Multi-spectral images classification based on intelligent water drops algorithm

Abstract

Mosul's city land covers soil, cultivated land, stony, pastoral land, water, and ploughed agricultural land. We have classified multispectral images captured by the sensor (TM) carried on the Landsat satellite. Integrated approach of intelligent water drops (IWDs) algorithm is used to identify natural terrain. In this research, IWDs have been suggested to find the best results for multispectral image classification. The purpose of using an algorithm, give accurate and fast results by comparing the IWD algorithm with the K-mean algorithm. The IWD algorithm is programmed using the Matlab2017b software environment to demonstrate the proposed methodology's effectiveness. The proposed integrated concept has been applied to satellite images of Mosul city in Iraq. By comparing the IWD with the K-mean, we found clear time superiority of the IWD algorithm, equal 1.4122 with (K-mean) time equal 18.9475. Furthermore, the water drop algorithm's classification accuracy is 95%, while the K-mean classification accuracy is 83.3%. Based on the analysis and results, we conclude the IWD is a robust promising and approach to detecting remote sensing image changes and multispectral image classification.

Classification of lower limb rehabilitation exercises with multiple and individual inertial measurement units

“…From the pilot study of the data, the BWT901CL and BMI160 IMU were configured to stream with sensor ranges of magnetometer (+/-1 Ga), gyroscope (+/-500 o /s) and (+/-2 g) 3-axis accelerometer. The calibration of the IMUs was done based on these particular sensor ranges using the "Phyphox" android mobile application developed by RWTH Aachen University and Witmotion Calibration application [21].…”

Image classification using machine learning

“…This model is associated with learning algorithms that analyze data for classification and regression analysis. A training model is a dataset used to train the SVM model which was created using OpenCV, Haar Indonesian J Elec Eng & Comp Sci ISSN: 2502-4752  cascade and scikit learn [31]- [33]. It is used to run the input data through our model to correlate the processed output against sample output.…”