相关论文: Optimizing Methane Detection On Board Satellites: …
Deep learning solutions of the salient object detection problem have achieved great results in recent years. The majority of these models are based on encoders and decoders, with a different multi-feature combination. In this paper, we show…
The standard gas mixture for the Resistive Plate Chambers (RPC), composed of C2H2F4/i-C4H10/SF6, allows the detector operation in avalanche mode, as required by the high-luminosity collider experiments. The gas density, the low current and…
With the high flexibility of supporting resource-intensive and time-sensitive applications, unmanned aerial vehicle (UAV)-assisted mobile edge computing (MEC) is proposed as an innovational paradigm to support the mobile users (MUs). As a…
This paper aims at designing an on-board beam generation process for multibeam satellite systems with the goal of reducing the traffic at the feeder link. Full frequency reuse among beams is considered and the beamforming at the satellite…
Ultrafast electron diffraction using MeV energy beams(MeV-UED) has enabled unprecedented scientific opportunities in the study of ultrafast structural dynamics in a variety of gas, liquid and solid state systems. Broad scientific…
Gravitational wave astronomy is a vibrant field that leverages both classic and modern data processing techniques for the understanding of the universe. Various approaches have been proposed for improving the efficiency of the detection…
Several measurements, including the data from the laser spectrometer in the Sample Analysis at Mars instrument suite on the Curiosity Rover in Gale crater, have measured seasonal variations in atmospheric methane at the 0.7 ppbv (parts per…
The complex marine environment exacerbates the challenges of object detection manifold. Marine trash endangers the aquatic ecosystem, presenting a persistent challenge. Accurate detection of marine deposits is crucial for mitigating this…
The description, imagery and interpretation of cloud scenes by remote sensing datasets from Earth-orbiting satellites have become a great debate for several decades. Presently, there are many models for cloud detection and its…
Non-linear detection schemes can substantially improve the achievable throughput and connectivity capabilities of uplink MU-MIMO systems that employ linear detection. However, the complexity requirements of existing non-linear soft…
Spaceborne imaging spectroscopy enables facility-scale methane (CH4) plume detection and quantification by exploiting absorption structure in the 1.65/2.3 um windows. However, performance ultimately depends on both radiometric sensitivity…
Recent advancements in synthetic aperture radar (SAR) ship detection using deep learning have significantly improved accuracy and speed, yet effectively detecting small objects in complex backgrounds with fewer parameters remains a…
Measurement-based methane inventories, which involve surveying oil and gas facilities and compiling data to estimate methane emissions, are becoming the gold standard for quantifying emissions. However, there is a current lack of…
We study the transport of methane in the external water envelopes surrounding water-rich super-Earths and estimate its outgassing into the atmosphere. We investigate the influence of methane on the thermodynamics and mechanics of the water…
Methane (CH$_4$) is the second most powerful greenhouse gas after carbon dioxide and plays a crucial role in climate change due to its high global warming potential. Accurately modeling CH$_4$ fluxes across the globe and at fine temporal…
In a typical multi-standard military communication receiver, fast and reliable spectrum sensing unit is required to extract the information of multiple channels (frequency bands) present in a wideband input signal. In this paper, an energy…
Water megamasers from circumnuclear disks in galaxy centers provide the most accurate measurements of supermassive black hole masses and uniquely probe the sub-parsec accretion processes. At the same time, these systems offer independent…
Cloud and cloud shadow masking is a crucial preprocessing step in hyperspectral satellite imaging, enabling the extraction of high-quality, analysis-ready data. This study evaluates various machine learning approaches, including gradient…
In cognitive radio networks, spectrum sensing is a crucial technique to discover spectrum opportunities for the Secondary Users (SUs). The quality of spectrum sensing is evaluated by both sensing accuracy and sensing efficiency. Here,…
Detecting and identifying objects in satellite images is a very challenging task: objects of interest are often very small and features can be difficult to recognize even using very high resolution imagery. For most applications, this…