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An Efficient Medical Image Deep Fusion Model Based on Convolutional Neural Networks

computers, Materials & Continua 2023年第2期74卷 2905-2925页

作者： Walid El-Shafai Noha A.El-Hag Ahmed Sedik Ghada Elbanby Fathi E.Abd El-Samie Naglaa F.Soliman Hussah Nasser AlEisa Mohammed E.Abdel Samea Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security Engineering Laboratory Department of Computer SciencePrince Sultan UniversityRiyadh11586Saudi Arabia Higher Institute of Commercial Science Management Information SystemsEl-Mahala El-KobraEgypt Department of the Robotics and Intelligent Machines Faculty of Artificial IntelligenceKafrelsheikh UniversityKafr El-SheikhEgypt Department of Industrial Electronics and Control Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadhSaudi Arabia Medical Imaging and Interventional Radiology National Liver InstituteMenoufia UniversityEgypt

Medical image fusion is considered the best method for obtaining one image with rich details for efficient medical diagnosis and *** learning provides a high performance for several medical image analysis *** paper proposes a deep learning model for the medical image fusion *** model depends on Convolutional Neural Network(CNN).The basic idea of the proposed model is to extract features from both CT and MR ***,an additional process is executed on the extracted *** that,the fused feature map is reconstructed to obtain the resulting fused ***,the quality of the resulting fused image is enhanced by various enhancement techniques such as Histogram Matching(HM),Histogram Equalization(HE),fuzzy technique,fuzzy type,and Contrast Limited Histogram Equalization(CLAHE).The performance of the proposed fusion-based CNN model is measured by various metrics of the fusion and enhancement *** realistic datasets of different modalities and diseases are tested and ***,real datasets are tested in the simulation analysis.

关键词： Image fusion CNN deep learning feature extraction evaluation metrics medical diagnosis

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Analysis of the Scientific Publication of Libyan State: A Bibliometric Review 3

Analysis of the Scientific Publication of Libyan State: A Bi...

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3rd IEEE International Maghreb Meeting of the Conference on Sciences and Techniques of Automatic Control and computer engineering, MI-STA 2023

作者： Jaradat, Yousef M. Zerek, Amer R. Masoud, Mohammad Z. Manasrah, Ahmad A. Abdaljlil, Sana Ahmed Alheyasat, Omar Al-Zaytoonah University of Jordan Communications and Computer Engineering Amman Jordan Libya Open University Communication Engineering Tripoli Libya Al-Zaytoonah University of Jordan Mechanical Engineering Amman Jordan AlBalqa' Applied University Computer Engineering Department Salt Jordan

ISBN: (纸本)9798350319897

This paper provides a detailed bibliometric analysis of the Libyan State's scientific publications (Libya). The study is based on data from the well-known Scopus database. The study spans the years 1948 to 2022. The study examines the growth of annual publications and citations. It has been demonstrated that over the last five years, 36% of total publications and 66% of total citations have been achieved. Science mapping activities such as co-occurrence and co-citation networks were used to reveal thematic clustering and research topic trends. The top source title with the most articles is the 2021 1ST MI-STA conference, which has 142 articles. The LANCET journal is the most frequently cited locally, with 1181 articles citing it, and the most prolific author is Dr. ElHadi from the University of Tripoli with 76 articles. © 2023 IEEE.

关键词： Publishing

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Crowd-Counting of Images in Rainy Weather Based on GAN-U-Net Model and Multi-column CNN Counting Approaches 3

Crowd-Counting of Images in Rainy Weather Based on GAN-U-Net...

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3rd IEEE International Conference on Electronic engineering, ICEEM 2023

作者： Saad, Rasha A. Abd El-Samie, Fathi E. Abdel-Azim, Mohammed El-Hoseny, Heba M. Obour Higher Institute for Engineering and Technology Department of Electronics and Electrical Communications Egypt Menoufia University Faculty of Electronic Engineering Department of Electronics and Electrical Communications Egypt Mansoura University Faculty of Engineering Department of Electronics and Electrical Communications Egypt The Higher Future Institute for Specialized Technological Studies Department of Computer Science Egypt

ISBN: (纸本)9798350323511

A count of crowds tries to determine the total number of persons in crowded places in order to avoid disruption of the safety system and maintain crowd safety. Accurate estimation of the size of crowds is a challenging process because of numerous challenges like occlusion, complicated backgrounds, varying sizes, uneven distribution, alteration of lighting, and adaptable weather. In this study, we propose a solution to two crowd counting challenges: poor weather such as rain and image scaling. We investigate crowd counting in the rainy Shanghai-Tec images. We adopt the GAN-U-Net de-raining model and the SAS-Net [1] and SGA-Net [2] crowd-counting models in our study. © 2023 IEEE.

关键词： computer vision

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Detecting Anomalies for corn crop disease using Isolation forest 1

Detecting Anomalies for corn crop disease using Isolation fo...

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1st IEEE International Conference on Networking and communications, ICNWC 2023

作者： Sowmiya, K. Thenmozhi, M. SRM Institute of Science and Technology Department of Computer Science and Engineering Chennai India SRM Institute of Science and Technology Department of Networking and Communications Chennai India

ISBN: (纸本)9798350336009

Today, the most challenging issue for researchers is to continue their research for crop disease using deep learning and image processing. One of the crucial detection methods used in one-class classification to find the outliers in the dataset is anomaly detection. The isolation forest approach is used in this work to discover anomalies using the corn dataset from Kaggleas a benchmark dataset. To find abnormalities in the provided dataset, this algorithm mimics a binary decision tree technique. This algorithm's classification accuracy is 89 percent. For the corn dataset, the experimental findings of the isolation forest show improved outcomes. Other anomaly identification methods will eventually combine anomaly scores and new datasets on leaf disease. © 2023 IEEE.

关键词： Image processing

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STACKMAPS: A Visualization Technique for Diabetic Retinopathy Grading 48

STACKMAPS: A Visualization Technique for Diabetic Retinopath...

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48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023

作者： El-Yamany, Ismail Wael, Abdelrahman Adly, Noha Torki, Marwan Ministry of Communications and Information Technology Applied Innovation Center Egypt Alexandria University Computer and Systems Engineering Department Egypt Microsoft Egypt

ISBN: (纸本)9781728163277

Convolution Neural Networks (CNN) excelled humans in many classification tasks, including medical imaging applications. However, model interpretation is still an active research area. In this paper, we address the model interpretation problem for the Diabetic Retinopathy grading task. We propose a novel visualization method called StackMaps. Our proposed method is class-agnostic, which fits the diabetic retinopathy grading problem better than other alternatives. Moreover, unlike previous visualization methods, StackMaps gets rid of the dependency on gradients. Our StackMaps technique gets the most significant feature maps at the last convolutional layer after one forward pass. We can also get the significant feature maps from lower layers using beam search guided by the feature maps obtained from the previous layer. Finally, we compute the final map as the sum of the significant feature maps obtained at each layer. We evaluate StackMaps against other state-of-the-art visualization methods qualitatively and quantitatively. We used the FGADR dataset to define our experimental setup. We show that StackMaps achieves better visual interpretation and lesion localization. © 2023 IEEE.

关键词： StackMaps Visual Explanations Weakly Supervised Learning

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Video quality enhancement using different enhancement and dehazing techniques

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Journal of Ambient Intelligence and Humanized Computing 2023年第12期14卷 16607-16635页

作者： Ayoub, Abeer Naeem, Ensherah A. El-Shafai, Walid El-Samie, Fathi E. Abd Hamad, Ehab K. I. El-Rabaie, El-Sayed M. Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt Electrical Department Faculty of Technology and Education Suez University Suez43527 Egypt Security Engineering Lab Computer Science Department Prince Sultan University Riyadh11586 Saudi Arabia Electrical Engineering Department Faculty of Engineering Aswan University Aswan81542 Egypt Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia

Video in an outdoor environment suffers from the haze problem due to smoke, dust, and other particles in the atmosphere. The quality of video under these atmospheric conditions is clearly/dramatically degraded, leading to poor contrast and information leakage. The proposed algorithm in this paper depends on pre-processing of video frames prior to the dehazing process. Different enhancement techniques are used to remove noise and control the dynamic range, because each frame has some noise due to sensor measurement errors. This noise might be magnified during the haze removal process, if totally neglected. Previous dehazing algorithms enhance the video contrast and reduce frame degradation. We use optimized dehazing algorithms, namely a dual-transmission-map dehazing algorithm, and a recursive Deep Residual Learning (DRL) network, as dehazing tools. We modify the previous dehazing algorithms to generate new algorithms to be suitable not only for visible frames but also for Near Infrared (NIR) frames. In the optimized dehazing algorithms, the haze effect is reduced, according to the hazing model. In the dual-transmission-map dehazing algorithm, the effect of attenuation parameter R and attenuation weight U on the dehazed frames is investigated. A dual-transmission-map algorithm, depending on the Dark Channel Prior (DCP) technique, is studied. We study the effect of a regularization parameter Ω on the visible and NIR dehazed frames without and with enhancement techniques. For the recursive deep residual learning algorithm, we increase the number of iterations in the DRL network from three iterations in the traditional DRL algorithm without denoising techniques to nine iterations, in order to explore the impact of increasing the number of iterations on the output dehazed frames. Since elapsed time grows with the number of iterations, we terminate the operation after the ninth iteration. A comparison between traditional algorithms and the proposed dehazing algorithms is

关键词： Deep learning

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Arduino Based Obstacle Avoiding Robot with Ultrasonic Sensors and Motor Functions 3

Arduino Based Obstacle Avoiding Robot with Ultrasonic Sensor...

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3rd IEEE International Conference on ICT in Business Industry and Government, ICTBIG 2023

作者： Abuan, Donabel Lim, Markquis Lontoc, Christian Rodel V. Sangrador, Jann See, Jethric Dadios, Elmer P. Gokongwei College of Engineering De la Salle University Department of Electronics and Communications Engineering Manila Philippines Gokongwei College of Engineering De la Salle University Department of Computer Engineering Manila Philippines

ISBN: (纸本)9798350343274

A simple robotics project simulated in Tinkercad based on Arduino Uno. It uses ultrasonic sensors for obstacle detection and can do basic movements using DC motors. The primary objective of this project is to develop an autonomous robot capable of navigating an environment while detecting and avoiding obstacles in its path. The robot utilizes ultrasonic sensors to measure distances and determine the presence of obstacles, employing an Arduino microcontroller to process sensor data and make real-time decisions. Motor functions are coordinated through the Arduino to enable dynamic movement and obstacle avoidance strategies. This project serves as a foundational framework for developing intelligent, obstacle-avoiding robotic systems using readily available components and open-source platforms like Arduino. By Using Tinkercad, it offers a virtual workspace where you can design circuits using Arduino boards, ultrasonic sensors, motor drivers, and other electronic components. You can drag and drop components onto a virtual breadboard, connect them using wires, and simulate the connections and interactions between the components. © 2023 IEEE.

关键词： Obstacle detectors

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How Lasers Exploit Photoacoustic and Photoelectric Phenomena to Inject Signals into MEMS Microphones

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Journal of Hardware and Systems Security 2025年 1-17页

作者： Cyr, Benjamin Sumaria, Vedant Long, Yan Tadigadapa, Srinivas Sugawara, Takeshi Fu, Kevin Computer Science and Engineering University of Michigan Ann Arbor USA Electrical & Computer Engineering Northeastern University Boston USA Department of Informatics The University of Electro-Communications Tokyo Japan

An amplitude-modulated laser can be used to generate false, yet coherent acoustic signals on the outputs of MEMS microphones. While this vulnerability has ramifications on the security of cyber-physical systems that trust these microphones, the physical explanation of this effect remained a mystery. Without an understanding of the physical phenomena contributing to this signal injection, it is difficult to design effective and reliable defenses. In this work, we show the degree to which the mechanisms of thermoelastic bending, thermal diffusion, and photocurrent generation are used to inject signals into MEMS microphones. We provide models for each of these mechanisms, develop a procedure to empirically determine their relative contributions, and highlight the effects on eight commercial MEMS microphones. We accomplish this with a precise setup to isolate each mechanism using several laser wavelengths and a vacuum chamber. The results indicate that the injected signal on the microphone is dependent on the wavelength of the incoming light. Shorter wavelengths (such as a 450 nm blue laser) exploit photoacoustic effects, and the periodic heating and expansion of air is the dominant factor in seven of eight sample microphones. Longer wavelengths (such as a 904 nm infrared laser) exploit photoelectric effects on the sensitive ASIC, generating signals that are between 2x and 100x stronger than photoacoustic signals in six of eight sample microphones. This understanding of the physical causality of laser signal injection leads to recommendations for future laser-resistant microphone designs. These include adding light-blocking structures at the system or device level, improving to glob top application, and adding simple light or temperature sensors for injection detection. Based on the fundamental causality, we also suggest potential vulnerabilities within other sensors with similar characteristics to MEMS microphones, such as conventional microphones, ultrasonic

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An Assessment on Integration of Wireless Sensor Networks with Cloud Computing

An Assessment on Integration of Wireless Sensor Networks wit...

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2022 International Conference on Emerging Trends in Smart Technologies, ICETST 2022

作者： Ahmed, Ali Ahmed, Huma Ali Bahria University Computer Engineering Department Karachi Campus Karachi Pakistan Newports Institute of Communications & Economics Department of Computer Science Karachi Pakistan

ISBN: (数字)9781665459358

ISBN: (纸本)9781665459358

Wireless sensor networks (WSNs) provides a major responsibility in the collection and processing of information from the real world. Similarly, cloud computing provides distributed platforms and resource sharing with the help of WSNs. The combination of these two technologies gives ease to communicate in virtual communities which is very beneficial in different domains. Cloud computing can be merged with WSNs in various applications. This will provide an easier way to understand sensor's data in real-time environments. We are going to perform a detailed survey on integration of WSNs with cloud computing and its infrastructural approaches in this research paper. © 2022 IEEE.

关键词： Cloud computing

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New Delay Doppler Communication Paradigm in 6G Era:A Survey of Orthogonal Time Frequency Space(OTFS)

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China communications 2023年第6期20卷 1-25页

作者： Weijie Yuan Shuangyang Li Zhiqiang Wei Yuanhao Cui Jiamo Jiang Haijun Zhang Pingzhi Fan Department of Electronic and Electrical Engineering Southern University of Science and TechnologyShenzhenChina Faculty of Electrical Engineering and Computer Science Technical University of BerlinBerlinGermany School of Mathematics and Statistics Xi’an Jiaotong UniversityXi’anChina Department of Communication Engineering Beijing University of Posts and TelecommunicationsBeijingChina China Academy of Information and Communications Technology BeijingChina School of Computer and Communication Engineering University of Science and Technology BeijingBeijingChina School of Information Science and Technology Southwest Jiaotong UniversityChengduChina

In the 6G era,Space-Air-Ground Integrated Network(SAGIN)are anticipated to deliver global coverage,necessitating support for a diverse array of emerging applications in high-mobility,hostile *** such conditions,conventional orthogonal frequency division multiplexing(OFDM)modulation,widely employed in cellular and Wi-Fi communication systems,experiences performance degradation due to significant Doppler *** overcome this obstacle,a novel twodimensional(2D)modulation approach,namely orthogonal time frequency space(OTFS),has emerged as a key enabler for future high-mobility use ***,OTFS modulates information within the delay-Doppler(DD)domain,as opposed to the timefrequency(TF)domain utilized by *** offers advantages such as Doppler and delay resilience,reduced signaling latency,a lower peak-to-average ratio(PAPR),and a reduced-complexity *** studies further indicate that the direct interplay between information and the physical world in the DD domain positions OTFS as a promising waveform for achieving integrated sensing and communications(ISAC).In this article,we present an in-depth review of OTFS technology in the context of the 6G era,encompassing fundamentals,recent advancements,and future *** objective is to provide a helpful resource for researchers engaged in the field of OTFS.

关键词： OTFS 6G delay-Doppler(DD)domain

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