Article
Environmental Sciences
Elias Manos, Chandi Witharana, Mahendra Rajitha Udawalpola, Amit Hasan, Anna K. Liljedahl
Summary: Rapid global warming is causing widespread permafrost degradation in the Arctic, leading to a high risk of structural failure for human-built infrastructure. This study utilizes the U-Net deep learning model to automatically detect Arctic built infrastructure, showing promising potential for future applications.
Article
Computer Science, Information Systems
Simrandeep Singh, Nitin Mittal, Harbinder Singh, Diego Oliva
Summary: Image segmentation is a critical stage in image analysis and pre-processing, where pixels are divided into segments based on threshold values. Multi-level thresholding approaches are more effective than bi-level methods, and a new modified Otsu function is proposed that combines Otsu's between-class variance and Kapur's entropy. Experimental results demonstrate the high efficiency of the modified Otsu method in terms of performance metrics.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Article
Computer Science, Information Systems
Chunzhi Wang, Chengkun Tu, Siwei Wei, Lingyu Yan, Feifei Wei
Summary: This paper proposes a multilevel thresholding image segmentation technique based on an improved whale optimization algorithm. The results of algorithm evaluation experiments demonstrate that the MSWOA has higher search accuracy and faster convergence speed. The image segmentation experimental results show that the MSWOA-Kapur technique can effectively and accurately search multilevel thresholds.
Article
Computer Science, Information Systems
Wei Chen, Cenyu He, Chunlin Ji, Meiying Zhang, Siyu Chen
Summary: This study presents an improved K-means algorithm for underwater image background segmentation, addressing issues with K value determination and initial centroid position. Experimental results show that the algorithm effectively segments underwater image backgrounds, with low color cast, low contrast, and blurred edges. While the algorithm has higher time cost than existing methods, it proves more efficient than manual segmentation.
MULTIMEDIA TOOLS AND APPLICATIONS
(2021)
Article
Engineering, Biomedical
Osama S. Faragallah, Heba M. El-Hoseny, Hala S. El-sayed
Summary: Image segmentation technology is important for computer-aided diagnostic systems to identify the area to be treated. This paper proposes an efficient approach using OTSU segmentation and K-means clustering segmentation in different transform domains to localize brain tumor area. The proposed enhanced segmentation approaches show high precision and reliability in brain tumor localization.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2023)
Article
Computer Science, Artificial Intelligence
Mohamed Abd Elaziz, Songfeng Lu, Sibo He
Summary: This paper presents a multilevel thresholding image segmentation method based on enhancing the performance of the whale optimization algorithm (WOA), called the multi-leader whale optimization algorithm (MLWOA). MLWOA integrates different tools with WOA to improve exploration ability and avoid the trap of local optima during the search process.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Computer Science, Information Systems
Prabodh Kumar Sahoo, Priyadarshi Kanungo, Satyasis Mishra, Bibhu Prasad Mohanty
Summary: The paper proposes an efficient spatiotemporal segmentation method for extracting VOP in head and shoulder video sequences. The method achieves high detection accuracy in experimental results.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2022)
Article
Computer Science, Interdisciplinary Applications
B. G. Kodge
Summary: The world is facing numerous environmental issues due to global warming and other factors. This study uses digital image processing and geospatial techniques to investigate the changes in snow-covered areas in the Himalayan ranges.
EARTH SCIENCE INFORMATICS
(2023)
Article
Chemistry, Analytical
Jan Kubicek, Alice Varysova, Martin Cerny, Kristyna Hancarova, David Oczka, Martin Augustynek, Marek Penhaker, Ondrej Prokop, Radomir Scurek
Summary: This study comprehensively analyzes the performance of optimization methods based on fuzzy soft segmentation in the segmentation of articular cartilage magnetic resonance (MR) images. The study suggests that the combination of fuzzy thresholding with an ABC algorithm gives the best performance in segmentation and features extraction compared to other methods.
Article
Computer Science, Information Systems
Kristina P. Sinaga, Ishtiaq Hussain, Miin-Shen Yang
Summary: The study introduces a new clustering algorithm called Entropy-k-means that can achieve feature reduction behavior without being affected by initial cluster settings. This algorithm automatically finds the optimal number of clusters by eliminating irrelevant features.
Article
Computer Science, Artificial Intelligence
Essam H. Houssein, Bahaa El-din Helmy, Diego Oliva, Ahmed A. Elngar, Hassan Shaban
Summary: This paper introduces the use of the Black Widow Optimization (BWO) algorithm to find the best threshold configuration for multi-level image segmentation, achieving higher efficiency and reliability compared to other meta-heuristic algorithms. Experimental results demonstrate the superior performance of the BWO-based method, showing potential applications in the field of image processing.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Physics, Multidisciplinary
Jules Clement Mba, Ehounou Serge Eloge Florentin Angaman
Summary: This study proposes three portfolio strategies for small- and large-cap cryptocurrencies: allocation based on the normality assumption, the skewed-Student t distribution, and the entropy pooling method. Backtesting these strategies during a crypto market crash reveals that the normality assumption strategy performs the best in terms of wealth progression, followed by the skewed-Student t distribution and the entropy pooling method. Furthermore, the study finds that portfolios consisting of large-cap cryptocurrencies outperform those consisting of small-cap cryptocurrencies in terms of wealth progression and performance measures.
Article
Mathematical & Computational Biology
Shikai Wang, Kangjian Sun, Wanying Zhang, Heming Jia
Summary: The paper proposes a modified ant lion optimizer algorithm based on opposition-based learning for optimizing multilevel thresholding in image segmentation, and experimental results show that the method outperforms others in terms of segmentation performance.
MATHEMATICAL BIOSCIENCES AND ENGINEERING
(2021)
Article
Computer Science, Artificial Intelligence
Ashish Kumar Gupta, Ayan Seal, Pritee Khanna, Ondrej Krejcar, Anis Yazidi
Summary: In this study, self-adjustable distance measures based on weighted k-means clustering (W-k-means) were proposed for generating superpixel segmentation, which outperformed the conventional SLIC algorithm on three benchmarks under different distance measures. The adaptive nature of the weight updates resulted in superpixels with better boundary adherence and compactness, demonstrating the effectiveness of the proposed AWkS over SLIC, particularly in saliency detection.
PATTERN ANALYSIS AND APPLICATIONS
(2021)
Article
Engineering, Electrical & Electronic
Nilima Shah, Dhanesh Patel, Pasi Franti
Summary: The study introduces how to integrate the Mumford-Shah model into the k-means algorithm to optimize the content and shape of image segmentation simultaneously. The experiments demonstrate that the proposed method provides better results compared to comparative methods.
JOURNAL OF ELECTRONIC IMAGING
(2021)
Article
Geosciences, Multidisciplinary
Manare Adnani, Mohammed Amine Azzaoui, Hicham Elbelrhiti, Mfedal Ahmaniou, Lhoussaine Masmoudi
Article
Engineering, Electrical & Electronic
Zakaria Kerkaou, Nawal Aliou, Mohamed El Ansari, Lhoussaine Masmoudi
JOURNAL OF ELECTRONIC IMAGING
(2018)
Article
Computer Science, Information Systems
Salah Eddine Mechkouri, Saleh El Joumani, Rachid Zennouhi, Lhoussaine Masmoudi
MULTIMEDIA TOOLS AND APPLICATIONS
(2020)
Article
Optics
Abdelkrim Abanay, Lhoussaine Masmoudi, Mohamed El Ansari
Summary: This paper presents a calibration method for 2D LIDAR-Visual sensors embedded on an agricultural robot. The method utilizes a plan-to-plan homography approach and a set of point correspondences to estimate the transformation between the sensors. The results show that the proposed method can accurately determine the extrinsic parameters without requiring complex calibration objects.
Proceedings Paper
Computer Science, Artificial Intelligence
Rania Majdoubi, Lhoussaine Masmoudi
Summary: This paper introduces the design of an ecological agricultural robot dedicated to maintaining strawberry cultivation in greenhouses, including components such as a mobile platform, vision system, pump system, and laser telemeter, with energy provided by a photovoltaic charging station. The classical design approach is used to present the robot prototype from technical specifications to CAD model.
2021 IEEE INTERNATIONAL CONFERENCE ON COMPUTING, COMMUNICATION, AND INTELLIGENT SYSTEMS (ICCCIS)
(2021)
Proceedings Paper
Engineering, Electrical & Electronic
Rania Majdoubi, Lhousasaine Masmoudi, Abderrahmane Elharif
Summary: This paper presents a method for controlling a Brushless Direct Current Motor (BLDCM) during the traction of an autonomous robot, optimizing power consumption to achieve optimal operation and reusing lost energy.
2021 IEEE INTERNATIONAL IOT, ELECTRONICS AND MECHATRONICS CONFERENCE (IEMTRONICS)
(2021)
Proceedings Paper
Computer Science, Theory & Methods
Samia Achouch, Lhoussaine Masmoudi, Pierre Nonnon, Mourad Gharbi
Summary: This study focuses on the fabrication of a capacitive 3D printed pressure sensor for educational use, aiming to address the lack of experimentation equipment in the Moroccan education system and Africa in general, by reducing the overall cost of experiments and improving teaching quality.
2021 IEEE 11TH ANNUAL COMPUTING AND COMMUNICATION WORKSHOP AND CONFERENCE (CCWC)
(2021)
Article
Computer Science, Artificial Intelligence
Zakaria Kerkaou, Mohamed El Ansari, Lhoussaine Masmoudi, Redouan Lahmyed
Summary: This paper presents a new method for matching stereo images by involving temporal matching and dynamic programming algorithm to achieve spatial matching of stereo images. The proposed approach has been tested on both real and synthetic stereo sequences with effective results.
IET IMAGE PROCESSING
(2021)
Article
Computer Science, Theory & Methods
M. A. Azzaoui, L. Masmoudi, H. El Belrhiti, I. E. Chaouki
INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS
(2020)
Article
Computer Science, Theory & Methods
M. A. Azzaoui, L. Masmoudi, H. El Belrhiti, I. E. Chaouki
INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS
(2019)
Proceedings Paper
Computer Science, Artificial Intelligence
Zakaria Kerkaou, Nawal Alioua, Mohamed El Ansari, Lhoussaine Masmoudi
2018 INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS AND COMPUTER VISION (ISCV2018)
(2018)
Proceedings Paper
Computer Science, Hardware & Architecture
A. Abanay, Lh. Masmoudi, A. Elharif, M. Gharbi, B. Bououlid
ICCWCS'17: PROCEEDINGS OF THE 2ND INTERNATIONAL CONFERENCE ON COMPUTING AND WIRELESS COMMUNICATION SYSTEMS
(2017)
