittently passes through adjacent organs.

System for treating unwanted tissue

Systems, methods, and computer-readable media for identifying a main group of people in an image via social relation recognition. The main group of people is identified within an image by identifying social relationships between people visible in the image. The identification of social relationships is performed by a Social Relation Recognition Network (SRRN) trained using deep learning. The SRRN combines two techniques for group identification, First Glance and Graph Reasoning, and fuses their outputs to generate a prediction of group membership. A group refinement module improves and filters the group membership after identification of an initial main group.

Systems, methods, and media for main group identification in images via social relation recognition

A crowd motion summarization method that provides a rich, real-time description of the crowd's characteristics from a video, such as, speed, orientation, count, spatial locations, and time. A feature tracking module receives each video frame and detects features (feature points) from the video frame. A crowd occupancy detection module receives the video frame and generates a binary crowd occupancy map having human pixel positions which indicate the human location versus non-human location, and generates a total human count of humans detected in the video frame. The feature tracking module generates feature tracking information for only those features contained in the human pixel positions which indicate the human location. In an example, the detected features are Kanade-Lucas-Tomasi (KLT) features. A feature-crowd matching module generates, using the feature tracking information and the total human count: crowd motion data. The method outputs the crowd motion data.

Methods and systems for crowd motion summarization via tracklet based human localization

Growing community of inventors

Vancouver, Canada

Kevin Cannons