Tung-Cheng Wang

ORCID: 0000-0001-6266-3449
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About
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Research Areas
  • Advanced Fluorescence Microscopy Techniques
  • Image Processing Techniques and Applications
  • Structural Response to Dynamic Loads
  • Cell Image Analysis Techniques
  • High-Velocity Impact and Material Behavior
  • Fish Biology and Ecology Studies
  • Fluid Dynamics Simulations and Interactions
  • Regional Development and Environment
  • Reproductive biology and impacts on aquatic species
  • Advanced Image Processing Techniques
  • Fish biology, ecology, and behavior
  • Photonic and Optical Devices
  • Rock Mechanics and Modeling
  • Wetland Management and Conservation
  • Near-Field Optical Microscopy

Vistec Electron Beam (Germany)
2024

Bielefeld University
2020-2024

National Pingtung University of Science and Technology
2017

National Taiwan University
2006

Super-resolution structured illumination microscopy (SR-SIM) provides an up to twofold enhanced spatial resolution of fluorescently labeled samples. The reconstruction high-quality SR-SIM images critically depends on patterned with high modulation contrast. Noisy raw image data (e.g., as a result low excitation power or exposure time), in artifacts. Here, we demonstrate deep-learning based denoising that results reconstructed images. A residual encoding–decoding convolutional neural network...

10.1364/prj.416437 article EN Photonics Research 2021-01-29

Abstract Background Convolutional neural network (CNN)–based methods have shown excellent performance in denoising and reconstruction of super-resolved structured illumination microscopy (SR-SIM) data. Therefore, CNN-based architectures been the focus existing studies. However, Swin Transformer, an alternative recently proposed deep learning–based image restoration architecture, has not fully investigated for SR-SIM images. Furthermore, it explored how well transfer learning strategies work...

10.1093/gigascience/giad109 article EN cc-by GigaScience 2024-01-01

Planar photonic waveguides enable ultrathin sample illumination in fluorescence microscopy over exceedingly large fields of view. Their fabrication has been based on hard coatings requiring sputter deposition and ion-beam lithography, making volume production cumbersome thereby limiting their availability. Additionally, they are typically fabricated top opaque silicon wafers, which restricts the use to upright microscopes. Here, we present a low-cost waveguide chip standard 170 μm thick...

10.1021/acsphotonics.1c00914 article EN ACS Photonics 2021-07-06

The intricate process of spermatogenesis in the paradise fish, Macropodus opercularis, was studied. In this species, unrestricted or lobular type testes lining caudal side body cavity are translucent and slender. Spermatogonia occur along length tubules development sperm takes place within cysts formed by Sertoli cells. Spermiogenesis involves preparatory morphological events followed conspicuous modifications such as movement centrioles, completion nuclear condensation, reduction cytoplasm,...

10.6165/tai.2006.51(3).170 article EN DOAJ (DOAJ: Directory of Open Access Journals) 2006-09-01

Seismic waves created during explosions are transmitted in an outward direction via the surrounding medium, creating a seismic effect that compromises security of facilities. The energy released forms dynamic pressure, which creates gas pressure-induced blast cause ground to vibrate. damage extent and influence dependent on by shock waves. Blast stability materials. Therefore, controlling vibration hazards is imperative ensuring material security. This study investigated explosion-induced...

10.21595/jve.2017.17404 article EN Journal of Vibroengineering 2017-06-30

Abstract Super-resolution structured illumination microscopy (SR-SIM) provides an up to two-fold enhanced spatial resolution of fluorescently labeled samples. The reconstruction high quality SR-SIM images critically depends on patterned with modulation contrast. Noisy raw image data, e.g. as a result low excitation power or exposure times, in artifacts. Here, we demonstrate deep-learning based denoising that results reconstructed images. A residual encoding-decoding convolution neural...

10.1101/2020.10.27.352633 preprint EN bioRxiv (Cold Spring Harbor Laboratory) 2020-10-27
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