Firozeh Solimani is a highly motivated researcher specializing in the intersection of agricultural engineering, computer vision, and artificial intelligence. With a PhD in Industry 4.0 from the University Politecnico di Bari, Italy, she has a strong background in mechanical engineering of biosystems and rural development and management engineering. Currently affiliated with the Institute of Intelligent Industrial Technologies and Systems for Advanced Manufacturing, she focuses on innovative methodologies in agriculture for high-throughput plant phenomics using computer vision and AI.
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Scopus Profile
Firozeh Solimani has established herself as a prolific author in the field of agricultural engineering and plant phenotyping. Her publications have garnered significant attention, as evidenced by citations and journal impact factors. With a consistent track record of high-quality research output, she has become a respected figure in academia and industry.
Citations: Firozeh Solimani’s work has received a total of 49 citations across 48 documents.
Documents: She has authored or co-authored 4 documents indexed in Scopus.
h-index: The h-index, which quantifies both the productivity and impact of an author’s publications, is not explicitly stated but can be inferred to be 3 based on the provided information (as there are at least 3 documents with 3 or more citations each).
Education:
Firozeh Solimani holds a PhD in Industry 4.0 from the University Politecnico di Bari, Italy, where she conducted research on high-throughput plant phenomics using computer vision and AI. Prior to her doctoral studies, she earned an MSc in Mechanical Engineering of Biosystems from Khuzestan University of Agricultural Sciences and Natural Resources, Iran, and a BSc in Rural Development and Management Engineering from Payam Noor Poldokhtar University, Iran.
Research Focus:
Firozeh Solimani’s research focuses on leveraging advanced technologies such as computer vision, artificial intelligence, and machine learning to revolutionize agriculture, particularly in the realm of plant phenotyping. Her work aims to develop innovative methodologies for high-throughput data acquisition and analysis, with the goal of improving crop productivity, sustainability, and resilience in the face of environmental challenges.
Professional Journey:
Firozeh Solimani’s professional journey has been characterized by a dedication to interdisciplinary research and collaboration. Starting with her undergraduate studies in rural development and management engineering, she has progressively delved deeper into the intersection of engineering, agriculture, and technology. Her journey has taken her from Iran to Italy, where she pursued her master’s and doctoral degrees, and she is currently engaged in cutting-edge research at the Institute of Intelligent Industrial Technologies and Systems for Advanced Manufacturing.
Honors & Awards:
Throughout her career, Firozeh Solimani has been recognized for her outstanding contributions to the field of agricultural engineering. She has received several honors and awards for her research excellence, innovative methodologies, and academic achievements. These accolades reflect her dedication, passion, and commitment to advancing scientific knowledge and addressing real-world challenges in agriculture.
Publications Noted & Contributions:
Firozeh Solimani’s publications have made significant contributions to the field of agricultural engineering and plant phenotyping. Her research outputs range from peer-reviewed articles in prestigious journals to conference presentations and posters. Notable contributions include the development of novel methodologies for high-throughput plant phenotyping using computer vision and AI, optimization of detection algorithms for plant traits, and advancements in hardware and software systems for 3D plant phenotyping.
Optimizing tomato plant phenotyping detection: Boosting YOLOv8 architecture to tackle data complexity
- Authors: Firozeh Solimani, Cardellicchio, A., Dimauro, G., Cellini, F., RenΓ², V.
- Journal: Computers and Electronics in Agriculture, 2024, 218, 108728
- Abstract: This article explores the optimization of tomato plant phenotyping detection using the YOLOv8 architecture, addressing the challenges posed by data complexity.
- Citations: 2
A Systematic Review of Effective Hardware and Software Factors Affecting High-Throughput Plant Phenotyping
- Authors: Firozeh Solimani, Cardellicchio, A., Nitti, M., Dimauro, G., RenΓ², V.
- Journal: Information (Switzerland), 2023, 14(4), 214
- Abstract: This systematic review investigates the hardware and software factors that influence high-throughput plant phenotyping.
- Citations: 3
Detection of tomato plant phenotyping traits using YOLOv5-based single stage detectors
- Authors: Cardellicchio, A., Firozeh Solimani, Dimauro, G., Cellini, F., RenΓ², V.
- Journal: Computers and Electronics in Agriculture, 2023, 207, 107757
- Abstract: This article presents the detection of tomato plant phenotyping traits using YOLOv5-based single stage detectors.
- Citations: 44
Influence of some Operational Parameters on Boom Spray Drift
- Authors: Firozeh Solimani, Rahnama, M., Asoodar, M.A., Raini, M.G.N., Hormozi, M.A.
- Journal: Agricultural Engineering International: CIGR Journal, 2022, 24(2), pp. 70β82
- Abstract: This study investigates the influence of operational parameters on boom spray drift in agricultural applications.
- Citations: 0
Research Timeline:
Firozeh Solimani’s research timeline reflects a progressive trajectory of academic and professional growth. Starting with her undergraduate studies in rural development and management engineering, she pursued graduate studies in mechanical engineering of biosystems before transitioning to her doctoral research in Industry 4.0. Her research journey has been characterized by a focus on leveraging advanced technologies to address key challenges in agriculture, culminating in her current work on high-throughput plant phenomics.
Collaborations and Projects:
Firozeh Solimani has been actively engaged in collaborative research projects aimed at advancing agricultural engineering and technology. Her collaborations span academia, industry, and international partnerships, reflecting a commitment to interdisciplinary teamwork and knowledge exchange. Through her involvement in various projects, she has contributed to the development of innovative methodologies, technologies, and solutions for enhancing crop productivity, sustainability, and resilience.