Here Global B.v.

Verily Life Sciences LLC

William Marks

Anish Mittal

Ritu Kapur

Erin Rainaldi

Lance Jonathan Myers

Maximilien Burq

Triggering information that defines conditions for presenting a virtual clinical exam may be downloaded to a user device. The user device may collect sensor data and use the sensor data to evaluate the conditions. When certain conditions are fulfilled, the user device may present the virtual clinical exam at the user device.

Triggering virtual clinical exams

An approach is provided for automated analysis and classification of quality characteristics associated with captured imagery that may be used in an application such as a map application. The approach includes determining digital data associated with a region of interest in an image. The approach also comprises processing and/or facilitating a processing of the digital data to determine one or more quality attributes associated with the region of interest. The approach further comprises causing, at least in part, a comparison of the one or more quality attributes to one or more criteria. The approach also comprises causing, at least in part, a generation of one or more classifications for the image based, at least in part, on the comparison.

Method and apparatus for providing classification of quality characteristics of images

An approach is provided for automated classification of an image based on the fogging attributes associated with the image. The approach involves processing and/or facilitating a processing of image data associated with at least one image to cause, at least in part, an extraction of one or more fogging attributes from the image data. The approach also involves causing, at least in part, a mapping of the one or more fogging attributes to one or more features of at least one classifier, wherein the at least one classifier is trained based, at least in part, on a co-registration of the one or more features to one or more records of previously made image judgements. The approach further involves causing, at least in part, a classification of the at least one image as either in a fogging-afflicted state or a non-fogging-afflicted state based, at least in part, on the at least one classifier.

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San Francisco, CA, United States of America

William Marks