Panton, Inc.

Mingyang Zhu

Saishi Frank Li

Yang Liu

Jack Dong Wang

Bo Chen

Guoyan Cao

Yong Chen

Methods for aerial image processing and object identification using an electronic computing device are presented, the methods including: causing the electronic computing device to build a deep learning model; receiving actual aerial image data; applying the deep learning model to the actual aerial image data to identify areas of interest; post-processing the areas of interest; and returning a number of classified objects corresponding with the areas of interest to a user. In some embodiments, methods further include: applying global positioning system (GPS) mapping to the number of classified objects with respect to the actual aerial image data.

Aerial image processing

Methods for analyzing a chart using an electronic computing device are presented, the methods including: causing the electronic computing device to receive a chart image corresponding with the chart, the chart image having recorded chart data; analyzing the recorded chart data, where the analyzing returns at least measurement values corresponding with the recorded chart data; and returning volumetric results of the processing to a user. In some embodiments, the recorded chart data corresponds with data selected from the group consisting of: temperature data, differential pressure data, and static pressure data. In some embodiments, the chart corresponds with a chart integration device or a chart recorder. In some embodiments, methods further include: capturing the chart image with a mobile image capture device.

Methods for automated chart analysis

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Missouri City, TX, United States of America

Mingyang Zhu