Dr. Sheng-Jen Hsieh Profile

Dr. Sheng-Jen Hsieh

Full Professor at Texas A&M Univ

SPIE Involvement:

Conference Program Committee | Author | Editor

Publications (36)

Proceedings Article | 12 April 2021 Presentation + Paper

Infrared imaging and machine learning techniques for plant root location and depth prediction

Xijin Shi, Sheng-Jen Hsieh

Proceedings Volume 11743, 1174303 (2021) https://doi.org/10.1117/12.2587357

KEYWORDS: Machine learning, Infrared imaging, Nondestructive evaluation, Magnetism, Ground penetrating radar, Artificial neural networks

Read Abstract +

A plant’s root system absorbs water and necessary nutrients, and synthesizes organic matter, which is essential for plant growth and regeneration. Therefore, investigating root system architecture (RSA) can potentially provide deep understanding and useful information about plant growth. Current approaches involve soil-coring and use of mini-rhizotrons, which can damage the root or be time consuming. Groundpenetrating radar has been employed but is not suitable for small plants because of the resolution needed. Nuclear magnetic resonance could provide valuable information of tiny roots, but the equipment is costly. In this study, infrared imaging—a-non-destructive method—was used to reveal the shape and position of small root systems, such as sugar beet roots. The finite element analysis (FEA) methodology was implemented toA plant’s root system absorbs water and necessary nutrients, and synthesizes organic matter, which is essential for plant growth and regeneration. Therefore, investigating root system architecture (RSA) can potentially provide deep understanding and useful information about plant growth. Current approaches involve soil-coring and use of mini-rhizotrons, which can damage the root or be time consuming. Ground-penetrating radar has been employed but is not suitable for small plants because of the resolution needed. Nuclear magnetic resonance could provide valuable information of tiny roots, but the equipment is costly. In this study, infrared imaging, a-non-destructive method, was used to reveal the shape and position of small root systems, such as sugar beet roots. The finite element analysis (FEA) methodology was implemented to validate the practicality of applying infrared imaging to detect roots. Artificial neural network (ANN) methods were used to determine the existence of a root system. Support vector machine (SVM) and ANN were employed to predict root depth and statistical tests were used to compare the results. The results of these experiments suggest that infrared imaging can be used to predict the presence and depth of roots. validate the practicality of applying infrared imaging to detect roots. Artificial neural network (ANN) methods were used to determine the existence of a root system. Support vector machine (SVM) and ANN were employed to predict root depth and statistical tests were used to compare the results. The results of these experiments suggest that infrared imaging can be used to predict the presence and depth of roots.

Proceedings Article | 23 April 2020 Presentation + Paper

Analytic models to predict root structure depth

Xijin Shi, Sheng-Jen (Tony) Hsieh

Proceedings Volume 11409, 1140904 (2020) https://doi.org/10.1117/12.2560771

KEYWORDS: Data modeling, Finite element methods, Statistical modeling, Thermal modeling, Artificial neural networks, Mathematical modeling, Infrared imaging

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Proceedings Article | 14 May 2018 Presentation + Paper

Evaluating convective heat transfer coefficients in fused deposition process using infrared imaging and neural networks

Xunfei Zhou, Sheng-Jen Hsieh

Proceedings Volume 10661, 106610K (2018) https://doi.org/10.1117/12.2305569

KEYWORDS: Fused deposition modeling, Neural networks, Manufacturing, Temperature metrology, Data modeling, Convection, Error analysis, Infrared imaging, Thermal modeling, Optical character recognition

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Proceedings Article | 14 May 2018 Presentation + Paper

Application of infrared imaging for monitoring retinal vascular network: an electric circuit analogy approach

Xunfei Zhou, Sheng-Jen Hsieh

Proceedings Volume 10661, 1066113 (2018) https://doi.org/10.1117/12.2305570

KEYWORDS: Resistance, Blood circulation, Temperature metrology, Eye, Infrared imaging, Thermography, Infrared cameras, Thermal modeling, Numerical simulations, Tissues

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Proceedings Article | 5 May 2017 Presentation + Paper

Life cycle monitoring of lithium-ion polymer batteries using cost-effective thermal infrared sensors with applications for lifetime prediction

Xunfei Zhou, Anav Malik, Sheng-Jen Hsieh

Proceedings Volume 10214, 102140A (2017) https://doi.org/10.1117/12.2262762

KEYWORDS: Thermography, Infrared imaging, Nondestructive evaluation, Machine learning, Data modeling, Thermal modeling, Sensors, Performance modeling, Temperature metrology, Statistical modeling, Data acquisition

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Proceedings Article | 5 May 2017 Paper

Thermal analysis of fused deposition modeling process using infrared thermography imaging and finite element modeling

Xunfei Zhou, Sheng-Jen Hsieh

Proceedings Volume 10214, 1021409 (2017) https://doi.org/10.1117/12.2262796

KEYWORDS: Fused deposition modeling, 3D modeling, Thermography, Finite element methods, Additive manufacturing, 3D printing, Infrared imaging, Nondestructive evaluation, Printing, Diffusion, Temperature metrology, Infrared sensors

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Proceedings Article | 11 May 2016 Paper

Thermography and k-means clustering methods for anti-reflective coating film inspection: scratch and bubble defects

Xunfei Zhou, Hongjin Wang, Sheng-Jen (Tony) Hsieh

Proceedings Volume 9861, 98610S (2016) https://doi.org/10.1117/12.2222313

KEYWORDS: Thermography, Inspection, Cameras, Antireflective coatings, Defect detection, Defect inspection, Image processing, Coating, Infrared radiation, Infrared technology

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Proceedings Article | 11 May 2016 Paper

Prediction of tomato freshness using infrared thermal imaging and transient step heating

Jing Xie, Sheng-Jen Hsieh, Zuojun Tan, Hongjin Wang, Jian Zhang

Proceedings Volume 9861, 98610B (2016) https://doi.org/10.1117/12.2223342

KEYWORDS: Thermography, Artificial neural networks, Infrared imaging, Thermal modeling, Data modeling, Hyperspectral imaging, Infrared radiation, Data acquisition, Infrared cameras, Process modeling

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Proceedings Article | 12 May 2015 Paper

Highly sensitive arrayed indium-antimony nanowires for infrared detection

Po-Chun Chen, Chien-Chon Chen, Shih-Hsun Chen, Chung-Yi Chou, Sheng-Jen Hsieh

Proceedings Volume 9485, 94850O (2015) https://doi.org/10.1117/12.2176796

KEYWORDS: Aluminum, Infrared detectors, Infrared radiation, Infrared detection, Oxides, Nanolithography, Infrared materials, Signal detection, Semiconductors, Nanowires

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Proceedings Article | 12 May 2015 Paper

Detection of pinhole defects in optical film using thermography and artificial neural network

Hongjin Wang, Sheng-Jen Hsieh, Bhavana Singh

Proceedings Volume 9485, 94850J (2015) https://doi.org/10.1117/12.2176539

KEYWORDS: Thermography, Defect detection, Data modeling, Artificial neural networks, Optics manufacturing, LCDs, Near field optics, Thermal modeling, Infrared cameras, Statistical modeling

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Proceedings Article | 12 May 2015 Paper

Comparison of step heating and modulated frequency thermography for detecting bubble defects in colored acrylic glass

Hongjin Wang, Sheng-Jen Hsieh

Proceedings Volume 9485, 94850I (2015) https://doi.org/10.1117/12.2176537

KEYWORDS: Thermography, Modulation, Defect detection, Signal to noise ratio, Heat flux, Glasses, Cameras, Polymers, Infrared cameras, Lamps

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SPIE Journal Paper | 13 August 2014

Evaluating the performance of artificial neural networks for estimating the nonmetallic coating thicknesses with time-resolved thermography

Hongjin Wang, Sheng-Jen Hsieh, Alex Stockton

OE, Vol. 53, Issue 08, 083102, (August 2014) https://doi.org/10.1117/12.10.1117/1.OE.53.8.083102

KEYWORDS: Coating, Thermography, Thermal modeling, Data modeling, Artificial neural networks, Infrared cameras, Statistical modeling, Cameras, Neural networks, Temperature metrology

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Proceedings Article | 21 May 2014 Paper

Modelling and predicting hidden solder joint shape using active thermography and parametric numerical analysis

Jose Benjamin Giron Palomares, Sheng-Jen Hsieh

Proceedings Volume 9105, 91050Q (2014) https://doi.org/10.1117/12.2053393

KEYWORDS: Thermal modeling, Thermography, Heat flux, Finite element methods, Shape analysis, Numerical analysis, Mathematical modeling, Chemical elements, Chromium, Modeling

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Proceedings Article | 21 May 2014 Paper

Estimating non-metallic coating thickness using artificial neural network modeled time-resolved thermography: capacity and constraints

Hongjin Wang, Sheng-Jen Hsieh

Proceedings Volume 9105, 91050K (2014) https://doi.org/10.1117/12.2049903

KEYWORDS: Coating, Data modeling, Thermal modeling, Artificial neural networks, Thermography, Neural networks, Statistical modeling, Performance modeling, Algorithm development, Inspection

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Proceedings Article | 21 May 2014 Paper

Survey of thermography in electronics inspection

Sheng-Jen Hsieh

Proceedings Volume 9105, 91050P (2014) https://doi.org/10.1117/12.2053134

KEYWORDS: Thermography, Inspection, Electronics, Amplifiers, Infrared radiation, Infrared imaging, Ultrasonography, Failure analysis, Temperature metrology, Infrared signatures

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Proceedings Article | 22 May 2013 Paper

Experimental model for determining developmental stage of chicken embryo using infrared images and artificial neural networks

Seung Kwon "Paul" Jung, Sheng-Jen "Tony" Hsieh, Che-Hao Chen

Proceedings Volume 8705, 87050H (2013) https://doi.org/10.1117/12.2015647

KEYWORDS: Infrared imaging, Heart, Infrared cameras, Infrared radiation, Data modeling, Cameras, Artificial neural networks, Image processing, Temperature metrology, Thermal modeling

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Proceedings Article | 22 May 2013 Paper

Non-visible defect detection in glass using infrared thermography and artificial neural networks

Amber Campa, Sheng Jen Hsieh, Hong Jen Wang

Proceedings Volume 8705, 87050R (2013) https://doi.org/10.1117/12.2015650

KEYWORDS: Artificial neural networks, Glasses, Defect detection, Mathematical modeling, Thermography, Data modeling, Neural networks, Manufacturing, Inspection, Infrared cameras

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Proceedings Article | 18 May 2012 Paper

Use of infrared imaging to predict the developmental stages and differences in chicken embryos exposed to different photoperiods

Rebecca Frederick, Sheng-Jen Hsieh, Benjamin Giron Palomares

Proceedings Volume 8354, 83540Y (2012) https://doi.org/10.1117/12.918539

KEYWORDS: Infrared imaging, Tomography, Ultrasonography, Data modeling, Magnetic resonance imaging, Optical coherence tomography, Thermography, Infrared radiation, Image analysis, Heart

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Proceedings Article | 18 May 2012 Paper

Development and validation of experimental models for hyperemic thermal response using IR imaging

Eulalia Moreno, Sheng-Jen Hsieh, Benjamin Giron Palomares

Proceedings Volume 8354, 83540U (2012) https://doi.org/10.1117/12.918740

KEYWORDS: Blood circulation, Mathematical modeling, Data modeling, Thermal modeling, Body temperature, Infrared imaging, Blood pressure, Blood, Heart, Thermal effects

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Proceedings Article | 10 May 2011 Paper

Use of infrared imaging for investigation of chicken embryo development

Ryan Frye, Sheng-Jen Hsieh, José Benjamín Girón Palomares

Proceedings Volume 8013, 801306 (2011) https://doi.org/10.1117/12.883752

KEYWORDS: Ultrasonography, Tomography, Thermography, Visualization, Magnetic resonance imaging, Infrared imaging, Optical coherence tomography, Heart, Image visualization, 3D acquisition

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Proceedings Article | 10 May 2011 Paper

Comparative analysis of pulse and active thermography for investigating solder joint geometry prediction

Becky Vela, Sheng-Jen Hsieh, José Benjamín Dolores Girón Palomares

Proceedings Volume 8013, 80130H (2011) https://doi.org/10.1117/12.883754

KEYWORDS: Thermography, Inspection, Switches, Infrared cameras, Sensors, Photonic integrated circuits, X-rays, Neural networks, Data modeling, Ultrasonography

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Proceedings Article | 4 May 2010 Paper

Finite element analysis and neural network model for electronic hidden solder joint geometry prediction

Jose Benjamin Dolores Giron Palomares, Sheng-Jen Hsieh

Proceedings Volume 7661, 76610T (2010) https://doi.org/10.1117/12.849935

KEYWORDS: Thermography, Finite element methods, Thermal modeling, 3D modeling, Data modeling, Infrared imaging, Neural networks, Infrared cameras, Inspection, Nondestructive evaluation

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Proceedings Article | 22 April 2009 Paper

Electronic hidden solder joint geometry characterization

Sheng-Jen Hsieh

Proceedings Volume 7299, 72990E (2009) https://doi.org/10.1117/12.819383

KEYWORDS: Thermal modeling, Data modeling, Inspection, Binary data, Neural networks, Thermography, X-rays, Evolutionary algorithms, Infrared cameras, Imaging systems

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Proceedings Article | 17 March 2008 Paper

Active thermography for potato characterization

Sheng-Jen Hsieh, Chih-Chen Sun

Proceedings Volume 6939, 69390P (2008) https://doi.org/10.1117/12.778137

KEYWORDS: Thermography, Inspection, Thermal modeling, Image processing, Data modeling, Analytical research, Food inspection, Lamps, Machine vision, Digital image processing

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Proceedings Article | 9 April 2007 Paper

Thermal profiling techniques for electronics inspection

Sheng-Jen Hsieh

Proceedings Volume 6541, 65410G (2007) https://doi.org/10.1117/12.720506

KEYWORDS: Inspection, Thermography, Electronics, Amplifiers, Neural networks, Data modeling, Infrared radiation, Infrared imaging, Thermal modeling, Microcontrollers

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Proceedings Article | 18 April 2006 Paper

Thermography and neural networks for SRAM voltage stress prediction

Sheng-Jen Hsieh, Kartik Sharma

Proceedings Volume 6205, 62050Q (2006) https://doi.org/10.1117/12.663726

KEYWORDS: Neural networks, Thermal modeling, Infrared cameras, Thermography, Connectors, Data modeling, Humidity, Artificial neural networks, Electronic components, Computer programming

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Proceedings Article | 18 April 2006 Paper

On-board SRAM signal density stress prediction

Sheng-Jen Hsieh, Kartik Sharma

Proceedings Volume 6205, 62050R (2006) https://doi.org/10.1117/12.664014

KEYWORDS: Neural networks, Data modeling, Thermal modeling, Computer programming, Failure analysis, Humidity, Infrared cameras, Artificial neural networks, Electronics, Electronic components

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Proceedings Article | 10 May 2005 Paper

Comprehensive CD uniformity control across lithography and etch

Qiaolin Zhang, Cherry Tang, Tony Hsieh, Nick Maccrae, Bhanwar Singh, Kameshwar Poolla, Costas Spanos

Proceedings Volume 5752, (2005) https://doi.org/10.1117/12.601087

KEYWORDS: Critical dimension metrology, Plasma, Plasma etching, Etching, Control systems, Semiconducting wafers, Lithography, Temperature metrology, Oxygen, Process control

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Proceedings Article | 28 March 2005 Paper

Analysis tool and methodology design for electronic vibration stress understanding and prediction

Sheng-Jen Hsieh, Robert Crane, Shamachary Sathish

Proceedings Volume 5782, (2005) https://doi.org/10.1117/12.605448

KEYWORDS: Neural networks, Electronic components, Amplifiers, Sensors, Temperature metrology, Lead, Algorithm development, Ultrasonography, Infrared cameras, Computer aided design

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Proceedings Article | 12 April 2004 Paper

Microcontroller signal density stress prediction framework

Sheng-Jen Hsieh, Sung-Ling Huang, Shao-Chin Chang

Proceedings Volume 5405, (2004) https://doi.org/10.1117/12.542439

KEYWORDS: Microcontrollers, Data modeling, Neural networks, Error analysis, Statistical modeling, Thermal modeling, Clocks, Statistical analysis, Evolutionary algorithms, Light emitting diodes

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Proceedings Article | 8 September 2003 Paper

Proof of principle for helmet-mounted display image quality tester

Sheng-Jen Hsieh, Thomas Harding, Clarence Rash, Howard Beasley, John Martin

Proceedings Volume 5079, (2003) https://doi.org/10.1117/12.485548

KEYWORDS: Cameras, Head-mounted displays, Image analysis, Prototyping, Inspection, Image quality, Human-machine interfaces, Image acquisition, Algorithm development, Image processing

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Helmet mounted displays (HMDs) provide essential pilotage and fire control imagery information for pilots. To maintain system integrity and readiness, there is a need to develop an image quality-testing tool for HMDs. There is currently no such tool. A framework for development of an image quality tester for the Integrated Helmet and Display Sighting System (IHADSS) used in the U.S. Army's AH-64 was proposed in Hsieh et al. This paper presents the prototype development, summarizes the bench test findings using three IHADSS helmet display units (HDUs), and concludes with recommendations for future directions. The prototype consists of hardware (two cameras, sensors, image capture/data acquisition cards, battery pack, HDU holder, moveable rack and handle, and computer) and software algorithms for image capture and analysis. Two cameras with different apertures were mounted in parallel on a rack facing the HDU holder. A handle was designed to allow users to position the HDU in front of the two cameras. The HMD test pattern was then captured. Sensors are used to detect the position of the holder and whether the HDU was angled correctly in relation to the camera. Two sets of unified algorithms were designed to detect features presented by the two cameras. These features include focus, orientation, displacement, field-of-view, and number of gray-shades. Images of test pattern were captured and analyzed, and used to develop a specification for each inspection feature. Experiments were conducted to verify the robustness of the algorithms. A worst-case scenario for factors such as clock-wise and counterclockwise tilt, degree of focus, magnitude of brightness and contrast, and shifted images were set up and evaluated. Bench testing of three field-quality HDUs indicate that the image analysis algorithms are robust and able to detect the desired image features. Suggested future work includes development of a learning algorithm to automatically develop or revise feature specifications as the number of inspection samples increases.

Proceedings Article | 1 April 2003 Paper

Thermal profiling for IC chip high-voltage stress prediction

Sheng-Jen Hsieh, Sung-Ling Huang

Proceedings Volume 5073, (2003) https://doi.org/10.1117/12.486872

KEYWORDS: Neural networks, Data modeling, Amplifiers, Evolutionary algorithms, Manufacturing, Statistical analysis, Humidity, Artificial neural networks, Profiling, Integrated circuits

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Proceedings Article | 15 March 2002 Paper

Neural network and statistical modeling techniques for electronic stress prediction

Sheng-Jen Hsieh

Proceedings Volume 4710, (2002) https://doi.org/10.1117/12.459630

KEYWORDS: Neural networks, Data modeling, Resistors, Statistical analysis, Statistical modeling, Error analysis, Reverse modeling, Electronic components, Thermal modeling, Evolutionary algorithms

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Proceedings Article | 22 August 2001 Paper

Design of an image-quality tester

Sheng-Jen Hsieh, Clarence Rash, Thomas Harding

Proceedings Volume 4361, (2001) https://doi.org/10.1117/12.437996

KEYWORDS: Head-mounted displays, Prototyping, Cameras, Visualization, Image quality, Inspection, Image analysis, Image processing, Algorithm development, CCD cameras

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Proceedings Article | 23 March 2001 Paper

Thermal signature for solder defect detection using a neural network approach

Sheng-Jen Hsieh, Agapito Calderon

Proceedings Volume 4360, (2001) https://doi.org/10.1117/12.421049

KEYWORDS: Neural networks, Resistors, Inspection, Defect detection, Image processing, X-rays, Thermography, Infrared cameras, Image analysis, MATLAB

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Proceedings Article | 23 March 2001 Paper

Thermal signature for printed circuit board stress-failure diagnosis

Sheng-Jen Hsieh

Proceedings Volume 4360, (2001) https://doi.org/10.1117/12.420975

KEYWORDS: Diagnostics, Infrared cameras, Printed circuit board testing, Thermography, Infrared signatures, Failure analysis, Cameras, Statistical analysis, Infrared imaging, Manufacturing

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Showing 5 of 36 publications

Proceedings Volume Editor (2)

SPIE Conference Volume | 10 June 2015

Thermosense: Thermal Infrared Applications XXXVII

SPIE Conference Volume | 17 June 2014

Thermosense: Thermal Infrared Applications XXXVI

Conference Committee Involvement (21)

Thermosense: Thermal Infrared Applications XLVII

13 April 2025 | Orlando, Florida, United States

Thermosense: Thermal Infrared Applications XLVI

22 April 2024 | National Harbor, Maryland, United States

Thermosense: Thermal Infrared Applications XLV

2 May 2023 | Orlando, Florida, United States

Thermosense: Thermal Infrared Applications XLIV

5 April 2022 | Orlando, Florida, United States

Thermosense: Thermal Infrared Applications XLIII

12 April 2021 | Online Only, Florida, United States

Thermosense: Thermal Infrared Applications XLII

27 April 2020 | Online Only, California, United States

Thermosense: Thermal Infrared Applications XLI

15 April 2019 | Baltimore, MD, United States

Thermosense: Thermal Infrared Applications XL

16 April 2018 | Orlando, FL, United States

Thermosense: Thermal Infrared Applications XXXIX

11 April 2017 | Anaheim, CA, United States

Thermosense: Thermal Infrared Applications XXXVIII

18 April 2016 | Baltimore, MD, United States

Thermosense: Thermal Infrared Applications XXXVII

20 April 2015 | Baltimore, MD, United States

Thermosense: Thermal Infrared Applications XXXVI

5 May 2014 | Baltimore, MD, United States

Thermosense: Thermal Infrared Applications XXXV

30 April 2013 | Baltimore, Maryland, United States

Thermosense: Thermal Infrared Applications XXXIV

23 April 2012 | Baltimore, Maryland, United States

Thermosense: Thermal Infrared Applications XXXIII

26 April 2011 | Orlando, Florida, United States

Thermosense XXXII

6 April 2010 | Orlando, Florida, United States

Thermosense XXXI

14 April 2009 | Orlando, Florida, United States

Thermosense XXX

18 March 2008 | Orlando, Florida, United States

Thermosense XXIX

10 April 2007 | Orlando, Florida, United States

Thermosense XXVIII

17 April 2006 | Orlando (Kissimmee), Florida, United States

Thermosense XXVII

29 March 2005 | Orlando, Florida, United States

Showing 5 of 21 Conference Committees

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