Airborne Object Detection Using Hyperspectral Imaging: Deep Learning Review

© 2019, Springer Nature Switzerland AG. Hyperspectral images have been increasingly important in object detection applications especially in remote sensing scenarios. Machine learning algorithms have become emerging tools for hyperspectral image analysis. The high dimensionality of hyperspectral images and the availability of simulated spectral sample libraries make deep learning an appealing approach. This report reviews recent data processing and object detection methods in the area including hand-crafted and automated feature extraction based on deep learning neural networks. The accuracy performances were compared according to existing reports as well as our own experiments (i.e., re-implementing and testing on new datasets). CNN models provided reliable performance of over 97% detection accuracy across a large set of HSI collections. A wide range of data were used: a rural area (Indian Pines data), an urban area (Pavia University), a wetland region (Botswana), an industrial field (Kennedy Space Center), to a farm site (Salinas). Note that, the Botswana set was not reviewed in recent works, thus high accuracy selected methods were newly compared in this work. A plain CNN model was also found to be able to perform comparably to its more complex variants in target detection applications

Quantum Rings in Electromagnetic Fields

This is the author accepted manuscript. The final version is available from Springer via the DOI in this recordThis chapter is devoted to optical properties of so-called Aharonov-Bohm quantum rings (quantum rings pierced by a magnetic flux resulting in AharonovBohm oscillations of their electronic spectra) in external electromagnetic fields. It studies two problems. The first problem deals with a single-electron AharonovBohm quantum ring pierced by a magnetic flux and subjected to an in-plane (lateral) electric field. We predict magneto-oscillations of the ring electric dipole moment. These oscillations are accompanied by periodic changes in the selection rules for inter-level optical transitions in the ring allowing control of polarization properties of the associated terahertz radiation. The second problem treats a single-mode microcavity with an embedded Aharonov-Bohm quantum ring which is pierced by a magnetic flux and subjected to a lateral electric field. We show that external electric and magnetic fields provide additional means of control of the emission spectrum of the system. In particular, when the magnetic flux through the quantum ring is equal to a half-integer number of the magnetic flux quanta, a small change in the lateral electric field allows for tuning of the energy levels of the quantum ring into resonance with the microcavity mode, thus providing an efficient way to control the quantum ring-microcavity coupling strength. Emission spectra of the system are discussed for several combinations of the applied magnetic and electric fields

Influence of groundwater flow on the estimation of subsurface thermal parameters

We investigated the influence of groundwater flow on the thermal tests performed in borehole heat exchangers to infer the underground thermal properties. Temperature\u2013time signals were simulated with a moving line source (MLS) model under different hypotheses of Darcy velocity. Periodic and random noise was included in the synthetic data obtained with this model in order to mimic high-frequency disturbances caused by several possible sources (e.g. equipment instability and changes in environmental conditions during the experiment) that often occur in real signals. The subsurface thermal conductivity, the Darcy velocity and the borehole thermal resistance were inferred by minimising the root-mean-square error between the synthetic dataset and the model. The calculated thermal and hydraulic parameters were consistent with the \u201ca priori\u201d values. The optimisation procedure results were then tested with the infinite line source (ILS) model. For a Darcy velocity exceeding 10 127 m s 121, ILS largely overestimates thermal conductivity. The approach relying on the MLS model was finally tested with real temperature\u2013time data and produced reliable estimates of thermal conductivity, Darcy velocity and borehole thermal resistance. The inferred groundwater flow was cross checked by means of an independent method based on the analysis of temperature\u2013depth logs recorded under thermal equilibrium conditions. Such a test validates the Darcy velocity inferred with the MLS approach