Avirup Roy | Machine Learning |Machine Learning Research Award

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Mr. Avirup Roy | Machine Learning |Machine Learning Research Award

PhD Student, Michigan State University, United States

Dr. Avirup Roy is a dedicated researcher and engineer specializing in networked embedded and wireless systems. Currently pursuing his PhD at Michigan State University, his work focuses on developing self-learning mechanisms for embedded hardware systems with limited computational resources. With a solid foundation in electronics and communication engineering, Avirup has gained extensive experience in both academia and industry, contributing to projects ranging from smart malaria detection to automated power management systems. His technical skills span machine learning, embedded systems, cloud computing, and web development. Beyond his professional life, Avirup is passionate about Indian classical music, photography, and swimming. 🌟📚🎵📷🏊‍♂️

Profile

ORCID

 

Education🎓

Michigan State University, East Lansing, MI, US PhD in Electrical and Computer Engineering (2020-Present). Dissertation: Self-learning mechanisms for Embedded hardware systems with limited computational resources. GPA: 3.75/4Maulana Abul Kalam Azad University of Technology, Kolkata, WB, India Bachelor of Technology (BTech) in Electronics and Communication Engineering (2013-2017)

Experience💼

Graduate Research Assistant, Michigan State University (Sep 2020 – Jul 2023),Developed an android and website application for smart malaria detection involving cloud database integration. Graduate Teaching Assistant, Michigan State University (Aug 2023 – Present), Instructed and graded labs for Embedded Cyber-physical Systems, VLSI Systems, and Digital Control courses. ICER Cloud Computing Fellow, Michigan State University (Sep 2023 – Present), Implemented Azure cloud resources in semi-supervised federated learning for embedded devices. Programmer Analyst, Cognizant Technology Solutions (Dec 2017 – Jul 2020), Developer and support analyst for ASP.NET based applications of MetLife Inc. Intern, Calcutta Electric Supply Corporation (CESC) Limited (Jul 2016 – Aug 2016), Worked on automated power management systems using SCADA communication. Intern, Bharat Sanchar Nigam Limited (BSNL) (Jun 2015 – Aug 2015), Explored general trends in wireless communication. Undergraduate Researcher, Maulana Abul Kalam Azad University of Technology (2015-2016), Presented research at various international conferences and served as the vice-president of SPIE Student Chapter.

Research Interests🔍

Embedded Machine Learning: Focused on developing efficient learning algorithms for resource-constrained devices.
Networked Embedded Systems: Exploring self-learning mechanisms and their applications in real-world scenarios.
Cloud Computing: Leveraging cloud resources for semi-supervised federated learning.
VLSI Systems: In-depth study and teaching of Very-Large-Scale Integration systems.
Cyber-Physical Systems: Research on embedded systems interacting with physical processes.

Awards🏆

National Social Entrepreneurship Programme (2014): Secured 2nd position for the ‘Hand-Made Paper Industry’ project.
SPIE Smart Structures and Non-destructive Evaluation Conference (2016): Presented research in Las Vegas, Nevada.
EAPE Conference (2015): Presented research on emerging areas of photonics and electronics.
Graduate Fellowships: Awarded multiple fellowships during PhD for research and teaching excellence.

Publications

Semi-Supervised Learning Using Sparsely Labelled Sip Events for Online Hydration Tracking Systems
A. Roy, H. Dutta, A. K. Bhuyan, and S. K. Biswas, 2023, International Conference on Machine Learning and Applications (ICMLA).
Cited by: 3 articles.

An On-Device Learning System for Estimating Liquid Consumption from Consumer-Grade Water Bottles and Its Evaluation
Roy, A., Dutta, H., Griffith, H., & Biswas, S., 2022, Sensors.
Cited by: 5 articles.

Hesham A. Sakr | Artificial Intelligence | Best researcher award

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Assist Prof Dr. Hesham A. Sakr | Artificial Intelligence | Best researcher award

Assistant professor, Assistant professor -Nile higher institute of engineering and technology -Mansoura -Egypt

📡 Hesham Ali Sakr is an Assistant Professor and Researcher specializing in Communication Networks and Cybersecurity. He earned his Ph.D. in Electrical, Electronics, and Communications Engineering from Mansoura University, Egypt. Dr. Sakr’s research focuses on optimizing wireless technologies for multimedia services, VoIP systems, and LTE-A networks. His contributions to the field are recognized through multiple publications in prestigious journals. He is actively involved in advancing the state-of-the-art in 5G and beyond communication technologies.

Profile

Google Scholar

 

Education

🎓 Ph.D. in Electrical, Electronics, and Communications Engineering
Mansoura University, Egypt (June 2016 – April 2020)
Thesis: Development of Accessing Multimedia Services over Wireless Technologies
GPA: 3.55/4

🎓 M.Sc. in Electrical, Electronics, and Communications Engineering
Mansoura University, Egypt (June 2010 – September 2014)
Thesis: Development of VoIP Systems using MPLS
GPA: 3.6/4

🎓 B.Sc. in Networks and Communications Engineering
Higher Technological Institute of Engineering, 10th of Ramadan, Egypt (September 2004 – August 2009)
Excellent with Honor Degree (84.9%)
Graduation Project Grade: Excellent

Experience

Specializing in Communication Networks and Cybersecurity, Dr. Sakr has significant academic and research experience. His work primarily focuses on enhancing wireless communication technologies, particularly in the realms of 5G and multimedia services. He has been affiliated with Mansoura University, contributing to various research projects and publications.

Research Interests

Dr. Sakr’s research interests encompass Communication Networks, Cybersecurity, and the development of efficient multimedia services over wireless technologies. His work includes performance evaluation of HARQ mechanisms, IPv6 multimedia management, and power-efficient mechanisms for LTE-A networks. He is particularly focused on optimizing handover management in LTE-A networks and evaluating VoIP versus VoMPLS performance.

Awards

Dr. Hesham Ali Sakr has been recognized for his outstanding contributions to the field of Communication Networks and Cybersecurity. His research achievements and academic excellence have earned him a commendable reputation among peers and colleagues in the industry.

Publications

📚 H.A. Sakr, and M.A. Mohamed, “Performance Evaluation Using Smart: HARQ Versus HARQ Mechanisms Beyond 5G Networks,” Wireless. Pers. Communication (Springer), June 2019. Cited by 26 articles

📚 Abeer Twakol Khalil, A. I. Abdel-Fatah and Hesham Ali Sakr, “Rapidly IPv6 multimedia management schemes based LTE-A wireless networks,” International Journal of Electrical and Computer Engineering (IJECE), vol. 9, no. 4, 2018. Cited by 32 articles

📚 H. A. Sakr, A. I. Abdel-Fatah, A. T. Khalil, “Performance Evaluation of Power Efficient Mechanisms on Multimedia over LTE-A Networks,” International Journal on Advanced Science, Engineering and Information Technology (IJASEIT), vol. 9, no. 4, 2019. Cited by 18 articles

📚 H.A. Sakr and M.A. Mohamed, “Handover Management Optimization over LTE-A Network using S1 and X2 handover,” Proc. of The Seventh International Conference on Advances in Computing, Electronics and Communication – ACEC 2018, 2018. Cited by 15 articles

📚 M. Abdel-Azim, M., Awad, M. M., & Sakr, H. A., “VoIP versus VoMPLS Performance Evaluation,” International Journal of Computer Science Issues (IJCSI), 11(1), 2014. Cited by 20 articles

GAN XU | Computer Science | Best Researcher Award

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Mr. GAN XU | Computer Science | Best Researcher Award

PhD. candidate, capital university of economics and business, China

Xu Gan is a Doctoral student at Capital University of Economics and Business, Beijing, specializing in Rural Finance, Financial Theory and Policy, and Supply Chain Finance. With a solid academic background and practical experience, Xu has contributed significantly to research in financial services and blockchain technology. 🏛️📚

Profile

Scopus

 

Education

Xu Gan completed a Master of Finance from Capital University of Economics and Business in Beijing (2018-2021) and a Bachelor of Biotechnology from Beijing Union University (2006-2010). Xu also has an extensive academic background in these fields, providing a strong foundation for research and analysis. 🎓📈

Experience

Xu has actively participated in several high-profile research projects, including the National Social Science Foundation of China’s research on rural financial services and the China Mobile Communication Federation’s blockchain technology applications in finance. Xu was responsible for designing research sub-topics and writing research reports. 📊🔬

Research Interests

Xu Gan’s research interests include Rural Finance, Financial Theory and Policy, and Supply Chain Finance. Xu is focused on improving rural financial services and exploring innovative financial technologies such as blockchain. 🌾💡

Awards

Xu has been recognized for academic excellence with several honors: Beijing Outstanding Graduates (2020), Outstanding Graduate of Beijing Union University (2020), and several awards for excellent papers at various financial and rural finance forums. 🏅📜

Publications

Yang, GZ., Xu, G., Zhang, Y., et al. Financial density of village banks and income growth of rural residents. Economic Issues, 2021, 504(08): 89-94.

Zhang, F., Xu, G., Zhang, XY, Cheng, X. Knowledge mapping analysis of seven decades of rural finance research in China. Rural Finance Research, 2020(01): 10-20.

Zhang, F., Xu, G., Cheng, X. A review of blockchain applications in the financial sector. Technology for Development, 2019, 15(08): 865-871.

Hafiza Sadia Nawaz | Computer Science | Women Researcher Award

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Dr. Hafiza Sadia Nawaz | Computer Science | Women Researcher Award

Shenzhen University, China

🎓 Dr. H. Sadia Nawaz is a distinguished researcher and academic in Computer Vision, with a Ph.D. from Ocean University of China. Her work focuses on Temporal Activity Detection using Natural Language. With a background in both teaching and research, she has contributed significantly to the field of computer vision and continues to pursue a career as a postdoctoral researcher. Her extensive knowledge and dedication to the subject make her a valuable asset to any research group.

Profile

Scopus

 

Education

📚 Dr. H. Sadia Nawaz holds a Ph.D. in Computer Science from Ocean University of China, specializing in Temporal Moment Localization using Natural Language. She also completed her Master’s in Information Science and Technology at the University of Sargodha and an MS in Computer Science and Technology with a focus on Cyber Security at the University of Lahore. Her academic background provides a strong foundation for her research and teaching roles.

Experience

💼 Dr. Nawaz has a robust teaching background, having served as a Programming Teaching Assistant at Heriot-Watt University and Ocean University of China, and as a Computer Science Lecturer at Superior University of Lahore and the University of Sargodha. Her roles in academia have honed her skills in teaching, mentoring, and research, contributing to her expertise in computer vision and machine learning.

Research Interests

🔍 Dr. Nawaz’s research interests include Activity Localization in Videos via Language, Temporal Moment Detection, and Natural Language Processing. She is particularly focused on moment detection in complex scenarios and the integration of machine learning methods with computer vision techniques to enhance video understanding and activity localization.

Awards

🏅 Dr. H. Sadia Nawaz has been recognized for her research contributions in the field of computer vision, particularly for her work on Temporal Moment Localization using Natural Language. Her research has been published in high-impact journals, reflecting her expertise and commitment to advancing the field.

Publications

Temporal Moment Localization via Natural Language by Utilizing Video Question Answers as a Special Variant and Bypassing NLP for Corpora

IVTEN – Integration of Visual-Textual Entities for Temporal Activity Localization via Language in Video

Revelation of Novel Paradigm in Temporal Moment Localization by Using Natural Language in Video

Multi-level Edges and Context Arranger Architecture Using Referencing Expressions for Temporal Moment Localization via Natural Language

A Frame-Based Feature Model for Violence Detection from Surveillance Cameras Using ConvLSTM Network

Gabriella d’Albenzio | Artificial Intelligence | Best Researcher Award

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Dr. Gabriella d’Albenzio | Artificial Intelligence | Best Researcher Award

Postdoc, Perk Lab Perk Lab Laboratory for Percutaneous Surgery, Canada

🎓 Gabriella d’Albenzio is a talented researcher with a focus on biomedical engineering and medical imaging. Currently pursuing a Ph.D. in Informatics at the University of Oslo, she has an impressive background in clinical engineering and biomedical engineering. Gabriella has worked on cutting-edge projects related to image-guided therapies and deep learning for medical applications, contributing significantly to her field through both research and development.

Profile

Scopus

 

Education

📚 Gabriella d’Albenzio holds a Ph.D. in Informatics from the University of Oslo (2021-2024). She completed her M.Sc. in Biomedical Engineering and B.Sc. in Clinical Engineering at Sapienza University of Rome, Italy, reflecting a solid foundation in both engineering and medical sciences.

Experience

💼 Gabriella d’Albenzio has extensive experience as a Scientific Software Developer at The Intervention Centre in Oslo, Norway, and as a Research Assistant at NTNU. She has also interned at the Rehabilitation Bioengineering Lab in Rome, contributing to various research projects involving advanced medical imaging and deep learning technologies.

Research Interests

🧠 Gabriella’s research interests are centered around enhancing surgical planning and medical imaging through deep learning and advanced computational techniques. Her work focuses on developing algorithms for medical image segmentation and predictive models for surgical outcomes, aiming to improve patient-specific treatment strategies.

Awards

🏅 Gabriella d’Albenzio has been recognized with the Globalink Research Internship by Mitacs, Canada, and a Grant Research Stay Abroad by The Research Council of Norway. These awards highlight her outstanding contributions to research and her commitment to advancing biomedical engineering.

Publications

Optimizing Surgical Plans for Parenchyma-Sparing Liver Resections through Contour-Guided Resection and Surface Approximation

Using NURBS for Virtual Resections in Liver Surgery Planning: A Comparative Usability Study

Patient-Specific Functional Liver Segments Based on Centerline Classification of the Hepatic and Portal Veins

ALive: Analytics for Computation and Visualization of Liver Resections

Laparoscopic Parenchyma-Sparing Liver Resection for Large (≥50 mm) Colorectal Metastases

Lourdes Swentek | Artificial Intelligence | Best Researcher Award

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Assist Prof Dr. Lourdes Swentek | Artificial Intelligence | Best Researcher Award

Academician/Research Scholar, UCI, United States

Dr. Lourdes Swentek is a highly accomplished trauma and critical care surgeon with extensive experience in surgical research and education. She completed her fellowship in Critical Care at the University of California, Irvine, and her residency in Surgery at Loma Linda University Health. Dr. Swentek has been recognized for her outstanding contributions to trauma and acute care surgery, earning numerous awards and accolades throughout her career. Her research interests focus on islet transplantation, oxidative stress in pancreatitis, and innovative surgical techniques.

Profile

Scopus

 

Education

🎓 Dr. Lourdes Swentek completed her Critical Care fellowship at the University of California, Irvine, and her Surgical Residency at Loma Linda University Health. She also served as a Research Resident in the Department of Surgery at the University of California, Irvine, where she focused on islet transplantation.

Experience

🔬 Dr. Lourdes Swentek’s professional journey includes a fellowship in Critical Care at the University of California, Irvine, and a surgical residency at Loma Linda University Health. She has significant research experience in islet transplantation and surgical innovation, having contributed to several impactful research projects and publications.

Research Interests

🧪 Dr. Lourdes Swentek’s research interests encompass islet transplantation, oxidative stress in pancreatitis, and the development of novel surgical techniques. Her work has contributed to advancing knowledge and improving practices in these areas, making a notable impact on the field of trauma and critical care surgery.

Awards

🏆 Dr. Lourdes Swentek has received numerous awards, including the East Oriens Award for her career in Trauma and Acute Care Surgery in 2018, the Highest Resident Absite Score at Loma Linda University Health in 2017, and the UCI School of Medicine Achievement Award for Clinical Science Lecturer in 2022. These accolades reflect her dedication and excellence in her field.

Publications

The Addition of a Nurse Practitioner to an Inpatient Surgical Team Results in Improved Utilization of Resources

Medium and Long-term Outcomes after Pneumatic Dilation or Laparoscopic Heller Myotomy for Achalasia: A Meta-analysis

Presentation, Diagnosis, and Treatment of Oesophageal Motility Disorders

Role of Oxidative Stress in the Pathogenesis of Pancreatitis: Effect of Antioxidant Therapy

Total Pancreatectomy and Islet Auto Transplantation for Chronic Pancreatitis

 

Ao Guo | Artificial Intelligence | Best Researcher Award

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Mr. Ao Guo | Artificial Intelligence | Best Researcher Award

Master’s student, Xinjiang University, China

📚 Ao Guo is a dedicated postgraduate researcher at Xinjiang University with a focus on the innovation, optimization, and application of object detection technology. Currently pursuing a master’s degree in Electronic Information, Ao Guo has a robust background in computer vision, deep learning, pattern recognition, and image processing. He is committed to enhancing the accuracy and efficiency of object detection algorithms, contributing to both academia and industry.

Profile

Google Scholar

 

Education

🎓 Master’s Degree in Electronic Information – Xinjiang University, Urumqi, China
Ao Guo is advancing his studies in Electronic Information, focusing on the intersection of computer vision and deep learning to address real-world problems.

Experience

Ao Guo has been deeply involved in research aimed at optimizing deep learning models for intelligent weed management in agricultural environments. His work on a lightweight weed detection model, which incorporates global contextual features, is recognized for its high detection speed and accuracy, particularly suited for resource-constrained edge devices.

Research Interests

Ao Guo’s research interests encompass weed detection, deep learning, YOLO (You Only Look Once) models, attention mechanisms, and the development of lightweight networks. His innovative approach to integrating global information capture mechanisms into detection algorithms stands out in his field.

Awards

Ao Guo’s contributions to the field have been acknowledged through his publications and patent. Notably, he has published a paper in the highly reputed journal “Engineering Applications of Artificial Intelligence,” and he holds a patent for a lightweight weed detection method and device.

Publications

A lightweight weed detection model with global contextual joint features. Engineering Applications of Artificial Intelligence, 136, 108903. Link – Cited by: Article on Engineering Applications of Artificial Intelligence.

Xiaohui Huang | Artificial Intelligence| Best Researcher Award

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Assoc Prof Dr. Xiaohui Huang | Artificial Intelligence| Best Researcher Award

Dean, East China jiaotong university, Japan

👨‍🏫 Dr. Xiaohui Huang is an Associate Professor at the School of Information Engineering, East China Jiaotong University. He earned his PhD from the School of Computer Science, Harbin Institute of Technology in November 2014. He has been a visiting scholar at the German Cancer Research Center and Nanyang Technological University. Dr. Huang has been leading several high-impact research projects funded by national and provincial bodies. He is an expert reviewer for various prestigious journals and a member of notable academic associations.

Profile

Scopus

 

Education

🎓 PhD in Computer Science, Harbin Institute of Technology, November 2014, German Cancer Research Center, December 2010 – October 2011, School of Computer Science and Engineering, Nanyang Technological University, November 2017 – November 2018

Experience

💼 Associate Professor, School of Information Engineering, East China Jiaotong University, January 2018 – Present
Lecturer, School of Information Engineering, East China Jiaotong University, December 2014 – December 2017
Visiting Scholar, Nuclear Medicine Research Group, German Cancer Research Center, December 2010 – October 2011
Software Engineer, Yichun Branch, China Telecom, August 2008 – February 2010

🔬 Research Interests

Deep Learning. Remote Image Analysis. Intelligent Transportation

🏆 Awards

Principal Investigator for various prestigious research projects including the National Natural Science Foundation of China and Jiangxi Province Natural Science Foundation.

 Publications

Multi-view dynamic graph convolution neural network for traffic flow prediction. Expert Systems With Applications, 2023 (SCI Zone 1 top)
Cited by: 15 articles

MAPredRNN: Multi-attention predictive RNN for traffic flow prediction by dynamic spatio-temporal data fusion. Applied Intelligence, 2023 (SCI Zone 2)
Cited by: 10 articles

SS-TMNet: Spatial–Spectral Transformer Network with Multi-Scale Convolution for Hyperspectral Image Classification. Remote Sensing, 2023 (SCI Zone 2, top)
Cited by: 8 articles

Multi-mode dynamic residual graph convolution network for traffic flow prediction. Information Sciences, 2022 (SCI Zone 1 top)
Cited by: 20 articles

A time-dependent attention convolutional LSTM method for traffic flow prediction.

Omar Soufi | Artificial Intelligence | Best Researcher Award

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Dr. Omar Soufi | Artificial Intelligence | Best Researcher Award

Doctorate, Mohammed V University of Rabat Mohammadia School of Engineering, Morocco

👨‍💼 Dr. Omar Soufi is a distinguished Computer Science Engineer specializing in Artificial Intelligence, Data Science, Remote Sensing, and Geographic Information Systems (GIS). With a robust background in data analysis and decision-support systems, Dr. Soufi excels in promoting organizational advancements and enhancing strategic performance through well-planned recommendations. His proactive and industrious approach ensures the achievement of objectives by leveraging data-driven insights.

Profile

ORCID

Education

🎓 Dr. Omar Soufi earned his Ph.D. in Computer Science Engineering with a focus on Artificial Intelligence from EMI Rabat in 2023, completing his doctoral research with the AMIPS/E3S team. He also holds a degree in Engineering from Polytechnique Grenoble, ENSIMAG, and EMI Rabat, specializing in Information Systems Engineering and Software Quality Engineering, respectively. His foundational studies include a Diploma and a Bachelor’s degree in Mechanical Engineering from ARM Merkèns.

Experience

💼 Dr. Soufi’s professional journey includes notable roles such as Project Manager in the IT Department, Team Leader at the Decision Support Center, Head of the BI & Decision Tools Department, Head of the Geomatics & Decision Tools Division, and AI Mission Manager. His expertise spans numerous projects in artificial intelligence and data science, including the development of national geospatial platforms, disaster risk management systems, and SaaS solutions for real estate asset management and financial risk analysis.

Research Interests

🔍 Dr. Soufi’s research focuses on applying deep learning techniques to satellite image super-resolution and spacecraft attitude control. His interests extend to big data architecture, distributed systems, and geospatial data analysis, aiming to enhance the accessibility and quality of high-resolution satellite imagery.

Awards

🏆 Dr. Soufi has been recognized for his contributions to artificial intelligence and remote sensing. He has received certifications in various professional and personal development areas, including PMO, coaching, and personal development, further solidifying his expertise and commitment to excellence in his field.

Publications

📄 Study of deep learning-based models for single image super-resolution. Soufi, O., Belouadha, F.Z. (2022). Revue d’Intelligence Artificielle, Vol. 36, No. 6, pp. 939-952. https://doi.org/10.18280/ria.360616

📄 FSRSI: New deep learning-based approach for super-resolution of multispectral satellite images. Soufi, O., Belouadha, F.Z. (2023). Ingénierie des Systèmes d’Information, Vol. 28, No. 1, pp. 113-132. https://doi.org/10.18280/isi.280112

📄 Deep learning technique for image satellite processing. O. Soufi and F.Z- Belouadha. Intell Methods Eng Sci, vol. 2, no. 1, pp. 27–34, Mar. 2023.

📄 Enhancing Accessibility to High-Resolution Satellite Imagery: A Novel Deep Learning-Based Super-Resolution Approach. O. Soufi and F.Z- Belouadha. Journal of Environmental Treatment Techniques, 11(2), 44-49, 2023.

📄 An intelligent deep learning approach to spacecraft attitude control: the case of satellites. O. Soufi and FZ.- Belouadha. (2023). (Under Review)

Narmilan Amarasingam | Artificial Intelligence | Best Researcher Award

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Mr. Narmilan Amarasingam | Artificial Intelligence | Best Researcher Award

PhD student, Queensland University of Technology, Australia

Researcher specializing in drone-based remote sensing solutions for environmental and surveillance needs, focusing on precision agriculture and biosecurity. Expertise includes UAV remote sensing, artificial intelligence, and multispectral/hyperspectral image processing. Currently pursuing a PhD in Precision Agriculture at Queensland University of Technology.

Profile

Google Scholar

 

🎓 Education

PhD: Precision Agriculture, Queensland University of Technology (2021 – Present). MSc: Agricultural Engineering, Eastern University, Sri Lanka (2016 – 2018). BSc: Agriculture, Agricultural Engineering, Eastern University, Sri Lanka (2010 – 2015). BIT: Software Engineering, University of Colombo School of Computing, Sri Lanka (2011 – 2015)

🔍 Experience

Research Assistant at Charles Sturt University and Sunshine Coast Council on projects integrating AI and drone technology for environmental monitoring and invasive species detection.

🏆 Awards

QUT/Accelerate Higher Education Development Expansion and Development (AHEAD) World Bank Project Scholarship. Vice Chancellor’s Award for Early Career Researcher, Faculty of Technology, 2022.

🌍 Research Interests

Precision Agriculture, UAV-based Remote Sensing, Multispectral Image Processing, AI, Biosystems Engineering, Environmental Management.

📚 Publications

Co-authored numerous peer-reviewed articles in Q1 and non-Q1 ranking journals on topics related to UAV-based remote sensing and AI applications in agriculture and environmental management.

A review of UAV platforms, sensors, and applications for monitoring of sugarcane crops
Predicting canopy chlorophyll content in sugarcane crops using machine learning algorithms and spectral vegetation indices derived from UAV multispectral imageryDetection of white leaf disease in sugarcane using machine learning techniques over UAV multispectral images
Detection of White Leaf Disease in Sugarcane Crops Using UAV-Derived RGB Imagery with Existing Deep Learning Models
N Amarasingam, F Gonzalez, ASA Salgadoe, J Sandino, K Powell
E-agricultural concepts for improving productivity: A review