Data-driven deep neural networks have demonstrated their superiority in high-resolution remote-sensing image (HRSI) classification based on superpixel-based objects. Currently, most HRSI classification methods that combine deep learning and superpixe...
Road extraction from remote sensing images is significant for urban planning, intelligent transportation, and vehicle navigation. However, it is challenging to automatically extract roads from remote sensing images because the scale difference of roa...
Integrated sensing and communication (ISAC) has become a key enabler in 5G-Advanced (5G-A) and future 6G systems, with Orthogonal Frequency Division Multiplexing (OFDM) widely adopted as the underlying waveform. However, due to the inherent structure...
Profiting from the surprising non-linear expressive capacity, deep convolutional neural networks have inspired lots of progress in low illumination (LI) remote sensing image enhancement. The key lies in sufficiently exploiting both the specific long-...
Acoustics is the primary means of long-range and wide-area sensing in the ocean due to the severe attenuation of electromagnetic waves in seawater. While it is known that densely packed fish groups can attenuate acoustic signals during long-range pro...
Flexure mechanisms, precision actuation, and micro/nanoscale sensing and control are the fundamental building blocks for precision engineering, micro/nanopositioning systems, and instrumentation for micro/nanoscale manufacturing. Furthermore, a growi...
In the realm of remote sensing image analysis, the task of road extraction poses significant complexities, especially in the context of intricate scenes and diminutive targets. In response to these challenges, we have developed a novel deep learning...
Semantic segmentation of ultra-high-resolution remote sensing (UHR-RS) imagery plays a critical role in land use and land cover analysis, yet it remains computationally intensive due to the enormous input size and high spatial complexity. Existing st...
Remote sensing images are characterized by high complexity, significant scale variations, and abundant details, which present challenges for existing deep learning-based super-resolution reconstruction methods. These algorithms often exhibit limited...
Soil salinity estimation across arid agricultural regions is challenging due to pronounced environmental heterogeneity and complex dependencies among multi-source variables. This study proposes a Long-Range Dependency-Enhanced Network (LRD-Net) for r...
Recent advances in deep learning have shown remarkable performance in road segmentation from remotely sensed images. However, these methods based on convolutional neural networks (CNNs) cannot obtain long-range dependency and global contextual inform...
We introduce a novel long-range traffic monitoring system for vehicle detection, tracking, and classification based on fiber-optic distributed acoustic sensing (DAS). High resolution and long range are provided by the use of an optimized setup incorp...
Biomass burning (BB) emits a large volume of trace gases and aerosols into the atmosphere, which can significantly affect the earth’s radiative balance and climate and has negative impacts on air quality and even human health. In late June 2017...
The inability of existing super-resolution methods to jointly model short-range and long-range spatial dependencies in remote sensing imagery limits reconstruction efficacy. To address this, we propose LSTMConvSR, a novel framework inspired by top-do...
The safety of vehicles is one of the major goals of driving automation. The safety distance is longer for rail vehicles such as trams because of the adherence limitations of the wheel-to-rail system. The major issues of fixed frontal sensing are fake...
Until recently, the amount of solar irradiance reaching the Earth surface was considered to be a steady value over the years. However, there is increasing observational evidence showing that this quantity undergoes substantial variations over time, w...
In cloud-based Distributed Acoustic Sensing (DAS) sensor data management, we are confronted with two primary challenges. First, the development of efficient storage mechanisms capable of handling the enormous volume of data generated by these sensors...
Indoor target localization is pivotal across various applications, encompassing security monitoring, behavioral analysis, and elderly care. This work proposes an advanced target localization algorithm that harnesses antennas endowed with sensing capa...
Wide-area building-structure mapping from long-range airborne LiDAR requires image products that can represent building footprints, roof-height variations, and structural discontinuities with low computational latency. Airborne streak-tube imaging Li...
In 2024, Brazil experienced record-breaking wildfire activity, underscoring the escalating influence of climate change. This study examines the long-range transport of wildfire-generated aerosol plumes to São Paulo, combining multi-platform ob...
Long-range airborne streak tube imaging lidar (ASTIL) raw echo images are degraded by atmospheric speckle, detector noise, and weak-return fluctuations, which can bias centroid localization before range calculation. This study presents a lightweight...
Smoke from the Canadian wildfires of August 2025 reached Cluj-Napoca, Romania, on 6–9 August as a thin layer at 5–8 km. We followed the plume from its source with the multi-angle polarimeters HARP2 and SPEXone and the OCI radiometer on NA...
Image-based displacement measurement techniques are widely used for sensing the deformation of structures, and plays an increasing role in structural health monitoring owing to its benefit of non-contacting. In this study, a non-overlapping dual came...
Radio frequency identification (RFID) represents an emerging platform for passive RF-powered wireless sensing. Differential Multi-port RFID systems are widely used to enable multiple independent measurands to be gathered, or to overcome channel varia...
Distributed fiber sensing (DFS) can provide real-time signals and warnings. The entire length of fiber optic cable can act as a sensing element, but the accuracy is sometimes limited. On the other hand, point-to-point fiber sensing (PPFS) is usually...
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Unconventional lithography (such as nanosphere lithography (NSL) and colloidal lithography (CL)) is an attractive alternative to sequential and very expensive conventional lithography for the low-cost fabrication of large-area nano-optical devices. A...
We propose and experimentally demonstrate a novel scheme of bi-directional Brillouin time domain analyzer (BD-BOTDA) to extend the sensing range. By deploying two pump-probe pairs at two different wavelengths, the Brillouin frequency shift (BFS) dist...
A Brillouin distributed acoustic sensor (DAS) based on optical time-domain refractometry exhibiting a maximum detectible strain of 8.7 m
Currently, smart farming is considered an effective solution to enhance the productivity of farms; thereby, it has recently received broad interest from service providers to offer a wide range of applications, from pest identification to asset monito...
The frequency of forest fires is increasing under global climate change, and forest fires can cause devastating disturbances to forest systems and varying degrees of recovery of forest ecosystems after a disaster. Due to the different intensity of fo...
3D point cloud understanding plays a vital role in remote sensing, robotic perception and intelligent scene analysis. However, real-world point cloud data are often affected by sensing noise, incomplete geometry, occlusion, and irregular sampling, po...
Remote sensing image dehazing is a well-known remote sensing image processing task focused on restoring clean images from hazy images. The Transformer network, based on the self-attention mechanism, has demonstrated remarkable advantages in various i...
Distributed optical fiber sensing technology has been widely applied in the areas of infrastructure health monitoring, national defense security, etc. The long-range high-spatial-resolution Brillouin optical correlation domain analysis (BOCDA) has ex...
This article introduces a long-range sensing system based on millimeter-wave radar, which is used to detect the roadside boundaries and track trains for trains. Due to the high speed and long braking distance of trains, existing commercial vehicle se...
For scalable quantum networks and distributed quantum sensing, remote NV color-center spin ensembles require controllable long-range coherent connections. However, the magnetic dipole coupling between NV centers decays rapidly with distance, making d...
Piezoelectric micromachined ultrasonic transducers (PMUTs) have been widely applied in distance sensing. However, the sensing distance of currently reported miniaturized ultrasonic sensors (e.g., PMUTs or CMUT) is still limited up to a certain range...
Semantic segmentation of high-resolution remote-sensing images is critical for urban planning, land-cover mapping, and ecological monitoring. However, existing methods face limitations in handling complex land-cover types, multi-scale objects, and mo...
Semantic segmentation of remote sensing images is a key technology for land cover interpretation and target identification. Although convolutional neural networks (CNNs) have achieved remarkable success in this field, their inherent limitation of loc...
Today’s wireless activity recognition research still needs to be practical, mainly due to the limited sensing range and weak through-wall effect of the current wireless activity recognition based on Wi-Fi, RFID (Radio Frequency Identification,...
Long-range radio transmissions open new sensor application fields, in particular for environment monitoring. For example, the LoRa radio protocol enables connecting remote sensors at a distance as long as ten kilometers in a line-of-sight. However, t...
Rare-earth intermetallic compounds are characterised by the presence of a long-range magnetic order due to the interaction of local magnetic moments periodically located within the crystal lattice. This paper considers the possibility of forming an o...
CloudSim is a versatile simulation framework for modeling cloud infrastructure components that supports customizable and extensible application provisioning strategies, allowing for the simulation of cloud services. On the other hand, Distributed Aco...
Reliable long-range onboard perception is a prerequisite for future railway safety systems, where potential obstacles must be recognized under long braking distances, sparse far-field returns, and strongly constrained rail-corridor geometry. This pap...
A guided−wave long−range surface plasmon resonance (GW−LRSPR) sensor was proposed in this investigation. In the proposed sensor, high−refractive−index (RI) dielectric films (i.e., CH3NH3PbBr3 perovskite, silicon) served...
We proposed an ultra-sensitive refractive index sensor by using indium-doped cadmium oxide as a plasmonic material operating in near-infrared based on Fano resonance. The proposed sensor has a hybrid multilayer waveguide structure that supports both...
In remote sensing image processing, cloud and cloud shadow detection is of great significance, which can solve the problems of cloud occlusion and image distortion, and provide support for multiple fields. However, the traditional convolutional or Tr...
The semantic segmentation of satellite and UAV remote sensing imagery is pivotal for address exploration, change detection, quantitative analysis and urban planning. Recent advancements have seen an influx of segmentation networks utilizing convoluti...
Remote-sensing images typically feature large dimensions and contain repeated texture patterns. To effectively capture finer details and encode comprehensive information, feature-extraction networks with larger receptive fields are essential for remo...
Although Transformer-based and state-space models (e.g., Mamba) have demonstrated impressive performance in image restoration, they remain deficient in remote sensing image dehazing. Transformer-based models tend to distribute attention evenly, makin...
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