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Modified total variation regularization using fuzzy complement for image denoising
(
IEEE Computer Society
, 2016 , Conference Paper)
In this paper, we propose a denoising algorithm based on the Total Variation (TV) model. Specifically, we associate to the regularization term of the Rodin-Osher-Fatimi (ROF) functional a small weight whenever denoising ...
Edge guided total variation for image denoising
(
Institute of Electrical and Electronics Engineers Inc.
, 2017 , Conference Paper)
In this paper, we present a novel denoising algorithm based on the Rodin-Osher-Fatemi (ROF) model. The goal is to ensure maximum noise removal while preserving image details. To achieve this goal, we developed a new edge ...
Deep learning approach for EEG compression in mHealth system
(
Institute of Electrical and Electronics Engineers Inc.
, 2017 , Conference Paper)
The emergence of mobile health (mHealth) systems has risen the challenges and concerns due to the sensitivity of the data involved in such systems. It is essential to ensure that these data are well delivered to the health ...
Using Deep Learning to Predict Stock Movements Direction in Emerging Markets: The Case of Qatar Stock Exchange
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Conference Paper)
Deep learning approaches have been utilized to predict stocks. In this study, we use convolutional neural network (CNN) to predict stocks direction in Qatar stock exchange (QE) as a case of emerging markets. Prediction in ...
Mobile crowdsourced sensors selection for journey services
(
Springer Verlag
, 2018 , Conference Paper)
We propose a mobile crowdsourced sensors selection approach to improve the journey planning service especially in areas where no wireless or vehicular sensors are available. We develop a location estimation model of journey ...
Dairy Cow Rumination Detection: A Deep Learning Approach
(
Springer Science and Business Media Deutschland GmbH
, 2020 , Conference Paper)
Cattle activity is an essential index for monitoring health and welfare of the ruminants. Thus, changes in the livestock behavior are a critical indicator for early detection and prevention of several diseases. Rumination ...
Gravitational weighted fuzzy c-means with application on multispectral image segmentation
(
Institute of Electrical and Electronics Engineers Inc.
, 2015 , Conference Paper)
This paper presents a novel clustering approach based on the classic Fuzzy c-means algorithm. The approach is inspired from the concept of interaction between objects in physics. Each data point is regarded as a particle. ...
A FCM and SURF based algorithm for segmentation of multispectral face images
(
IEEE
, 2013 , Conference Paper)
In this paper, we propose a novel clustering algorithm based on Fuzzy C-Means (FCM) and Speeded-Up Robust Feature (SURF) for multispectral image segmentation. In the experiments, color images and multispectral images from ...
Factors Affecting Student Satisfaction Towards Online Teaching: A Machine Learning Approach
(
Springer Science and Business Media Deutschland GmbH
, 2022 , Conference Paper)
During the outbreak of the Covid-19 pandemic, universities were forced to adopt technology and collaboration tools to reinforce online teaching and sustain their operations. This radical change pushes universities, ...
LIME: Long-Term Forecasting Model for Desalination Membrane Fouling to Estimate the Remaining Useful Life of Membrane
(
Springer Science and Business Media Deutschland GmbH
, 2023 , Conference Paper)
Membrane fouling is one of the major problems in desalination processes as it can cause a severe drop in the quality and quantity of the permeate water. This paper presents a data-driven approach for long-term forecasting ...