Applications of terahertz spectroscopy in the detection and recognition of substances
X Fu, Y Liu, Q Chen, Y Fu, TJ Cui - Frontiers in Physics, 2022 - frontiersin.org
Recently, terahertz spectroscopy has received a lot of attention because of its unique
properties such as biosafety, fingerprint spectrum, and good penetration. In this review, we …
properties such as biosafety, fingerprint spectrum, and good penetration. In this review, we …
Terahertz imaging and sensing for healthcare: current status and future perspectives
M Gezimati, G Singh - IEEE Access, 2023 - ieeexplore.ieee.org
There is a keen interest in the exploration of new generation emitters and detectors due to
advancements in innovation of new materials and device processing technologies which …
advancements in innovation of new materials and device processing technologies which …
Machine learning and application in terahertz technology: A review on achievements and future challenges
Y Jiang, G Li, H Ge, F Wang, L Li, X Chen, M Lu… - IEEE …, 2022 - ieeexplore.ieee.org
Terahertz (THz) radiation (THz) shows great potential in agricultural products detection,
biomedical, and security inspection in recent years. Machine learning methods are widely …
biomedical, and security inspection in recent years. Machine learning methods are widely …
Terahertz phasr scanner with 2 khz, 100 ps time-domain trace acquisition rate and an extended field-of-view based on a heliostat design
Recently, we introduced a Portable HAndheld Spectral Reflection (PHASR) Scanner to
allow terahertz time-domain spectroscopic (THz-TDS) imaging in clinical and industrial …
allow terahertz time-domain spectroscopic (THz-TDS) imaging in clinical and industrial …
Review of bioplastics characterisation by terahertz techniques in the view of ensuring a circular economy
The increasing scarcity of natural resources, worsening global climate change,
environmental degradation, and rising demand for food are forcing the biotechnology and …
environmental degradation, and rising demand for food are forcing the biotechnology and …
Deep learning for terahertz image denoising in nondestructive historical document analysis
Historical documents contain essential information about the past, including places, people,
or events. Many of these valuable cultural artifacts cannot be further examined due to aging …
or events. Many of these valuable cultural artifacts cannot be further examined due to aging …
Prediction of IDH mutation status of glioma based on terahertz spectral data
Z Sun, X Wu, R Tao, T Zhang, X Liu, J Wang… - … Acta Part A: Molecular …, 2023 - Elsevier
Gliomas are the most common type of primary tumor in the central nervous system in adults.
Isocitrate dehydrogenase (IDH) mutation status is an important molecular biomarker for adult …
Isocitrate dehydrogenase (IDH) mutation status is an important molecular biomarker for adult …
Terahertz cancer imaging and sensing: open research challenges and opportunities
M Gezimati, G Singh - Optical and Quantum Electronics, 2023 - Springer
There has been a rapid development of THz technology—sources, detectors and various
THz imaging and sensing techniques. The THz technology demonstrates great potential as …
THz imaging and sensing techniques. The THz technology demonstrates great potential as …
Enhancing brain tumor classification with transfer learning: Leveraging DenseNet121 for accurate and efficient detection
A Raza, MS Alshehri, S Almakdi… - … Journal of Imaging …, 2024 - Wiley Online Library
Brain tumors pose a serious neurological threat to human life, necessitating improved
detection and classification methods. Deep transfer learning (TL), in particular in key tumor …
detection and classification methods. Deep transfer learning (TL), in particular in key tumor …
Transfer Learning for Accurate Classification of Breast Cancer in Medical Imaging
R Sangeetha, RP Shukla, S Vats… - 2023 International …, 2023 - ieeexplore.ieee.org
Transfer learning has recently been developed as a powerful technique for accurate
classification of medical images. It is predominantly used in deep learning models to …
classification of medical images. It is predominantly used in deep learning models to …