Prof. Velislava Lyubenova | Online Monitoring Awards | Best Researcher Award

Prof. Velislava Lyubenova | Online Monitoring Awards | Best Researcher Award

Prof. Velislava Lyubenova, Bulgarian Academy of Science, Bulgaria

Professor Velislava Noreva Lyubenova is a distinguished Bulgarian researcher in the field of biotechnological systems and process control. Currently serving as the Scientific Secretary of the Institute of Robotics at the Bulgarian Academy of Sciences (IR-BAS), she also leads the Section of Mechatronic Bio/Technological Systems. With over three decades of research experience, she holds two doctoral degrees, including a Doctor of Technical Sciences, and has developed innovative methodologies for the monitoring and adaptive control of biotechnological processes. Professor Lyubenova has led or participated in more than 30 national and international research projects, including EU-funded Erasmus and Structural Fund programs. She has supervised multiple PhD students, delivered invited lectures at prestigious institutions globally, and published over 200 papers in high-impact journals. Her notable accolades include the “Marin Drinov” Young Scientist Award from BAS and memberships in international scientific organizations. A skilled communicator and academic leader, she continues to advance interdisciplinary research in bioengineering and control systems.

Professional Profile:

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Summary of Suitability for Best Researcher Award – Prof. Velislava Noreva Lyubenova

Prof. Velislava Noreva Lyubenova exemplifies the qualities of a top-tier candidate for the Best Researcher Award, with over three decades of sustained excellence in biotechnological process monitoring and control, and a robust leadership profile in national and international R&D projects. With dual doctoral degrees (Ph.D. and Doctor of Technical Sciences) and a long-standing affiliation with the Bulgarian Academy of Sciences, she has led or participated in over 29 major research projects—spanning EU programs, Structural Funds, and academic exchanges.

🎓 Education & Qualifications

  • 🧠 Doctor of Technical Sciences, Institute of Robotics – BAS (2016)

  • 🎓 Ph.D. in Technical Sciences, TU-Sofia (1988–1993) – Dissertation on parameter estimation and state variables in biotechnological processes

  • 📡 Radio Electronics Engineer, TU-Sofia, Faculty of Radioelectronics (1982–1987)

💼 Work Experience

  • 👩‍🔬 Scientific Secretary, Institute of Robotics – BAS & Member of PNEC Technical Sciences (2022–present)

  • 👩‍🏫 Professor & Head, Section “Mechatronic Bio/technological Systems”, IR-BAS (2017–present)

  • 🧪 Associate Professor, Bioengineering, ISRI-BAS (2015–2016)

  • 🧬 Associate Professor, Section “Bioengineering”, ISIR-BAS (2010–2015)

  • 🤖 Associate Professor, Adaptive & Robust Control Section, IUSI-BAS (2005–2010)

  • 🧠 Associate Professor, Knowledge-Based Management Systems, IUSI-BAS (2000–2005)

  • 🔬 Research Fellow, Adaptive Control & Knowledge-Based Systems, IUSI-BAS (1994–2000)

  • 👩‍💻 Research Fellow, Adaptive Control Section, Bioprocessing & Automation, BAS (1992–1994)

🏆 Achievements

  • 🧪 Developed innovative technologies for monitoring and control of biotechnological processes

  • 📊 Led and participated in over 29 projects (15 international, 14 national)

  • 🧑‍🏫 Supervised 3 Ph.D. students (2 completed, 1 ongoing)

  • 🖥️ Expert in MATLAB, LABVIEW, and Microsoft Office for biotechnological control systems

  • 🌍 Delivered 21 invited lectures (15 abroad, 6 in Bulgaria)

  • 📚 Published 200+ papers, many in high-impact journals like AIMS Bioengineering and Engineering in Life Sciences

🥇 Awards & Honors

  • 🏅 Marin Drinov Young Scientist Award, General Assembly of BAS (1998)

  • 🧬 Reviewer for major journals: Journal of Bioprocess and Biosystems Engineering, Processes, etc.

  • 📝 Editorial Board Member of multiple peer-reviewed journals

  • 🧑‍🔬 Member of multiple scientific and expert committees at BAS (including examination and academic jury panels)

  • 🌐 Member of 2 international and 1 national scientific organizations

Publication Top Notes:

A System Designed for Modelling, Monitoring, and Control of Fermentation Processes, Powered by Metaheuristic Algorithms

Contemporary Bioprocesses Control Algorithms for Educational Purposes

Simultaneous State and Kinetic Observation of Class-Controllable Bioprocesses

Escherichia coli cultivation process modelling using abc-ga hybrid algorithm

Investigation of fermentation regimes for the production of low-alcohol and non-alcohol beers

Metaheuristic Algorithms: Theory and Applications

Model-based monitoring of biotechnological processes-a review

Mr. Liang Peng | Tracking | Best Researcher Award

Mr. Liang Peng | Tracking | Best Researcher Award

Mr. Liang Peng, Yangtze University, China

Peng Liang is a dedicated researcher in the field of computer vision and deep learning, currently pursuing a Master’s degree through a joint training program between Yangtze University and the Institute of Software at the Chinese Academy of Sciences. He holds a Bachelor’s degree in Software Engineering from Fuyang Normal University. His research focuses on object tracking, detection, and medical image analysis. Peng has led several high-impact projects, including VastTrack—an industry-leading visual object tracking dataset accepted at NeurIPS 2024—and developed advanced algorithms for product detection and video text spotting. He has interned at Pengcheng Laboratory and the Institute of Software, contributing to algorithm migration and medical imaging research. Proficient in Python, Java, PyTorch, and Linux, he has authored multiple software copyrights and received numerous academic and technical awards, including scholarships, innovation project leadership roles, and national competition prizes. Peng also shares his knowledge widely through his blog, which has gained over 500,000 views. He is recognized for his strong problem-solving ability, technical expertise, and leadership in collaborative research environments.

Professional Profile:

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🎓 Education

  • Master’s Degree (Joint Training Program)
    Yangtze University & Institute of Software, Chinese Academy of Sciences (Sep 2022 – Jun 2025)

    • GPA: 3.43 / 4.0

    • Research Interests: Deep Learning, Computer Vision, Object Tracking, Object Detection

    • Relevant Courses: Data Structures (90), Algorithm Design (96), Data Mining (97), Operating Systems (90), Design Patterns (97), Probability Theory (95), UML Modeling (98)

  • Bachelor’s Degree in Software Engineering
    Fuyang Normal University (Sep 2017 – Jun 2021)

💼 Work Experience

  • Algorithm Intern — Pengcheng Laboratory (May 2022 – Dec 2022)

    • Migrated ByteTrack (multi-object tracking algorithm) from PyTorch to MindSpore framework

    • Reconstructed and optimized algorithm to maintain performance and accuracy

    • Shared code/documentation on GitHub for cross-framework migration

  • Algorithm Intern — Institute of Software, Chinese Academy of Sciences (Sep 2020 – Sep 2023)

    • Collaborated on medical imaging project with Fuwai Hospital

    • Developed 3D U-Net ventricular segmentation model for cardiac CT sequences

    • Designed abnormal ventricular diagnosis algorithm with clinically validated accuracy

🏆 Achievements & Awards

  • 2024 University Third Prize Scholarship

  • 2023 University Second Prize Scholarship

  • 2023 MindSpore Active Contributor

  • 2022-2023 First author on three software copyright applications

  • 2021 “Three Good Student” Award

  • 2020 First Prize Scholarship & National Encouragement Scholarship, “Three Good Student”

  • 2019 First Prize, Anhui Province Big Data and AI Application Competition

  • 2019 Second Prize, Anhui Province Blue Bridge Cup Java Group

  • 2019 Third Prize, Anhui Province AI Solution Design, Chinese University Student Design Competition

  • 2019 Third Prize, Anhui Province Big Data Application, Chinese University Computer Design Competition

  • 2019 “Three Good Student” Honor & First Prize Scholarship

  • 2018 Second Prize, Anhui Province Big Data and AI Application Competition

Publication Top Notes:

CITED:15

Prof. Dr. Len Gelman | Monitoring | Best Researcher Award

Prof. Dr. Len Gelman | Monitoring | Best Researcher Award 

Prof. Dr. Len Gelman, The University of Huddersfield, United Kingdom

Professor Len Gelman is a distinguished academic and researcher in the fields of Signal Processing, Condition Monitoring, and Maintenance. He holds a PhD and Doctor of Science (Habilitation) degrees and is a Fellow of several prestigious institutions, including the British Institute of Non-Destructive Testing (BINDT), IAENG, IDE, and HEA. Since 2017, Professor Gelman has served as the Professor and Chair in Signal Processing and Condition Monitoring/Maintenance at the University of Huddersfield, where he is also the Director of the Maintenance Centre for Efficiency and Performance Engineering. Prior to this, he was a Professor at Cranfield University (2002-2017), where he established a leading research programme in vibro-acoustical condition monitoring. Professor Gelman has received numerous accolades, including the UK Rolls-Royce Innovation Award (2019), the COMADIT Prize (2017), and the Best Paper Award at the International Condition Monitoring/Maintenance Conference (2016 and 2013). With extensive experience in both academia and industry, he has developed pioneering technologies for damage detection in turbines and aircraft engines, with significant contributions to Rolls-Royce, Dresser-Rand, and Scottish Southern Energy. Professor Gelman has built strategic international partnerships with top universities and research centres across the globe, including institutions in China, Korea, the USA, and Europe. He has supervised numerous postdoctoral fellows and researchers and is renowned for his leadership in vibro-acoustical condition monitoring, a field in which he has secured over £7.3M in research grants.

Professional Profile:

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Summary of Suitability for Best Researcher Award

Professor Len Gelman is an outstanding researcher whose extensive contributions to signal processing, condition monitoring, and maintenance engineering position him as a leading figure in his field, making him an ideal candidate for the Best Researcher Award. His innovative work has consistently benefited both industry and society, earning him significant recognition and awards.

Education 🎓

  • BSc (Hons), MSc (Hons) in Signal Processing and Condition Monitoring/Maintenance

  • PhD, Doctor of Science (Habilitation) in Vibro-Acoustical Monitoring/Maintenance

Work Experience 💼

  • 2017-present
    Professor and Chair in Signal Processing and Condition Monitoring/Maintenance
    Director of the Maintenance Centre for Efficiency and Performance Engineering
    University of Huddersfield, UK

  • 2002-2017
    Professor and Chair in Vibro-Acoustical Monitoring/Maintenance
    Cranfield University, UK

Achievements 🏆

  • Led research in condition monitoring and maintenance for complex systems.

  • Built the novel “Vibro-acoustical condition monitoring of complex mechanical systems” research program at Cranfield University.

  • Recruited over 90 MSc students from various international universities for MSc studies at Cranfield.

  • Successfully gained £7.3M in research grants for research projects involving leading companies like Rolls-Royce, Caterpillar, and Shell.

  • Established strategic international partnerships with world-class universities and research centres around the globe. Monitoring

Awards and Honors 🥇

  • UK Rolls-Royce Innovation Award (2019)

  • COMADIT Prize for significant contributions to condition monitoring/maintenance (2017)

  • Rolls-Royce Engineering Award for Innovation (2012)

  • EC Fellowship Award (2015) – European Social Fund-Human Capital Operational Programme

  • Oxford Academic Health Science Network Award (2014)

  • Best Paper Award at CM/MFPT 2016 and CM/MFPT 2013

  • William Sweet Smith Prize from the UK Institution of Mechanical Engineers (2010)

  • USA Navy Award for helicopter fault diagnosis methodologies (1998)

  • Acoustical Society of America Award (1998)

Professional Recognition 🌟

  • Chairman of several international committees, including:

    • International Institute of Acoustics and Vibration (USA) (2014-2016)

    • International Society for Condition Monitoring/Maintenance (2011-2017)

    • European Federation of NDT (2014-present)

  • Editorial Board Member for renowned journals:

    • “Insight” NDT and Condition Monitoring

    • “Electronics” (MDPI)

    • “Energies” (MDPI)

    • “Prognostics and Health Management”

    • IEEE Fellow (Recognized as a leading professional in the field)

Publication Top Notes:

Novel Investigation of Influence of Torsional Load on Unbalance Fault Indicators for Induction Motors

Vibration analysis of rotating porous functionally graded material beams using exact formulation

Novel instantaneous wavelet bicoherence for vibration fault detection in gear systems

Novel prediction of diagnosis effectiveness for adaptation of the spectral kurtosis technology to varying operating conditions

Vibration health monitoring of rolling bearings under variable speed conditions by novel demodulation technique

Novel fault identification for electromechanical systems via spectral technique and electrical data processing

Novel method for vibration sensor-based instantaneous defect frequency estimation for rolling bearings under non-stationary conditions

Novel higher-order spectral cross-correlation technologies for vibration sensor-based diagnosis of gearboxes

Novel vibration structural health monitoring technology for deep foundation piles by non-stationary higher order frequency response function

 

Prof. Mehdi Behzad | Monitoring | Lifetime achievement Award

Prof. Mehdi Behzad | Monitoring | Lifetime achievement Award 

Prof. Mehdi Behzad, Sharif University of Technology, Iran

Professor Mehdi Behzad is a distinguished academic and expert in mechanical engineering at the Sharif University of Technology, Tehran, Iran. He earned his Ph.D. from the University of New South Wales, Australia, in 1995, with a specialization in rotor dynamics and coupled vibrations. With over three decades of academic and industrial experience, Professor Behzad has led pioneering research in vibration analysis, condition monitoring, and fault diagnostics of rotating machinery. He has supervised more than 90 M.Sc. and 11 Ph.D. theses, contributed extensively to national industrial projects, and developed intelligent software solutions for signal processing and machinery health assessment. His professional service includes chairing major national conferences on condition monitoring and maintenance, as well as delivering keynote lectures at international forums such as the CM2024 in Oxford, UK. Professor Behzad’s contributions span academic teaching, applied research, and industrial consultancy, making him a leading figure in the field of vibration analysis and mechanical systems diagnostics.

Professional Profile:

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Summary of Suitability for Lifetime Achievement Award

Prof. Mehdi Behzad is a distinguished academic and industry expert whose lifelong dedication to mechanical engineering, particularly in the field of vibration analysis and rotor dynamics, exemplifies the qualities honored by the Lifetime Achievement Award. His career spans over three decades of impactful teaching, groundbreaking research, industrial collaboration, and academic leadership.

👨‍🎓 Education

📍 Ph.D. in Mechanical Engineering
University of New South Wales, Sydney, Australia – May 1995

  • 🌀 Thesis: Transfer matrix analysis of rotor systems with coupled lateral and torsional vibrations

  • 🧮 Courses: Finite elements, vibration, frequency analysis, lubrication

  • 🧑‍💻 Developed vibration analysis software using Riccati transfer matrix

  • 📄 Published 3 papers on rotor dynamics

📍 M.Sc. in Mechanical Engineering
Sharif University of Technology, Tehran, Iran – May 1989

  • 📘 Thesis: Transfer Function and stability of electrohydraulic servo systems

  • 🧪 Repaired an electrohydraulic servo system for experiments

  • 📚 Advanced studies in control, dynamics, nonlinear vibration

📍 B.Sc. in Mechanical Engineering
Isfahan University of Technology, Iran – Feb 1986

  • 🔧 Broad mechanical engineering training including dynamics, turbomachinery, heat transfer

🧑‍🏫 Academic & Teaching Experience

📍 Professor – Sharif University of Technology (1994–2025)

  • 👨‍🔬 Supervised 90+ M.Sc. and 11 Ph.D. theses

  • 📘 Taught undergrad & grad courses in vibration, rotor dynamics, control, mathematics

  • 🛠 Developed curricula & practical labs

  • 🧑‍🏭 Founded training centers, oversaw solid mechanics lab & naval division

  • 📜 Organized nationwide Condition Monitoring & Fault Diagnosis conference (2007–2024)

🧪 Research & Industrial Experience

📍 University of New South Wales (1990–1995)

  • 📊 Built and used data acquisition systems

  • 🔁 Solved numerical issues in transfer matrix methods

  • 📝 Wrote reports for Sydney Electricity & Pacific Power

📍 Sazeh Consultant, Tehran (1988–1990)

  • 🛠 Vibration analysis for industrial structures

  • 🧾 Created guidelines for thermal stress, piping design, and actuator testing

📍 Industrial Consultant (1996–2024)

  • 🏭 Completed 50+ major vibration and condition monitoring projects

  • 🔍 Diagnosed faults in turbines, compressors, cement mills, pumps, and more

  • 🖥 Developed intelligent diagnostic software

  • 🌊 Assessed vibration in hydropower & petrochemical plants

  • 🚂 Involved in projects with railways, powerplants, and petrochemical complexes

🏆 Achievements, Awards & Honors

🎤 Keynote & Invited Speaker

  • 📍 20th International Conference on Condition Monitoring and Asset Management (CM2024), Oxford, UK

    • 🗣 “Challenges in Condition Monitoring”

    • 🎙 “Vibration Features for Machinery Condition Monitoring”

🏅 Leadership Roles

  • 🎖 Chairman of Iran Maintenance Association (2007–2012)

  • 🧩 Research Deputy, Sharif University – Mechanical Eng. Dept.

  • 🎓 Director, University Center for Training (since 2010)

📘 Curriculum Innovator & Educator

  • 🛠 Founded and led numerous industrial courses & workshops on:

    • Vibration Analysis Levels 1 & 2

    • Rotor Dynamics

    • API 687 Repair Technologies

    • Reliability Centered Maintenance

    • Shaft Alignment

Publication Top Notes:

CITED:219
CITED:118
CITED:103
CITED:73
CITED:66
CITED:65

Dr. Yue Wang | Sensor development Award | Best Researcher Award

Dr. Yue Wang | Sensor development Award | Best Researcher Award 

Dr. Yue Wang, University of Science and Technology Liaoning, China

Dr. Yue Wang is an Associate Professor at the School of Chemical Engineering at the University of Science and Technology Liaoning in China. He earned his Bachelor’s degree from the University of Science and Technology Anshan and both his Master’s and Doctorate degrees from the University of Science and Technology Liaoning and Saitama Institute of Technology, Japan, respectively. Since joining the University of Science and Technology Liaoning in 2006, Dr. Wang has focused his research on sensors and biosensors, biofuel cells, supercapacitors, energy harvesting, and artificial muscles. His work has resulted in over 60 published scientific papers, garnering approximately 600 citations, reflecting his significant contributions to the field. Dr. Wang has secured multiple research grants from various institutions, including the Education Department of Liaoning Province and the Natural Science Foundation of Liaoning Province, to advance his projects on conductive sensors, pesticide sensors, electrochemical biosensors, and wearable smart sensing technologies. Additionally, he completed a visiting scholarship at the University of Texas at Dallas in 2019-2020, further enhancing his academic and research expertise.

Professional Profile:

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Summary of Suitability for Best Researcher Award: Yue Wang

Yue Wang is an exemplary candidate for the Best Researcher Award, primarily due to his substantial academic qualifications, extensive research contributions, and impactful work in the field of Material Science, specifically within sensor and biosensor technologies.

Education

  • Bachelor’s Degree in Material Science
    University of Science and Technology Anshan, China
    September 1998 – July 2002
  • Master’s Degree in Material Science
    University of Science and Technology Liaoning, China
    September 2003 – March 2006
  • Ph.D. in Material Science
    Saitama Institute of Technology, Japan
    April 2008 – March 2011

Work Experience

  • Associate Professor
    University of Science and Technology Liaoning, China
    April 2006 – Present
  • Visiting Scholar
    University of Texas at Dallas
    April 2019 – March 2020

Publication top Notes:

A carbon black–doped chalcopyrite–based electrochemical sensor for determination of hydrogen peroxide

Glucose oxidase, horseradish peroxidase and phenothiazine dyes-co-adsorbed carbon felt-based amperometric flow-biosensor for glucose

Crab gill–derived nanorod-like carbons as bifunctional electrochemical sensors for detection of hydrogen peroxide and glucose

Cellulose-derived hierarchical porous carbon based electrochemical sensor for simultaneous detection of catechol and hydroquinone

A triphenylamine based fluorescent probe for Zn2+ detection and its applicability in live cell imaging

1,8-naphthalimide-triphenylamine-based red-emitting fluorescence probes for the detection of hydrazine in real water samples and applications in bioimaging in vivo

Prof. Yankun Peng | Smart Monitoring Award | Best Researcher Award

Prof. Yankun Peng | Smart Monitoring Award | Best Researcher Award 

Prof. Yankun Peng, China Agricultural University, China

Dr. Peng is a distinguished researcher and professor in the field of Agricultural Engineering with a focus on intelligent detection systems and automated devices for evaluating agricultural product quality and safety. He holds a Ph.D. in Biological and Agricultural Engineering from Tokyo University of Agriculture and Technology, Japan, and has extensive academic and professional experience in both China and the United States. Since 2007, Dr. Peng has served as a Professor and PhD supervisor at the College of Engineering, China Agricultural University (CAU), where he also holds key leadership roles including Director of the National R&D Center for Agro-Processing Technology and Equipment and the National Technical Center for Nondestructive Evaluation, Identification, Instrument, and Equipment of Famous Agro-foods.

Professional Profile:

 

Summary of Suitability for Best Researcher Award 

Dr. Peng has authored 293 peer-reviewed journal articles and 257 conference proceedings, showcasing his prolific research output.He holds 107 patents (including a US patent), with 22 patents industrialized, reflecting his significant contributions to applied science and technology. Additionally, he has developed 18 series of equipment for agro-food quality inspection and grading. Dr. Peng has established 14 standards and authored 4 books and 17 book chapters, demonstrating his leadership in setting benchmarks and contributing to scientific literature.

Education

  • Ph.D. in Biological and Agricultural Engineering
    Tokyo University of Agriculture and Technology, Tokyo, Japan
    Apr. 1993 – Mar. 1996
    Major: Agricultural Engineering, Specialty in Biological Production Science
    Dissertation Title: Active Noise Control on Agricultural/Biological Production Machinery

    • Developed and designed a new type of Active Noise Control (ANC) system/equipment.
    • Proposed a Recurrent Least Squares (RLS) algorithm for noise reduction.
    • Conducted computer simulations of noise reduction effects using C/C++ programming language.
    • Constructed an Adaptive Digital Filter (ADF) system with digital signal processors (DSP) and C/C++ programming.
    • Evaluated the control system on actual machinery and simplified the control algorithm using matrix theory.
  • M.S. in Engineering in Agricultural Electrification & Automation
    Graduate School of Northeast Agricultural University, Harbin, China
    Sep. 1985 – Dec. 1988
    Major: Agricultural Electrification & Automation
    Thesis Title: A Microcomputer Control System for Livestock Granulated Feed Processing

    • Developed a PID feedback control system using a microcomputer.
    • Proposed a new control method for the rotation speed of a servomechanism.
    • Designed a controller using a microcomputer and assembly programming language.
    • Invented a grain flow sensor and applied the control system to livestock feed production.
    • Proposed a method for judging the stability of linear time-invariant systems.

Professional Experience

  • Professor and Ph.D. Supervisor
    Department of Agricultural Engineering, College of Engineering, China Agricultural University (CAU)
    Beijing, China
    Mar. 2007 – Present

    • Research in nondestructive measurement and instrumentation for agricultural product quality and safety.
    • Development of hyperspectral/multispectral and Raman spectral imaging methods for meat microbial contamination detection.
    • Development of rapid real-time inspection/detection systems and NIR optical instruments for agricultural product contaminants.
    • Teaching courses on nondestructive measurement technology and hyperspectral imaging techniques for agro-food quality attributes.
    • Supervised over 60 graduate students in agricultural engineering research.
  • Director, National R&D Center for Agro-Processing Technology and Equipment
    Ministry of Agriculture and Rural Affairs, China
    Nov. 2009 – Present

    • Oversight of national research and development projects related to agro-processing technology and equipment.
  • Director, National Technical Center for Nondestructive Evaluation, Identification, Instrument and Equipment of Famous, Special, Excellent and New Agro-foods
    Ministry of Agriculture and Rural Affairs, China
    Dec. 2019 – Present

    • Leadership in the development and evaluation of nondestructive techniques and equipment for agro-food quality assessment.

Publication top Notes:

Real-time lettuce-weed localization and weed severity classification based on lightweight YOLO convolutional neural networks for intelligent intra-row weed control

Tailored Au@Ag NPs for rapid ractopamine detection in pork: Optimizing size for enhanced SERS signals

Optimization of Online Soluble Solids Content Detection Models for Apple Whole Fruit with Different Mode Spectra Combined with Spectral Correction and Model Fusion

SERS characterization and concentration prediction of Salmonella in pork

Rapid Quantitative detection of Ractopamine using Raman scattering features combining with Deep Learning

Non-destructive detection of TVC in pork by machine learning techniques based on spectral information