This important work presents a self-supervised method for the segmentation of 3D cells in fluorescent microscopy images, conveniently packaged as a Napari plugin and tested on an annotated dataset.

Optical Character Recognition (OCR) is a powerful technology that converts images of text into machine-readable content. With the growing need for automation in data extraction, OCR tools have become ...

Abstract: The 850nm near-infrared (NIR) palm vein pattern imageries are considered and have been successfully recognized utilizing image processing in machine learning. The proposed method has well ...

This article provides a review and test of image-analysis methods for bacteria growing in the 'mother-machine' microfluidic device, introducing also a new graphical user interface for the ...

Improving the resolution of medical imaging systems and facial recognition algorithms has given rise to concerns about the identifiability of CT, MRI, and PET image data. In any imaging study ...

Made by Mathijs van Gorcum during his PhD at the Physics of Fluids group of the University of Twente. For the user documentation go to drop-analysis.com. Python program to analyze sessile drops by ...

Abstract: Weed control is essential in agricultural productivity as weeds act as a pest to crops. The conventional methods of weed removal are time-consuming and require more manual labour work. Hence ...

Aiming at the problem that it is difficult to identify two types of weeds, grass weeds and broadleaf weeds, in complex field environments, this paper proposes a semantic segmentation method with an ...