localisation

KEWLS and KFF 2D Comparative Model

This Matlab model and the included results are submitted as reference for the paper ''.

Presenting a comparative study of the Sequential Unscented Kalman Filter (SUKF), Least-squares (LS) Multilateration and standard Unscented Kalman Filter (UKF) for localisation that relies on sequentially received datasets.

The KEWLS and KKF approach presents a novel solution using Linear Kalman Filters (LKF) to extrapolate individual sensor measurements to a synchronous point in time for use in LS Multilateration.

Categories:: Communications
Energy
Sensors
Nonlinear signal processing

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Endoscopy Disease Detection and Segmentation (EDD2020)

Endoscopy is a widely used clinical procedure for the early detection of cancers in hollow-organs such as oesophagus, stomach, and colon. Computer-assisted methods for accurate and temporally consistent localisation and segmentation of diseased region-of-interests enable precise quantification and mapping of lesions from clinical endoscopy videos which is critical for monitoring and surgical planning. Innovations have the potential to improve current medical practices and refine healthcare systems worldwide.

Artificial Intelligence

Image Processing

Computer Vision

Machine Learning

Biomedical and Health Sciences

Medical Imaging

Submitted On:

Wed, 01/15/2020 - 11:24

Last Updated On:

Sat, 02/27/2021 - 05:11