Abstract: Instance segmentation of remote sensing images (RSIs) is an essential task for a wide range of applications such as land planning and intelligent transport. Instance segmentation of RSIs is ...
Abstract: State-of-the-art (SOTA) methods for cell instance segmentation are based on deep learning (DL) semantic segmentation approaches, focusing on distinguishing foreground pixels from background ...
ABSTRACT: To address the issues of missed detection and false detection during the defect inspection process of the PCB, an improved YOLOv7-based algorithm for PCB defect detection is proposed.
I'm interested in using Coconut for semantic segmentation. I'm looking at the semantic segmentation tutorial. Is it normal that, in the configuration in the conf folder, only instance segmentation and ...
In recent years, the exploitation of three-dimensional (3D) data in deep learning has gained momentum despite its inherent challenges. The necessity of 3D approaches arises from the limitations of two ...
Customer segmentation and personalization are increasingly pivotal in shaping the landscape of marketing and insurance industries. By leveraging advanced technologies, businesses can analyze customer ...
Codebase for supervised segmentation of vasculature in 3D HiP-CT volumes using a 2.5D U-Net (stacked slices as colour channels with 2D convolutions). This repository adapts and refactors the Team-1 ...
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