Sophie Tan: New Applications
https://www.maplesoft.com/applications/author.aspx?mid=327463
en-us2022 Maplesoft, A Division of Waterloo Maple Inc.Maplesoft Document SystemMon, 17 Jan 2022 23:04:14 GMTMon, 17 Jan 2022 23:04:14 GMTNew applications published by Sophie Tanhttps://www.maplesoft.com/images/Application_center_hp.jpgSophie Tan: New Applications
https://www.maplesoft.com/applications/author.aspx?mid=327463
Circle Detection with Hough Transform
https://www.maplesoft.com/applications/view.aspx?SID=154477&ref=Feed
Circular Hough Transform is a variation of the classical Hough Transform that detects circles instead of straight lines in an image. The theory behind the two algorithms are the same: they let all edge pixels "vote" and select the candidates with the most votes to be the detected shapes.This application will demonstrate circle detection from a real life image with Hough Transform.<img src="https://www.maplesoft.com/view.aspx?si=154477/Billiard.jpg" alt="Circle Detection with Hough Transform" style="max-width: 25%;" align="left"/>Circular Hough Transform is a variation of the classical Hough Transform that detects circles instead of straight lines in an image. The theory behind the two algorithms are the same: they let all edge pixels "vote" and select the candidates with the most votes to be the detected shapes.This application will demonstrate circle detection from a real life image with Hough Transform.https://www.maplesoft.com/applications/view.aspx?SID=154477&ref=FeedFri, 20 Jul 2018 04:00:00 ZSophie TanSophie TanLine Detection with Hough Transform
https://www.maplesoft.com/applications/view.aspx?SID=154476&ref=Feed
Hough transform is a feature extraction algorithm widely used in the field of object detection and image processing. It employs a voting procedure where all edge pixels vote to identify a certain class of shapes in the image. Classical Hough transform is designed to detect straight lines, but with some modification it can be used to detect other arbitrary shapes (usually circles and ellipses). In this application, we will implement the Hough Line Transform and use it to extract straight lines from an image of a traffic lane. An interesting fact about line detection is that the technique is being actively studied in research of self-driving cars, where image of lanes/roadways is processed to adjust the car's motion.<img src="https://www.maplesoft.com/view.aspx?si=154476/lines.png" alt="Line Detection with Hough Transform" style="max-width: 25%;" align="left"/>Hough transform is a feature extraction algorithm widely used in the field of object detection and image processing. It employs a voting procedure where all edge pixels vote to identify a certain class of shapes in the image. Classical Hough transform is designed to detect straight lines, but with some modification it can be used to detect other arbitrary shapes (usually circles and ellipses). In this application, we will implement the Hough Line Transform and use it to extract straight lines from an image of a traffic lane. An interesting fact about line detection is that the technique is being actively studied in research of self-driving cars, where image of lanes/roadways is processed to adjust the car's motion.https://www.maplesoft.com/applications/view.aspx?SID=154476&ref=FeedFri, 20 Jul 2018 04:00:00 ZSamir KhanSamir KhanDiscrete Haar Wavelet Image Compression
https://www.maplesoft.com/applications/view.aspx?SID=154471&ref=Feed
This application demonstrates how to perform both lossy and lossless image compression with Haar Wavelet Transform using DWT() command in the SignalProccessing Package.
Haar Wavelet compression modifies the entries in an image matrix to increase the number of zero entries, thus resulting in a sparse matrix that can be stored more efficiently by the computer.<img src="https://www.maplesoft.com/view.aspx?si=154471/original.jpeg" alt="Discrete Haar Wavelet Image Compression" style="max-width: 25%;" align="left"/>This application demonstrates how to perform both lossy and lossless image compression with Haar Wavelet Transform using DWT() command in the SignalProccessing Package.
Haar Wavelet compression modifies the entries in an image matrix to increase the number of zero entries, thus resulting in a sparse matrix that can be stored more efficiently by the computer.https://www.maplesoft.com/applications/view.aspx?SID=154471&ref=FeedMon, 25 Jun 2018 04:00:00 ZSophie TanSophie TanRemoval of Periodic and Salt & Pepper Noise from an Image
https://www.maplesoft.com/applications/view.aspx?SID=154470&ref=Feed
This application demonstrates the removal of two common noises-periodic noises and salt & pepper noises - from an image. Periodic noises result in repeating patterns being added onto the picture, while salt & pepper noises refer to when there are bright and dark pixels randomly spread across an image. This application employs Fourier Transform and median filter to remove the two noises with respect.<img src="https://www.maplesoft.com/view.aspx?si=154470/image1_-_Copy.jpeg" alt="Removal of Periodic and Salt & Pepper Noise from an Image" style="max-width: 25%;" align="left"/>This application demonstrates the removal of two common noises-periodic noises and salt & pepper noises - from an image. Periodic noises result in repeating patterns being added onto the picture, while salt & pepper noises refer to when there are bright and dark pixels randomly spread across an image. This application employs Fourier Transform and median filter to remove the two noises with respect.https://www.maplesoft.com/applications/view.aspx?SID=154470&ref=FeedMon, 18 Jun 2018 04:00:00 ZSamir KhanSamir KhanPrediction of malignant/benign of breast mass with DNN classifier
https://www.maplesoft.com/applications/view.aspx?SID=154469&ref=Feed
This demonstration application employs the DeepLearning package to train a DNN classifer with the Breast Cancer Wisconsin (Diagnostic) Data Set and uses the classifier to predict the diagnosis of a breast mass with 30 real input values.<img src="https://www.maplesoft.com/view.aspx?si=154469/Capture.PNG" alt="Prediction of malignant/benign of breast mass with DNN classifier" style="max-width: 25%;" align="left"/>This demonstration application employs the DeepLearning package to train a DNN classifer with the Breast Cancer Wisconsin (Diagnostic) Data Set and uses the classifier to predict the diagnosis of a breast mass with 30 real input values.https://www.maplesoft.com/applications/view.aspx?SID=154469&ref=FeedFri, 15 Jun 2018 04:00:00 ZSophie TanSophie TanPredicting Forest Fires with DNN Regressor
https://www.maplesoft.com/applications/view.aspx?SID=154467&ref=Feed
This application employs the DeepLearning Package to train a DNN Regressor with the ForestFires Data Set on UCI Machine Learning Repository and uses the trained model to predict the burnt area of a forest fire with 10 real input values. The original data set belongs to UCI Machine Learning Repository and can be accessed at https://archive.ics.uci.edu/ml/datasets/Forest+Fires<img src="https://www.maplesoft.com/view.aspx?si=154467/Forest-Fire.jpg" alt="Predicting Forest Fires with DNN Regressor" style="max-width: 25%;" align="left"/>This application employs the DeepLearning Package to train a DNN Regressor with the ForestFires Data Set on UCI Machine Learning Repository and uses the trained model to predict the burnt area of a forest fire with 10 real input values. The original data set belongs to UCI Machine Learning Repository and can be accessed at https://archive.ics.uci.edu/ml/datasets/Forest+Fireshttps://www.maplesoft.com/applications/view.aspx?SID=154467&ref=FeedFri, 15 Jun 2018 04:00:00 ZSophie TanSophie Tan