Abstract: A method includes classifying, via a computational model, images of a source image stream as valid images or invalid images based on whether the images include biological tissue or a surgical tool; and generating a condensed image stream that includes the valid images. Another method includes classifying input images as valid images or invalid images using: a clustering algorithm that classifies each of the input images into either a first group or a second group and using labels that indicate whether the input images include a surgical tool. The method also includes training a computational model to identify the valid images based on whether the valid images include biological tissue or a surgical tool, or whether the valid images have at least a threshold level of clarity.

Abstract: A novel nonlinear method for area-wide near surface air temperature precision retrieval is described. The steps include: First, construct the 1st sub-model modelVEC1 to the f-th sub-model modelVECf. Establish and normalize raw data vectors of each gridded pixel sBlkVEC in the targeted area. Calculate the retrieved full maps (surfTf) of near surface air temperatures using each sub-model. Then, identify abnormal samples and define their near-range regions in surfTf Apply a selective arithmetic mean (SAM) approach to achieve precision temperature map surfT. And finally apply further modification to the pixels of surfT where pixlf?badsurfT?f is true to all f=1, 2, 3, . . . . Using the super nonlinear algorithm, this invention provides a solution of retrieving near surface air temperature based on combinations of various factors (information fusion) to achieve satisfied prediction errors, which are independent of cloud levels and topographic characteristics.

Abstract: A novel nonlinear method for area-wide near surface air temperature precision retrieval is described. The steps include: First, construct the 1st sub-model modelVEC1 to the f-th sub-model modelVECf. Establish and normalize raw data vectors of each gridded pixel sBlkVEC in the targeted area. Calculate the retrieved full maps (surfTf) of near surface air temperatures using each sub-model. Then, identify abnormal samples and define their near-range regions in surfTf Apply a selective arithmetic mean (SAM) approach to achieve precision temperature map surfT. And finally apply further modification to the pixels of surfT where pixlf?badsurfT?f is true to all f=1, 2, 3, . . . . Using the super nonlinear algorithm, this invention provides a solution of retrieving near surface air temperature based on combinations of various factors (information fusion) to achieve satisfied prediction errors, which are independent of cloud levels and topographic characteristics.