Fusion-based detection This approach mainly aims to fuse patients’ clinical data with any other possible information, such as chest X-ray and/or CT images, to use as the inputs for predictive models. Using a relatively large CT image dataset from multiple institutions across three continents, ...
We propose to develop an app for data fusion, which integrates the collected and analyzed information for stakeholders’ visualization. In the following sections, we first review the related works (Section 2), including image stitching, pig segmentation, and pig weight estimation methods. Then, in...
YOLO v3 [40] is extremely fast and treats the detection of the regions of interest as a regression problem by dividing the input image into a grid of size m × m, and for each cell in that grid it determines the probability that it belongs to a class of interest. A comprehensive ...