Doaa Sami Khafaga¹, Sarah M. Alhammad^1,*, Amal Magdi², Osama ElKomy², Nabil A. Lashin², Khalid M. Hosny²

Computer Systems Science and Engineering, Vol.47, No.2, pp. 1967-1986, 2023, DOI:10.32604/csse.2023.040345

Abstract Image authentication techniques have recently received a lot of attention for protecting images against unauthorized access. Due to the wide use of the Internet nowadays, the need to ensure data integrity and authentication increases. Many techniques, such as watermarking and encryption, are used for securing images transmitted via the Internet. The majority of watermarking systems are PC-based, but they are not very portable. Hardware-based watermarking methods need to be developed to accommodate real-time applications and provide portability. This paper presents hybrid data security techniques using a zero watermarking method to provide copyright protection for the transmitted color images using multi-channel… More >

Turki M. Alanazi^*

Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 3343-3354, 2023, DOI:10.32604/iasc.2023.036411

Abstract Detecting and recognizing text from natural scene images presents a challenge because the image quality depends on the conditions in which the image is captured, such as viewing angles, blurring, sensor noise, etc. However, in this paper, a prototype for text detection and recognition from natural scene images is proposed. This prototype is based on the Raspberry Pi 4 and the Universal Serial Bus (USB) camera and embedded our text detection and recognition model, which was developed using the Python language. Our model is based on the deep learning text detector model through the Efficient and Accurate Scene Text Detector… More >

G. Arunachalam^1,*, P. SureshKumar²

Computer Systems Science and Engineering, Vol.45, No.2, pp. 1279-1294, 2023, DOI:10.32604/csse.2023.031001

Abstract The main components of Cognitive Radio networks are Primary Users (PU) and Secondary Users (SU). The most essential method used in Cognitive networks is Spectrum Sensing, which detects the spectrum band and opportunistically accesses the free white areas for different users. Exploiting the free spaces helps to increase the spectrum efficiency. But the existing spectrum sensing techniques such as energy detectors, cyclo-stationary detectors suffer from various problems such as complexity, non-responsive behaviors under low Signal to Noise Ratio (SNR) and computational overhead, which affects the performance of the sensing accuracy. Many algorithms such as Long-Short Term Memory (LSTM), Convolutional Neural… More >

N. Penchalaiah¹, Abeer S. Al-Humaimeedy², Mashael Maashi³, J. Chinna Babu^4,*, Osamah Ibrahim Khalaf⁵, Theyazn H. H. Aldhyani⁶

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5349-5365, 2022, DOI:10.32604/cmc.2022.029639

Abstract The expanding amounts of information created by Internet of Things (IoT) devices places a strain on cloud computing, which is often used for data analysis and storage. This paper investigates a different approach based on edge cloud applications, which involves data filtering and processing before being delivered to a backup cloud environment. This Paper suggest designing and implementing a low cost, low power cluster of Single Board Computers (SBC) for this purpose, reducing the amount of data that must be transmitted elsewhere, using Big Data ideas and technology. An Apache Hadoop and Spark Cluster that was used to run a… More >

Thien Khai Tran¹, Kha Tu Huynh^2,*, Dac-Nhuong Le³, Muhammad Arif⁴, Hoa Minh Dinh¹

Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 2479-2491, 2023, DOI:10.32604/iasc.2023.029078

Abstract Environmental pollution has had substantial impacts on human life, and trash is one of the main sources of such pollution in most countries. Trash classification from a collection of trash images can limit the overloading of garbage disposal systems and efficiently promote recycling activities; thus, development of such a classification system is topical and urgent. This paper proposed an effective trash classification system that relies on a classification module embedded in a hard-ware setup to classify trash in real time. An image dataset is first augmented to enhance the images before classifying them as either inorganic or organic trash. The… More >

Rihem Farkh^*, Khaled Aljaloud

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 901-911, 2023, DOI:10.32604/iasc.2023.027614

Abstract In a controlled indoor environment, line tracking has become the most practical and reliable navigation strategy for autonomous mobile robots. A line tracking robot is a self-mobile machine that can recognize and track a painted line on the floor. In general, the path is set and can be visible, such as a black line on a white surface with high contrasting colors. The robot’s path is marked by a distinct line or track, which the robot follows to move. Several scientific contributions from the disciplines of vision and control have been made to mobile robot vision-based navigation. Localization, automated map… More >

Rihem Farkh^1,2, Saad Alhuwaimel^3,*, Sultan Alzahrani³, Khaled Al Jaloud¹, Mohammad Tabrez Quasim⁴

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2811-2824, 2022, DOI:10.32604/cmc.2022.020259

Abstract Several applications of machine learning and artificial intelligence, have acquired importance and come to the fore as a result of recent advances and improvements in these approaches. Autonomous cars are one such application. This is expected to have a significant and revolutionary influence on society. Integration with smart cities, new infrastructure and urban planning with sophisticated cyber-security are some of the current ramifications of self-driving automobiles. The autonomous automobile, often known as self-driving systems or driverless vehicles, is a vehicle that can perceive its surroundings and navigate predetermined routes without human involvement. Cars are on the verge of evolving into… More >

Abdulfattah Noorwali¹, Ameni Yengui^2,*, Kaiçar Ammous², Anis Ammous¹

Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 455-466, 2022, DOI:10.32604/iasc.2022.020574

Abstract Early fetal cardiac diseases and heart abnormalities can be detected and appropriately treated by monitoring fetal health during pregnancy. Advancements in computer sciences and the technology of sensors show that is possible to monitor fetal electrocardiogram (fECG). Both signal processing and experimental aspects are needed to be investigated to monitor fECG. In this study, we aim to design and realize a non invasive fECG monitoring system. In the first part of this work, a remote study process of the electrical activity of the heart is achieved. In fact, our proposed design considers transmitting the detected signals in real time using… More >

Huijin Park, Soobin Ou, Jongwoo Lee^*

Intelligent Automation & Soft Computing, Vol.29, No.1, pp. 247-258, 2021, DOI:10.32604/iasc.2021.015274

Abstract Blind people are highly exposed to numerous dangers when they walk alone outside as they cannot obtain sufficient information about their surroundings. While proceeding along a crosswalk, acoustic signals are played, though such signals are often faulty or difficult to hear. The bollards can also be dangerous if they are not made with flexible materials or are located improperly. Therefore, since the blind cannot detect proper information about these obstacles while walking, their environment can prove to be dangerous. In this paper, we propose an object recognition system that allows the blind to walk safely outdoors. The proposed system can… More >

Rihem Farkh^1,5,*, Mohammad Tabrez Quasim², Khaled Al jaloud¹, Saad Alhuwaimel³, Shams Tabrez Siddiqui⁴

CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 1065-1079, 2021, DOI:10.32604/cmc.2021.016600

Abstract With the development of artificial intelligence technology, various sectors of industry have developed. Among them, the autonomous vehicle industry has developed considerably, and research on self-driving control systems using artificial intelligence has been extensively conducted. Studies on the use of image-based deep learning to monitor autonomous driving systems have recently been performed. In this paper, we propose an advanced control for a serving robot. A serving robot acts as an autonomous line-follower vehicle that can detect and follow the line drawn on the floor and move in specified directions. The robot should be able to follow the trajectory with speed… More >