Alireza Akoushideh | Computer Science | Best Researcher Award

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Assist. Prof. Dr. Alireza Akoushideh | Computer Science | Best Researcher Award

Electrical and Computer Department from Iran’s National University of Skill, Iran

Dr. Alireza Akoushideh is an Assistant Professor in Electronics Engineering with a specialization in image processing, parallel processing, and microcontroller-based systems. With over two decades of experience in academia and research, he has made significant contributions to digital electronics, focusing on industrial applications. His expertise extends to supervising research projects, authoring academic books, and securing multiple patents. Dr. Akoushideh has been an active participant in national and international collaborations, including a visiting research position at the University of Twente in the Netherlands and participation in the Erasmus+ program in Romania. In addition to his academic contributions, he has played a vital role in fostering technological innovations as the former manager of the Growth Centre at Guilan Science and Technology Park. His work emphasizes bridging the gap between academia and industry, particularly in the development of applied research projects and commercialization of new technologies. Recognized for his research excellence, he has received multiple awards, including the Best Researcher title at Guilan Technical and Vocational University. With a strong background in electronics and computer engineering, Dr. Akoushideh continues to contribute to advancements in artificial intelligence, IoT, and digital systems, making him a distinguished researcher in his field.

Professional Profile

Education

Dr. Akoushideh has a strong academic foundation in electrical and electronics engineering. He earned his Ph.D. in Electrical Engineering with a specialization in Electronics from Shahid Beheshti University, where his research focused on developing noise-resistant feature extraction operators for texture classification. His doctoral work contributed significantly to the fields of image processing and pattern recognition. Prior to that, he completed his Master’s degree at Amirkabir University of Technology (Tehran Polytechnic), specializing in electronics. His master’s thesis revolved around designing a pacemaker system based on the detection of cardiac arrests, demonstrating his early interest in biomedical applications of electronics. Dr. Akoushideh obtained his Bachelor’s degree from the University of Guilan, where he specialized in electronics engineering. His undergraduate research involved the development of a computer-based microcontroller trainer, highlighting his inclination towards microcontroller-based system design. Throughout his academic journey, he has consistently focused on applying electronics engineering principles to real-world challenges, which is evident in his later research projects and technological innovations. His education, spanning three prestigious Iranian institutions, has provided him with the necessary expertise to excel in both theoretical and applied aspects of electronics, further enriching his contributions to academia, research, and industry.

Professional Experience

Dr. Akoushideh has had an extensive career in academia, research, and industry. He is currently an Assistant Professor at the Technical and Vocational University in Iran, where he teaches courses in image processing, computer architecture, microcontrollers, and digital systems. His role extends beyond teaching, as he actively supervises undergraduate and graduate research projects, guiding students in developing innovative solutions for industrial and technological challenges. He has also served as a visiting researcher at the University of Twente in the Netherlands, where he collaborated on biometrics and pattern recognition research. Additionally, he participated in the Erasmus+ program at Pitesti University in Romania, contributing to international discussions on vocational education and training. Dr. Akoushideh has held managerial roles, including serving as the Growth Centre Manager at Guilan Science and Technology Park, where he played a key role in supporting technology startups and commercializing academic research. His industry experience includes co-founding Rayaneh Gostar Moein Co., where he worked on network design, industrial automation, and electronic content production. His diverse professional background reflects his ability to integrate academic research with industrial applications, making significant contributions to both education and technology-driven initiatives.

Research Interests

Dr. Akoushideh’s research interests lie in the intersection of digital electronics, image processing, artificial intelligence, and microcontroller-based systems. His work primarily focuses on developing advanced image processing techniques for applications such as biometrics, video surveillance, and medical diagnostics. He has also contributed to research in pattern recognition, deep learning, and IoT-based automation systems. His interest in parallel processing has led him to explore hardware acceleration techniques for computationally intensive tasks, improving the efficiency of embedded systems. In addition to theoretical advancements, Dr. Akoushideh is deeply involved in applied research, particularly in developing smart electronic devices and automation systems for industrial and consumer applications. His projects include intelligent power management systems, real-time video analytics, and embedded system design for IoT applications. He is also keen on integrating artificial intelligence into embedded systems, exploring new methods for enhancing efficiency and performance in real-time processing environments. With a strong background in both academic and practical research, his work contributes to the advancement of smart technologies, automation, and digital signal processing, positioning him as a leading researcher in electronics and computer engineering.

Research Skills

Dr. Akoushideh possesses a diverse range of research skills spanning hardware and software domains. He has expertise in digital image processing, machine learning, and deep learning techniques, applying them to areas such as biometrics, video analysis, and industrial automation. His programming proficiency includes MATLAB, Python, C++, and hardware description languages like VHDL, allowing him to develop and implement complex algorithms for embedded systems. His hands-on experience with microcontrollers such as AVR, ARM, and PIC enables him to design and prototype advanced electronic devices. Additionally, he is skilled in PCB design using Altium Designer and FPGA-based system development using Xilinx ISE and Synopsys tools. His research capabilities extend to IoT and smart systems, where he has worked on projects involving sensor networks, remote monitoring, and intelligent control systems. Dr. Akoushideh is also experienced in conducting experimental research, statistical data analysis, and scientific writing, which are essential for publishing in high-impact journals. His interdisciplinary approach, combining hardware and software expertise, makes him highly proficient in designing, developing, and optimizing electronic and computational systems for various applications.

Awards and Honors

Dr. Akoushideh has been recognized multiple times for his contributions to research and technology. He was awarded the Best Researcher title at Guilan Technical and Vocational University in 2022 and previously in 2018 and 2019. In 2021, he received the first award at the Technical and Vocational University of Iran, a national-level recognition of his excellence in research and academia. He was also acknowledged by the Guilan Science and Technology Park for his contributions as an innovator and technologist, winning awards such as “Encouraging Thinkers, Technologists, and Innovators” in 2019. Additionally, he won a provincial award in the Young Idea Supporters category the same year. His entrepreneurial spirit was recognized in 2007 when he was named the Best Entrepreneur in Information Technology by the Ministry of Labor and Social Affairs. His academic achievements include ranking second in his graduating class in electronic engineering at Guilan University in 1997. These awards highlight his dedication to advancing research, education, and innovation, further solidifying his reputation as a leading researcher in his field.

Conclusion

Dr. Alireza Akoushideh is a distinguished researcher with extensive expertise in electronics engineering, particularly in image processing, embedded systems, and IoT applications. His academic journey, spanning Iran’s top universities, has provided him with a strong foundation in both theoretical and applied research. His professional experience as a university professor, visiting researcher, and technology leader has allowed him to make significant contributions to academia and industry. With numerous research projects, patents, and international collaborations, he has established himself as a key figure in his field. His research interests in artificial intelligence, parallel processing, and industrial automation align with current technological advancements, making his work highly relevant. His technical skills in programming, hardware design, and system optimization further enhance his ability to develop innovative solutions. Recognized with multiple awards for research excellence, teaching, and entrepreneurship, he has consistently demonstrated his commitment to knowledge creation and dissemination. Dr. Akoushideh’s career reflects a balance between academic research and practical applications, positioning him as a thought leader in digital electronics and embedded systems. His contributions continue to drive technological innovation, benefiting both academia and industry.

Publications Top Notes

  • Title: Motion-based vehicle speed measurement for intelligent transportation systems
    Authors: A. Tourani, A. Shahbahrami, A. Akoushideh, S. Khazaee, C.Y. Suen
    Year: 2019
    Citations: 33

  • Title: A robust vehicle detection approach based on faster R-CNN algorithm
    Authors: A. Tourani, S. Soroori, A. Shahbahrami, S. Khazaee, A. Akoushideh
    Year: 2019
    Citations: 25

  • Title: Facial expression recognition using a combination of enhanced local binary pattern and pyramid histogram of oriented gradients features extraction
    Authors: M. Sharifnejad, A. Shahbahrami, A. Akoushideh, R.Z. Hassanpour
    Year: 2020
    Citations: 19

  • Title: Iranis: A large-scale dataset of Iranian vehicles license plate characters
    Authors: A. Tourani, S. Soroori, A. Shahbahrami, A. Akoushideh
    Year: 2021
    Citations: 16

  • Title: Iranian license plate recognition using deep learning
    Authors: A.R. Rashtehroudi, A. Shahbahrami, A. Akoushideh
    Year: 2020
    Citations: 15

  • Title: High performance implementation of texture features extraction algorithms using FPGA architecture
    Authors: A.R. Akoushideh, A. Shahbahrami, B.M.N. Maybodi
    Year: 2014
    Citations: 13

  • Title: Copy-move forgery detection using convolutional neural network and K-mean clustering
    Authors: A. Pourkashani, A. Shahbahrami, A. Akoushideh
    Year: 2021
    Citations: 12

  • Title: Accelerating texture features extraction algorithms using FPGA architecture
    Authors: A.R. Akoushideh, A. Shahbahrami
    Year: 2010
    Citations: 12

  • Title: Parallel Implementation of a Video-based Vehicle Speed Measurement System for Municipal Roadways
    Authors: A.J. Afshany, A. Tourani, A. Shahbahrami, S. Khazaee, A. Akoushideh
    Year: 2019
    Citations: 10

  • Title: Challenges of Video-Based Vehicle Detection and Tracking in Intelligent Transportation Systems
    Authors: A. Tourani, A. Shahbahrami, A. Akoushideh
    Year: 2017
    Citations: 9

 

Liangyu Yin | Artificial Intelligence | Best Researcher Award

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Dr. Liangyu Yin | Artificial Intelligence | Best Researcher Award

Research Professor at Xinqiao Hospital, Army Medical University, China

Dr. Liangyu Yin is an accomplished academic and researcher specializing in clinical nutrition, epidemiology, and artificial intelligence. He has made significant contributions to understanding cancer nutrition and malnutrition, particularly in oncology patients. His expertise spans the intersection of nutrition, cancer biology, and advanced machine learning methodologies. With numerous publications in prestigious journals such as Journal of Cachexia Sarcopenia Muscle, American Journal of Clinical Nutrition, and Clinical Nutrition, Dr. Yin is recognized as a thought leader in his field. He is currently a Research Professor at the Department of Nephrology, Xinqiao Hospital, Army Medical University, where he continues to advance research on cancer cachexia, nutritional interventions, and artificial intelligence applications. His work is aimed at improving patient outcomes, especially for cancer patients, by utilizing innovative research methods, including AI-driven diagnostics and predictive models for malnutrition and cancer prognosis.

Professional Profile

Education:

Dr. Liangyu Yin’s educational journey is marked by a strong foundation in medicine and nutrition. He earned his Ph.D. in Nutrition and Food Hygiene from Army Medical University in 2022, following a Master of Medicine in Nutrition and Food Hygiene from Chongqing Medical University in 2012. His academic journey began with a Bachelor of Arts degree in English, specializing in Biomedical English, from Chongqing Medical University. This diverse educational background has provided him with a robust understanding of both medical and nutritional sciences, which he applies in his research. His ongoing contributions reflect his dedication to bridging clinical nutrition with the latest advancements in artificial intelligence and cancer epidemiology.

Professional Experience:

Dr. Liangyu Yin’s professional experience spans several prestigious roles in academic research, clinical settings, and health science institutions. He currently serves as a Research Professor in the Department of Nephrology at Xinqiao Hospital, Army Medical University. Previously, he held positions as an Associate Research Professor at both Daping Hospital and Southwest Hospital within the Army Medical University, focusing on cancer epidemiology, nutrition, and artificial intelligence. Dr. Yin began his research career as a Research Assistant at the Institute of Hepatobiliary Surgery, Southwest Hospital, where he worked on cancer biology and non-coding RNA. His long-standing career at Army Medical University has contributed to the development of novel methodologies and interventions in clinical nutrition and cancer treatment. His expertise in epidemiology, nutrition, and AI has shaped the direction of his research in improving patient care outcomes.

Research Interests:

Dr. Liangyu Yin’s primary research interests lie at the intersection of clinical nutrition, cancer epidemiology, and artificial intelligence. His work focuses on understanding the role of malnutrition in cancer progression, with a particular emphasis on cancer cachexia, a complex metabolic syndrome associated with cancer. Dr. Yin is dedicated to developing predictive models and AI-driven solutions to identify and address malnutrition in cancer patients, improving patient outcomes and survival rates. His research also investigates non-coding RNA and its role in cancer biology, with a focus on its potential applications in cancer treatment. Through his interdisciplinary approach, combining machine learning with clinical nutrition, Dr. Yin aims to revolutionize cancer care by improving diagnosis, prognosis, and nutritional interventions in clinical practice.

Research Skills:

Dr. Liangyu Yin possesses a diverse set of research skills, enabling him to conduct cutting-edge investigations in the fields of clinical nutrition, cancer epidemiology, and artificial intelligence. His proficiency in utilizing machine learning models to predict and diagnose malnutrition in cancer patients demonstrates his technical expertise. Additionally, Dr. Yin’s deep understanding of cancer biology, especially cancer cachexia and non-coding RNA, is critical to his work. His research skills also extend to conducting large-scale cohort studies and multicenter analyses, as evidenced by his numerous publications. Moreover, his ability to integrate AI with clinical nutrition research allows him to pioneer innovative solutions in medical diagnostics and patient care, making him a leader in his field.

Awards and Honors:

Dr. Liangyu Yin has received numerous accolades and honors for his contributions to clinical nutrition and cancer research. His work has been consistently recognized in prestigious academic journals, and his research has influenced global medical practices regarding nutrition in cancer care. Dr. Yin’s expertise in combining artificial intelligence with nutrition science has earned him several recognitions for innovation in healthcare. He is a highly regarded researcher within the medical and scientific community, regularly invited to present his findings at international conferences and to collaborate on advanced research projects. His commitment to improving cancer patient outcomes through his interdisciplinary research has made him a prominent figure in his field.

Conclusion:

Liangyu Yin is an outstanding candidate for the Best Researcher Award. His research in clinical nutrition, cancer epidemiology, and the innovative use of artificial intelligence sets him apart as a leader in his field. His work has made significant strides in understanding malnutrition and cancer cachexia, with implications for improving patient care. By expanding the scope of his research and enhancing the real-world application of his findings, he has the potential to make an even greater impact on global health. Therefore, he is highly deserving of this award, and his future contributions will continue to shape the field of clinical nutrition and cancer care.

Publication Top Notes:

  1. Early prediction of severe acute pancreatitis based on improved machine learning models
    • Authors: Li, L., Yin, L., Chong, F., Wang, Y., Xu, H.
    • Journal: Journal of Army Medical University
    • Year: 2024
    • Volume: 46(7)
    • Pages: 753–759
  2. Association of possible sarcopenia with all-cause mortality in patients with solid cancer: A nationwide multicenter cohort study
    • Authors: Yin, L., Song, C., Cui, J., Shi, H., Xu, H.
    • Journal: Journal of Nutrition, Health and Aging
    • Year: 2024
    • Volume: 28(1)
    • Article ID: 100023
    • Citations: 3
  3. Comment on: “Triceps skinfold-albumin index significantly predicts the prognosis of cancer cachexia: A multicentre cohort study” by Yin et al. – the authors reply
    • Authors: Yin, L., Cui, J., Lin, X., Shi, H., Xu, H.
    • Journal: Journal of Cachexia, Sarcopenia and Muscle
    • Year: 2023
    • Volume: 14(6)
    • Pages: 2993–2994
  4. Comparison of the performance of the GLIM criteria, PG-SGA and mPG-SGA in diagnosing malnutrition and predicting survival among lung cancer patients: A multicenter study
    • Authors: Huo, Z., Chong, F., Yin, L., Shi, H., Xu, H.
    • Journal: Clinical Nutrition
    • Year: 2023
    • Volume: 42(6)
    • Pages: 1048–1058
    • Citations: 6
  5. Ensemble learning system to identify nutritional risk and malnutrition in cancer patients without weight loss information
    • Authors: Yin, L., Liu, J., Liu, M., Shi, H., Xu, H.
    • Journal: Science China Life Sciences
    • Year: 2023
    • Volume: 66(5)
    • Pages: 1200–1203
  6. Kruppel-like Factors 3 Regulates Migration and Invasion of Gastric Cancer Cells Through NF-κB Pathway
    • Authors: Liang, X., Feng, Z., Yan, R., Lu, H., Zhang, L.
    • Journal: Alternative Therapies in Health and Medicine
    • Year: 2023
    • Volume: 29(2)
    • Pages: 64–69
    • Citations: 1
  7. Triceps skinfold–albumin index significantly predicts the prognosis of cancer cachexia: A multicentre cohort study
    • Authors: Yin, L., Cui, J., Lin, X., Shi, H., Xu, H.
    • Journal: Journal of Cachexia, Sarcopenia and Muscle
    • Year: 2023
    • Volume: 14(1)
    • Pages: 517–533
    • Citations: 5

 

 

Fahd Alharithi | Artificial Intelligence | Best Researcher Award

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Assoc Prof Dr. Fahd Alharithi | Artificial Intelligence | Best Researcher Award

Department chair at Taif University, Saudi Arabia

Dr. Fahd Saad Alharithi is an accomplished researcher and academic with a Ph.D. in Computer Science from Florida Institute of Technology and extensive experience in both teaching and research. Currently an Assistant Professor at Taif University, his research spans a wide array of topics, including medical data categorization, oil spill detection, COVID-19 diagnosis, and IoT security. Dr. Alharithi has published numerous papers in high-impact journals such as Sensors and Remote Sensing, showcasing his innovative approaches and significant contributions to his field. In addition to his research, he has a strong background in teaching, having served as a lecturer and teaching assistant at various institutions. His involvement in volunteer work and leadership roles further highlights his commitment to community service. While his diverse research and impactful publications are noteworthy, highlighting research grants and awards could strengthen his profile for recognition.

Profile

Education

Dr. Fahd Saad Alharithi completed his educational journey with a strong foundation in Computer Science. He earned his Ph.D. from the Florida Institute of Technology, USA, in 2019, where he focused on advanced topics in the field. Prior to that, he obtained his Master of Science degree in Computer Science from the University of New Haven, USA, in 2013. His academic journey began with a Bachelor of Science degree in Computer Science from Taif University, Saudi Arabia, in 2008. This comprehensive educational background, spanning both international and local institutions, has equipped Dr. Alharithi with a robust theoretical and practical understanding of Computer Science, paving the way for his subsequent research and teaching career. His diverse educational experiences contribute significantly to his expertise and innovative approaches in the field.

Professional Experience

Dr. Fahd Saad Alharithi has garnered extensive experience in academia and education, currently serving as an Assistant Professor in the Computer Science Department at Taif University since 2019. His career began with roles as a Lecturer and Teacher Assistant at Taif University and the University of New Haven, where he honed his teaching and research skills. Dr. Alharithi has also contributed as a Trainer at New Horizons Institute, showcasing his versatility in the field. His professional journey is marked by significant research achievements, including innovative publications in medical data categorization, AI-assisted algorithms, and IoT security. His role extends beyond teaching, encompassing volunteer work with the Hemaya Group and leadership positions like President of the Saudi Student Club. Dr. Alharithi’s career reflects a robust blend of research excellence, educational dedication, and active community involvement.

Research Interest

Dr. Fahd Saad Alharithi’s research interests primarily focus on advancing computational methods and applications across various domains. His work explores medical data categorization using flexible mixture models, oil spill detection through SAR image analysis, and the development of hybrid convolutional neural network models for diagnosing diseases from chest X-ray images. Dr. Alharithi is also deeply involved in enhancing IoT security with AI-assisted bio-inspired algorithms and addressing environmental challenges through intelligent garbage detection systems. His research extends to secure communication protocols and energy-efficient solutions for sensor networks, demonstrating a strong emphasis on both practical and theoretical advancements. By integrating innovative methodologies such as deep learning and AI, Dr. Alharithi aims to address complex problems in medical imaging, environmental monitoring, and network security, reflecting a broad and impactful approach to computational science.

Research Skills

Dr. Fahd Saad Alharithi exhibits a robust set of research skills, underscored by his extensive work in computer science and related fields. His proficiency in advanced methodologies, including deep learning, AI-assisted algorithms, and hybrid models, highlights his capacity for innovative problem-solving. Dr. Alharithi’s experience with diverse data types and applications, such as medical data categorization, oil spill detection, and IoT security, demonstrates his ability to tackle complex, interdisciplinary challenges. His strong analytical skills are evident from his impactful publications in high-impact journals like Sensors and Remote Sensing. Additionally, his adeptness in leveraging various computational techniques and his commitment to exploring novel solutions further underscore his research capabilities. Dr. Alharithi’s contributions reflect a deep understanding of both theoretical and practical aspects of his field, positioning him as a skilled researcher with a significant impact on advancing technology and knowledge.

Award and Recognition

Dr. Fahd Saad Alharithi’s research has garnered considerable recognition within the academic community. He has published extensively in high-impact journals, including Sensors, Remote Sensing, and Computers, Materials & Continua, showcasing his significant contributions to fields such as medical data categorization, oil spill detection, and AI-assisted algorithms. His innovative work, particularly in developing hybrid convolutional neural network models and intelligent systems for garbage detection, underscores his leadership in advancing technology. Although specific awards and formal recognitions are not detailed in his resume, Dr. Alharithi’s influential publications and his role in mentoring and educating future researchers highlight his exceptional impact in computer science. His involvement in volunteer activities and community service further demonstrates his commitment to fostering academic and professional excellence.

Conclusion

Dr. Taimoor Asim is a strong candidate for the Best Researcher Award due to his substantial contributions to Mechanical Engineering, particularly in fluid dynamics and renewable energy systems. His extensive research experience, leadership roles, and professional achievements make him a noteworthy contender. To strengthen his candidacy, he could focus on broadening his research impact, exploring diverse research areas, and enhancing community engagement related to his work. Overall, Dr. Asim’s profile reflects a high level of expertise and dedication, aligning well with the criteria for the Best Researcher Award.

Publications Top Notes

  1. Machine learning approaches for advanced detection of rare genetic disorders in whole-genome sequencing
    • Authors: Alzahrani, A.A., Alharithi, F.S.
    • Journal: Alexandria Engineering Journal
    • Year: 2024
    • Volume: 106, pp. 582–593
  2. IoT-enabled healthcare systems using blockchain-dependent adaptable services
    • Authors: Arul, R., Alroobaea, R., Tariq, U., Alharithi, F.S., Shoaib, U.
    • Journal: Personal and Ubiquitous Computing
    • Year: 2024
    • Volume: 28(1), pp. 43–57
    • Citations: 13
  3. A comprehensive cost performance analysis for a QoS-based scheme in network mobility (NEMO)
    • Authors: Hussein, L.F., Abass, I.A.M., Aissa, A.B., Alzahrani, A.A., Alharithi, F.S.
    • Journal: Alexandria Engineering Journal
    • Year: 2023
    • Volume: 76, pp. 349–360
    • Citations: 1
  4. Performance Analysis of Machine Learning Approaches in Automatic Classification of Arabic Language
    • Authors: Alharithi, F.S.
    • Journal: Information Sciences Letters
    • Year: 2023
    • Volume: 12(3), pp. 1563–1578
    • Citations: 1
  5. A blockchain-based hybrid platform for multimedia data processing in IoT-Healthcare
    • Authors: Taloba, A.I., Elhadad, A., Rayan, A., Alharithi, F.S., Park, C.
    • Journal: Alexandria Engineering Journal
    • Year: 2023
    • Volume: 65, pp. 263–274
    • Citations: 74
  6. Optimal Sizing and Deployment of Renewable Energy Generators in Practical Transmission Network Using Grid-Oriented Multiobjective Harmony Search Algorithm for Loss Reduction and Voltage Profile Improvements
    • Authors: Kumar, P., Swarnkar, N.K., Mahela, O.P., Mazon, J.L.V., Alharithi, F.S.
    • Journal: International Transactions on Electrical Energy Systems
    • Year: 2023
    • Volume: 2023, 6315918
    • Citations: 1
  7. Energy-Aware Live VM Migration Using Ballooning in Cloud Data Center
    • Authors: Gupta, N., Gupta, K., Qahtani, A.M., Singh, A., Goyal, N.
    • Journal: Electronics (Switzerland)
    • Year: 2022
    • Volume: 11(23), 3932
    • Citations: 4
  8. NLP-Based Application for Analyzing Private and Public Banks Stocks Reaction to News Events in the Indian Stock Exchange
    • Authors: Dogra, V., Alharithi, F.S., Álvarez, R.M., Singh, A., Qahtani, A.M.
    • Journal: Systems
    • Year: 2022
    • Volume: 10(6), 233
    • Citations: 7
  9. Deep learned BLSTM for online handwriting modeling simulating the Beta-Elliptic approach
    • Authors: Hamdi, Y., Boubaker, H., Rabhi, B., Dhahri, H., Alimi, A.M.
    • Journal: Engineering Science and Technology, an International Journal
    • Year: 2022
    • Volume: 35, 101215
    • Citations: 6
  10. A software for thorax images analysis based on deep learning
    • Authors: Almulihi, A.H., Alharithi, F.S., Mechti, S., Alroobaea, R., Rubaiee, S.
    • Book Chapter: Research Anthology on Improving Medical Imaging Techniques for Analysis and Intervention
    • Year: 2022
    • Pages: 1166–1178