Reusability report: Unpaired deep-learning approaches for holographic image - Zhang, Yuhe; Ritschel, Tobias; Villanueva Perez, Pablo; Lund University, Faculty of Science, Department of Physics, Synchrotron Radiation Research, Lunds universitet, Naturvetenskapliga fakulteten, Fysiska institutionen, Synkrotronljusfysik, Originator; Lund University, Profile areas and other strong research environments, Strategic research areas (SRA), NanoLund: Centre for Nanoscience, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Strategiska forskningsområden (SFO), NanoLund: Centre for Nanoscience, Originator; Lund University, Faculty of Engineering, LTH, LTH Profile areas, LTH Profile Area: Nanoscience and Semiconductor Technology, Lunds universitet, Lunds Tekniska Högskola, LTH profilområden, LTH profilområde: Nanovetenskap och halvledarteknologi, Originator; Lund University, Profile areas and other strong research environments, Lund University Profile areas, LU Profile Area: Light and Materials, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Lunds universitets profilområden, LU profilområde: Ljus och material, Originator; Lund University, Faculty of Engineering, LTH, LTH Profile areas, LTH Profile Area: Photon Science and Technology, Lunds universitet, Lunds Tekniska Högskola, LTH profilområden, LTH profilområde: Avancerade ljuskällor, Originator (Nature Machine Intelligence Advancing X-ray imaging with deep learning, 2024)