most citedEfficient Segment Anything with Depth-Aware Fusion and Limited Training Data

1 citations · 3 across the 11 of their papers we have counts for

collaborators

14 papers

physics.app-ph2026

Quantitative Infrared Thermographic Assessment of Hand Cooling Dynamics During Controlled Contact with Metal Plates

Pengfei Zhu, Hai Zhang, Stefano Sfarra +4

This study investigates the spatiotemporal thermal response of human hands during controlled contact cooling using short wave infrared (SWIR), mid wave infrared (MWIR), and long wa…

physics.app-ph2026

Generalized virtual wave reconstruction for vibrothermography: Overcoming the wavefront-free behavior and quantification challenges in the diffusion-wave field

Pengfei Zhu, Julien Lecompagnon, Mathias Ziegler +2

Wavefront-free behavior and the resulting quantification difficulties are intrinsic limitations of vibrothermography due to the diffusive nature of thermal fields. This work propos…

cs.CV2026

Principal Component Analysis-Based Terahertz Self-Supervised Denoising and Deblurring Deep Neural Networks

Pengfei Zhu, Stefano Sfarra, Hai Zhang +4

Terahertz (THz) systems inherently introduce frequency-dependent degradation effects, resulting in low-frequency blurring and high-frequency noise in amplitude images. Conventional…

physics.app-ph2026

Field-material coupled neural network: A novel prior-free and data-free inverse problem solver for extracting complex dielectric constant in terahertz band

Pengfei Zhu, Stefano Sfarra, Elena Pivarciova +2

Accurate extraction of the complex dielectric constant in the terahertz (THz) band is essential for material characterization and non-destructive evaluation yet remains challenging…

cs.CV2026★ 1 cited

Efficient Segment Anything with Depth-Aware Fusion and Limited Training Data

Yiming Zhou, Xuenjie Xie, Panfeng Li +3

Segment Anything Models (SAM) achieve impressive universal segmentation performance but require massive datasets (e.g., 11M images) and rely solely on RGB inputs. Recent efficient…

eess.IV2026

Non-Invasive Diagnosis for Clubroot Using Terahertz Time-Domain Spectroscopy and Physics-Constrained Neural Networks

Pengfei Zhu, Jiaxu Wu, Alyson Deslongchamps +2

Clubroot, a major soilborne disease affecting canola and other cruciferous crops, is characterized by the development of large galls on the roots of susceptible hosts. In this stud…

physics.optics2025★ 1 cited

A review of cultural heritage inspection: Toward terahertz from mid-infrared region

Pengfei Zhu, Hai Zhang, Stefano Sfarra +2

This review explores non-invasive imaging (NII) methods covering the mid- and far-infrared to the terahertz spectral regions (up to approximately 1000 um) for the detection and ana…

physics.optics2025

Modeling Terahertz Propagation via Frequency-Domain Physics-Informed Neural Networks

Pengfei Zhu, Hai Zhang, Stefano Sfarra +3

Terahertz time-domain spectroscopy (THz-TDS) provides a non-invasive and label-free method for probing the internal structure and electromagnetic response of materials. Numerical s…

physics.optics2025

THz-PINNs: Time-Domain Forward Modeling of Terahertz Spectroscopy with Physics-Informed Neural Networks

Pengfei Zhu, Xavier Maldague

Terahertz time-domain spectroscopy (THz-TDS) is a powerful tool for extracting optical and electrical parameters, as well as probing internal structures and surface morphology of m…

physics.app-ph2025

Thermal diffusivity measurement based on evaporative cryocooling excitation: Theory and experiments

Pengfei Zhu, Hai Zhang, Stefano Sfarra +4

Photo-thermal methods for measuring thermal diffusivity inherently pose an ill-posed inverse problem, affected by factors such as sample thickness, heating or cooling time, and exc…

physics.app-ph2025★ 1 cited

Real-Time Super-Resolution Imaging System Based on Zero-Shot Learning for Infrared Non-Destructive Testing

Pengfei Zhu, Ziang Wei, Ahmad Osman +4

Infrared thermography (IRT) and photothermal coherence tomography (PCT) exhibit potential in non-destructive testing and biomedical fields. However, the inevitable heat diffusion s…

physics.app-ph2025

Thermal diffusivity characterization of impacted composites using evaporative cryocooling excitation and inverse physics-informed neural networks

Pengfei Zhu, Hai Zhang, Stefano Sfarra +5

The thermal diffusivity measurement of impacted composites using pulsed methods presents an ill-posed inverse problem influenced by multiple factors such as sample thickness, cooli…

physics.app-ph2025

A novel IR-SRGAN assisted super-resolution evaluation of photothermal coherence tomography for impact damage in toughened thermoplastic CFRP laminates under room temperature and low temperature

Pengfei Zhu, Hai Zhang, Stefano Sfarra +4

Evaluating impact-induced damage in composite materials under varying temperature conditions is essential for ensuring structural integrity and reliable performance in aerospace, p…

physics.app-ph2025

Making neural networks understand internal heat transfer using Fourier-transformed thermal diffusion wave fields

Pengfei Zhu, Hai Zhang, Clemente Ibarra-Castanedo +2

Heat propagation is governed by phonon interactions and mathematically described by partial differential equations (PDEs), which link thermal transport to the intrinsic properties…