arXiv subjects

Lan Fu

Publications and source records attributed to Lan Fu.

31 records · Page 2Linked to original sources

arXiv2023

Defense against Adversarial Cloud Attack on Remote Sensing Salient Object Detection

Detecting the salient objects in a remote sensing image has wide applications for the interdisciplinary research. Many existing deep learning methods have been proposed for Salient Object Detection (SOD) in remote sensing images and get remarkable results. However, the recent adversarial attack examples, generated by changing a few pixel values on the original remote sensing image, could result in a collapse for the well-trained deep learning based SOD model. Different with existing methods adding perturbation to original images, we propose to jointly tune adversarial exposure and additive perturbation for attack and constrain image close to cloudy image as Adversarial Cloud. Cloud is natural and common in remote sensing images, however, camouflaging cloud based adversarial attack and defense for remote sensing images are not well studied before. Furthermore, we design DefenseNet as a learn-able pre-processing to the adversarial cloudy images so as to preserve the performance of the deep learning based remote sensing SOD model, without tuning the already deployed deep SOD model. By considering both regular and generalized adversarial examples, the proposed DefenseNet can defend the proposed Adversarial Cloud in white-box setting and other attack methods in black-box setting. Experimental results on a synthesized benchmark from the public remote sensing SOD dataset (EORSSD) show the promising defense against adversarial cloud attacks.

cs.CV↗

arXiv2023

Semi-supervised Large-scale Fiber Detection in Material Images with Synthetic Data

Accurate detection of large-scale, elliptical-shape fibers, including their parameters of center, orientation and major/minor axes, on the 2D cross-sectioned image slices is very important for characterizing the underlying cylinder 3D structures in microscopic material images. Detecting fibers in a degraded image poses a challenge to both current fiber detection and ellipse detection methods. This paper proposes a new semi-supervised deep learning method for large-scale elliptical fiber detection with synthetic data, which frees people from heavy data annotations and is robust to various kinds of image degradations. A domain adaptation strategy is utilized to reduce the domain distribution discrepancy between the synthetic data and the real data, and a new Region of Interest (RoI)-ellipse learning and a novel RoI ranking with the symmetry constraint are embedded in the proposed method. Experiments on real microscopic material images demonstrate the effectiveness of the proposed approach in large-scale fiber detection.

cs.CV↗

arXiv2023

Pushing limits of photovoltaics and photodetection using radial junction nanowire devices

Nanowire devices have long been proposed as an efficient alternative to their planar counterparts for different optoelectronic applications. Unfortunately, challenges related to the growth and characterization of doping and p-n junction formation in nanowire devices (along axial or radial axis) have significantly impeded their development. The problems are further amplified if a p-n junction has to be implemented radially. Therefore, even though radial junction devices are expected to be on par with their axial junction counterparts, there are minimal reports on high-performance radial junction nanowire optoelectronic devices. This paper summarizes our recent results on the simulation and fabrication of radial junction nanowire solar cells and photodetectors, which have shown unprecedented performance and clearly demonstrate the importance of radial junction for optoelectronic applications. Our simulation results show that the proposed radial junction device is both optically and electrically optimal for solar cell and photodetector applications, especially if the absorber quality is extremely low. The radial junction nanowire solar cells could achieve a 17.2% efficiency, whereas the unbiased radial junction photodetector could show sensitivity down to a single photon level using an absorber with a lifetime of less than 50 ps. In comparison, the axial junction planar device made using same substrate as absorber showed less than 1% solar cell efficiency and almost no photodetection at 0 V. This study is conclusive experimental proof of the superiority of radial junction nanowire devices over their thin film or axial junction counterparts, especially when absorber lifetime is extremely low. The proposed device holds huge promise for III-V based photovoltaics and photodetectors.

cond-mat.mtrl-sci↗

arXiv2022

Nanoscale 3D tomography by in-flight fluorescence spectroscopy of atoms sputtered by a focused ion beam

Nanoscale fabrication and characterisation techniques critically underpin a vast range of fields, including materials science, nanoelectronics and nanobiotechnology. Focused ion beam (FIB) techniques are particularly appealing due to their high spatial resolution and widespread use for processing of nanostructured materials and devices. Here, we introduce FIB-induced fluorescence spectroscopy (FIB-FS) as a nanoscale technique for spectroscopic detection of atoms sputtered by an ion beam. We use semiconductor heterostructures to demonstrate nanoscale lateral and depth resolution and show that it is limited by ion-induced intermixing of nanostructured materials. Sensitivity is demonstrated qualitatively by depth-profiling of 3.5, 5 and 8 nm quantum wells, and quantitatively by detection of trace-level impurities present at parts-per-million levels. To showcase the utility of the FIB-FS technique, we use it to characterise quantum wells and Li-ion batteries. Our work introduces FIB-FS as a high-resolution, high sensitivity, 3D analysis and tomography technique that combines the versatility of FIB nanofabrication techniques with the power of diffraction-unlimited fluorescence spectroscopy. It is applicable to all elements in the periodic table, and enables real-time analysis during direct-write nanofabrication by focused ion beams.

physics.app-ph↗

arXiv2021

Benchmarking Shadow Removal for Facial Landmark Detection and Beyond

Facial landmark detection is a very fundamental and significant vision task with many important applications. In practice, facial landmark detection can be affected by a lot of natural degradations. One of the most common and important degradations is the shadow caused by light source blocking. While many advanced shadow removal methods have been proposed to recover the image quality in recent years, their effects to facial landmark detection are not well studied. For example, it remains unclear whether shadow removal could enhance the robustness of facial landmark detection to diverse shadow patterns or not. In this work, for the first attempt, we construct a novel benchmark to link two independent but related tasks (i.e., shadow removal and facial landmark detection). In particular, the proposed benchmark covers diverse face shadows with different intensities, sizes, shapes, and locations. Moreover, to mine hard shadow patterns against facial landmark detection, we propose a novel method (i.e., adversarial shadow attack), which allows us to construct a challenging subset of the benchmark for a comprehensive analysis. With the constructed benchmark, we conduct extensive analysis on three state-of-the-art shadow removal methods and three landmark detectors. The observation of this work motivates us to design a novel detection-aware shadow removal framework, which empowers shadow removal to achieve higher restoration quality and enhance the shadow robustness of deployed facial landmark detectors.

cs.CV↗

arXiv2021

Self-powered InP Nanowire Photodetector for Single Photon Level Detection at Room Temperature

Highly sensitive photodetectors with single photon level detection is one of the key components to a range of emerging technologies, in particular the ever-growing field of optical communication, remote sensing, and quantum computing. Currently, most of the single-photon detection technologies require external biasing at high voltages and/or cooling to low temperatures, posing great limitations for wider applications. Here, we demonstrate InP nanowire array photodetectors that can achieve single-photon level light detection at room temperature without an external bias. We use top-down etched, heavily doped p-type InP nanowires and n-type AZO/ZnO carrier selective contact to form a radial p-n junction with a built-in electric field exceeding 3x10^5 V/cm at 0 V. The device exhibits broadband light sensitivity and can distinguish a single photon per pulse from the dark noise at 0 V, enabled by its design to realize near-ideal broadband absorption, extremely low dark current, and highly efficient charge carrier separation. Meanwhile, the bandwidth of the device reaches above 600 MHz with a timing jitter of 538 ps. The proposed device design provides a new pathway towards low-cost, high-sensitivity, self-powered photodetectors for numerous future applications.

physics.optics↗

arXiv2021

Ultralow Threshold, Single-Mode InGaAs/GaAs Multi-Quantum Disk Nanowire Lasers

We present single-mode nanowire (NW) lasers with ultralow threshold in the near-infrared spectral range. To ensure the single-mode operation, the NW diameter and length are reduced specifically to minimize the longitudinal and transverse modes of the NW cavity. Increased optical losses and reduced gain volume by the dimension reduction are compensated by excellent NW morphology and InGaAs/GaAs multi-quantum disks. At 5 K, a threshold low as 1.6 μJ/cm2 per pulse is achieved with a resulting quality factor exceeding 6400. By further passivating the NW with an AlGaAs shell to suppress surface non-radiative recombination, single-mode lasing operation is obtained with a threshold of only 48 μJ/cm2 per pulse at room temperature with a high characteristic temperature of 223 K and power output of ~ 0.9 μW. These single-mode, ultralow threshold, high power output NW lasers are promising for the development of near-infrared nanoscale coherent light sources for integrated photonic circuits, sensing, and spectroscopy.

physics.optics↗

arXiv2021

Let There be Light: Improved Traffic Surveillance via Detail Preserving Night-to-Day Transfer

In recent years, image and video surveillance have made considerable progresses to the Intelligent Transportation Systems (ITS) with the help of deep Convolutional Neural Networks (CNNs). As one of the state-of-the-art perception approaches, detecting the interested objects in each frame of video surveillance is widely desired by ITS. Currently, object detection shows remarkable efficiency and reliability in standard scenarios such as daytime scenes with favorable illumination conditions. However, in face of adverse conditions such as the nighttime, object detection loses its accuracy significantly. One of the main causes of the problem is the lack of sufficient annotated detection datasets of nighttime scenes. In this paper, we propose a framework to alleviate the accuracy decline when object detection is taken to adverse conditions by using image translation method. We propose to utilize style translation based StyleMix method to acquire pairs of day time image and nighttime image as training data for following nighttime to daytime image translation. To alleviate the detail corruptions caused by Generative Adversarial Networks (GANs), we propose to utilize Kernel Prediction Network (KPN) based method to refine the nighttime to daytime image translation. The KPN network is trained with object detection task together to adapt the trained daytime model to nighttime vehicle detection directly. Experiments on vehicle detection verified the accuracy and effectiveness of the proposed approach.

cs.CV↗

arXiv2021

Auto-Exposure Fusion for Single-Image Shadow Removal

Shadow removal is still a challenging task due to its inherent background-dependent and spatial-variant properties, leading to unknown and diverse shadow patterns. Even powerful state-of-the-art deep neural networks could hardly recover traceless shadow-removed background. This paper proposes a new solution for this task by formulating it as an exposure fusion problem to address the challenges. Intuitively, we can first estimate multiple over-exposure images w.r.t. the input image to let the shadow regions in these images have the same color with shadow-free areas in the input image. Then, we fuse the original input with the over-exposure images to generate the final shadow-free counterpart. Nevertheless, the spatial-variant property of the shadow requires the fusion to be sufficiently `smart', that is, it should automatically select proper over-exposure pixels from different images to make the final output natural. To address this challenge, we propose the shadow-aware FusionNet that takes the shadow image as input to generate fusion weight maps across all the over-exposure images. Moreover, we propose the boundary-aware RefineNet to eliminate the remaining shadow trace further. We conduct extensive experiments on the ISTD, ISTD+, and SRD datasets to validate our method's effectiveness and show better performance in shadow regions and comparable performance in non-shadow regions over the state-of-the-art methods. We release the model and code in https://github.com/tsingqguo/exposure-fusion-shadow-removal.

cs.CV↗

arXiv2019

Ferroelectric driven exciton and trion modulation in monolayer MoSe2 and WSe2

In this work, we show how domain engineered lithium niobate can be used to selectively dope monolayer MoSe2 and WSe2 and demonstrate that these ferroelectric domains can significantly enhance or inhibit photoluminescence (PL) with the most dramatic modulation occurring at the heterojunction interface between two domains. A micro-PL and Raman system is used to obtain spatially resolved images of the differently doped transition metal dichalcogenides (TMDs). The domain inverted lithium niobate causes changes in the TMDs due to electrostatic doping as a result of the remnant polarization from the substrate. Moreover, the differently doped TMDs (n-type MoSe2 and p-type WSe2) exhibit opposite PL modulation. Distinct oppositely charged domains were obtained with a 9-fold PL enhancement for the same single MoSe2 sheet when adhered to the positive (P+) and negative (P-) domains. This sharp PL modulation on the ferroelectric domain results from different free electron or hole concentrations in the materials conduction band or valence band. Moreover, excitons dissociate rapidly at the interface between the P+ and P- domains due to the built-in electric field. We are able to adjust the charge on the P+ and P- domains using temperature via the pyroelectric effect and observe rapid PL quenching over a narrow temperature range illustrating the observed PL modulation is electronic in nature. This observation creates an opportunity to harness the direct bandgap TMD 2D materials as an active optical component for the lithium niobate platform using domain engineering of the lithium niobate substrate to create optically active heterostructures that could be used for photodetectors or even electrically driven optical sources on-chip.

cond-mat.mtrl-sci↗

arXiv2018

Impact of Land Use on the DOM Composition in Different Seasons in a Subtropical River Flowing through the Region Undergoing Rapid Urbanization

The dissolved organic matter (DOM) composition in river ecosystems could reflect the human impacts on the river ecosystem, and plays an important role in the carbon cycling process. We collected water and phytoplankton samples at 107 sites in the Dongjiang River in two seasons to assess the impact of the sub-catchments land use structure on the DOM composition. The results showed that (1) the forested sub-catchments had higher humic-like C1 (16.45%) and C2 (25.04%) and lower protein-like C3 (22.57%) and C4 (35.95%) than urbanized and mixed forest-agriculture sub-catchments, while the urbanized sub-catchments showed an inverse trend (4.54%, 15.51%, 33.97% and 45.98%, respectively). (2) The significant variation in the proportion of C1 and C4 between the dry and rainy seasons was recorded in both the forested and the mixed forest-agriculture sub-catchments (p<0.01), but only C4 showed an obvious seasonal variation in the urbanized sub-catchments (p<0.01). While the DOM composition was mainly related to the proportion of urbanized land and forested land year-round (p<0.01), it had stronger correlation with forested land in the dry season and urbanized land in the rainy season. (3) No significant correlation between the DOM composition and the agricultural land proportion was found in either season (p>0.05). Our findings indicated that the DOM composition was strongly dependent on the land use structure of the sub-catchments and varied seasonally, but the seasonal variation pattern could be disturbed by human activities in the extensively urbanized catchments. Notably, the higher C4 proportion compared with those in temperate rivers implied a larger amount of CO2 released from the subtropical rivers into the atmosphere when considering bioavailability.

q-bio.PE↗

arXiv2016

Molecule-Induced Conformational Change in Boron Nitride Nanosheets with Enhanced Surface Adsorption

Surface interaction is extremely important to both fundamental research and practical application. Physisorption can induce shape and structural distortion (i.e. conformational changes) in macromolecular and biomolecular adsorbates, but such phenomenon has rarely been observed on adsorbents. Here, we demonstrate theoretically and experimentally that atomically thin boron nitride (BN) nanosheets as an adsorbent experience conformational changes upon surface adsorption of molecules, increasing adsorption energy and efficiency. The study not only provides new perspectives on the strong adsorption capability of BN nanosheets and many other two-dimensional nanomaterials but also opens up possibilities for many novel applications. For example, we demonstrate that BN nanosheets with the same surface area as bulk hBN particles are more effective in purification and sensing.

cond-mat.mes-hall↗

arXiv2014

Extraordinarily bound quasi-one-dimensional trions in two-dimensional phosphorene atomic semiconductors

The anisotropic nature of the new two-dimensional (2D) material phosphorene, in contrast to other 2D materials such as graphene and transition metal dichalcogenide (TMD) semiconductors, allows excitons to be confined in a quasi-one-dimensional (1D) space predicted in theory, leading to remarkable phenomena arising from the reduced dimensionality and screening. Here, we report a trion (charged exciton) binding energy of 190 meV in few-layer phosphorene at room temperature, which is nearly one to two orders of magnitude larger than those in 2D TMD semiconductors (20-30 meV) and quasi-2D quantum wells (1-5 meV). Such a large binding energy has only been observed in truly 1D materials such as carbon nanotubes, whose optoelectronic applications have been severely hurdled by their intrinsically small optical cross-sections. Phosphorene offers an elegant way to overcome this hurdle by enabling quasi-1D excitonic and trionic behaviors in a large 2D area, allowing optoelectronic integration. We experimentally validated the quasi-1D nature of excitonic and trionic dynamics in phospherene by demonstrating completely linearly polarized light emission from excitons and trions. The implications of the extraordinarily large trion binding energy in a higher-than-one-dimensional material are far-reaching. It provides a room-temperature 2D platform to observe the fundamental many-body interactions in the quasi-1D region. The strong photoluminescence emission in phosphorene has been electrically tuned over a large spectral range at room temperature, which opens a new route for tunable light sources.

cond-mat.mtrl-sci↗