Few-shot Object Detection on Remote Sensing Images

In this paper, we deal with the problem of object detection on remote sensing images. Previous methods have developed numerous deep CNN-based methods for object detection on remote sensing images and the report remarkable achievements in detection performance and efficiency. However, current CNN-based methods mostly require a large number of annotated samples to train deep neural networks and tend to have limited generalization abilities for unseen object categories. In this paper, we introduce a few-shot learning-based method for object detection on remote sensing images where only a few annotated samples are provided for the unseen object categories. More specifically, our model contains three main components: a meta feature extractor that learns to extract feature representations from input images, a reweighting module that learn to adaptively assign different weights for each feature representation from the support images, and a bounding box prediction module that carries out object detection on the reweighted feature maps. We build our few-shot object detection model upon YOLOv3 architecture and develop a multi-scale object detection framework. Experiments on two benchmark datasets demonstrate that with only a few annotated samples our model can still achieve a satisfying detection performance on remote sensing images and the performance of our model is significantly better than the well-established baseline models.Comment: 12pages, 7 figure

Enhanced independent pole control of hybrid MMC-HVDC system

This paper presents an enhanced independent pole control scheme for hybrid modular multilevel converter (MMC) based on full bridge sub-module (FBSM) and half bridge sub-module (HBSM). A detailed analysis of power distribution between upper and lower arms under asymmetrical DC pole voltages is presented. It is found that the fundamental AC currents in the upper and lower arms are asymmetrical. To enable operation under asymmetrical DC pole voltages, an enhanced independent pole control scheme is proposed. The controller is composed of two DC control loops, two AC control loops and circulating current suppression control based on current injection. Six modulation indices are presented to independently control the upper and lower arms. With this controller, the DC voltage operating region is significantly extended. To ride through pole to ground DC fault without bringing DC bias at the neutral point of interface transformer, a pole to ground DC fault ride through strategy is proposed. Feasibility and effectiveness of the proposed control scheme are verified by simulation results using PSCAD/EMTDC

Lattice strain effects on the optical properties of MoS2 nanosheets.

"Strain engineering" in functional materials has been widely explored to tailor the physical properties of electronic materials and improve their electrical and/or optical properties. Here, we exploit both in plane and out of plane uniaxial tensile strains in MoS2 to modulate its band gap and engineer its optical properties. We utilize X-ray diffraction and cross-sectional transmission electron microscopy to quantify the strains in the as-synthesized MoS2 nanosheets and apply measured shifts of Raman-active modes to confirm lattice strain modification of both the out-of-plane and in-plane phonon vibrations of the MoS2 nanosheets. The induced band gap evolution due to in-plane and out-of-plane tensile stresses is validated by photoluminescence (PL) measurements, promising a potential route for unprecedented manipulation of the physical, electrical and optical properties of MoS2

Automatic gauge detection via geometric fitting for safety inspection

For safety considerations in electrical substations, the inspection robots are recently deployed to monitor important devices and instruments with the presence of skilled technicians in the high-voltage environments. The captured images are transmitted to a data station and are usually analyzed manually. Toward automatic analysis, a common task is to detect gauges from captured images. This paper proposes a gauge detection algorithm based on the methodology of geometric fitting. We first use the Sobel filters to extract edges which usually contain the shapes of gauges. Then, we propose to use line fitting under the framework of random sample consensus (RANSAC) to remove straight lines that do not belong to gauges. Finally, the RANSAC ellipse fitting is proposed to find most fitted ellipse from the remaining edge points. The experimental results on a real-world dataset captured by the GuoZi Robotics demonstrate that our algorithm provides more accurate gauge detection results than several existing methods

SOOD: Towards Semi-Supervised Oriented Object Detection

Semi-Supervised Object Detection (SSOD), aiming to explore unlabeled data for boosting object detectors, has become an active task in recent years. However, existing SSOD approaches mainly focus on horizontal objects, leaving multi-oriented objects that are common in aerial images unexplored. This paper proposes a novel Semi-supervised Oriented Object Detection model, termed SOOD, built upon the mainstream pseudo-labeling framework. Towards oriented objects in aerial scenes, we design two loss functions to provide better supervision. Focusing on the orientations of objects, the first loss regularizes the consistency between each pseudo-label-prediction pair (includes a prediction and its corresponding pseudo label) with adaptive weights based on their orientation gap. Focusing on the layout of an image, the second loss regularizes the similarity and explicitly builds the many-to-many relation between the sets of pseudo-labels and predictions. Such a global consistency constraint can further boost semi-supervised learning. Our experiments show that when trained with the two proposed losses, SOOD surpasses the state-of-the-art SSOD methods under various settings on the DOTA-v1.5 benchmark. The code will be available at https://github.com/HamPerdredes/SOOD.Comment: Accepted to CVPR 2023. Code will be available at https://github.com/HamPerdredes/SOO

N-cadherin in osteolineage cells modulates stromal support of tumor growth

Tumor growth and metastases are dependent on interactions between cancer cells and the local environment. Expression of the cell-cell adhesion molecule N-cadherin (Ncad) is associated with highly aggressive cancers, and its expression by osteogenic cells has been proposed to provide a molecular dock for disseminated tumor cells to establish in pre-metastatic niches within the bone. To test this biologic model, we conditionally deleted the Ncad gene

Depositing boron on Cu(111): Borophene or boride?

Large-area single-crystal surface structures were successfully prepared on Cu(111) substrate with boron deposition, which is critical for prospective applications. However, the proposed borophene structures do not match the scanning tunneling microscopy (STM) results very well, while the proposed copper boride is at odds with the traditional knowledge that ordered copper-rich borides normally do not exist due to small difference in electronegativity and large difference in atomic size. To clarify the controversy and elucidate the formation mechanism of the unexpected copper boride, we conducted systematic STM, X-ray photoelectron spectroscopy and angle-resolved photoemission spectroscopy investigations, confirming the synthesis of two-dimensional copper boride rather than borophene on Cu(111) after boron deposition under ultrahigh vacuum. First-principles calculations with defective surface models further indicate that boron atoms tend to react with Cu atoms near terrace edges or defects, which in turn shapes the intermediate structures of copper boride and leads to the formation of stable Cu-B monolayer via large-scale surface reconstruction eventually.Comment: 15 pages, 4 figure

Helium-bearing superconductor at high pressure

Helium (He) is the most inert noble gas at ambient conditions. It adopts a hexagonal close packed structure (P63/mmc) and remains in the insulating phase up to 32 TPa. In contrast, lithium (Li) is one of the most reactive metals at zero pressure, while its cubic high-pressure phase (Fd-3m) is a weak metallic electride above 475 GPa. Strikingly, a stable compound of Li5He2 (R-3m) was formed by mixing Fd-3m Li with P63/mmc He above 700 GPa. The presence of helium promotes the lattice transformation from Fd-3m Li to Pm-3m Li, and tuns the three-dimensional distributed interstitial electrons into the mixture of zero- and two-dimensional anionic electrons. This significantly increases the degree of metallization at the Fermi level, consequently, the coupling of conductive anionic electrons with the Li-dominated vibrations is the key factor to the formation of superconducting electride Li5He2 with a transition temperature up to 26 K, dynamically stable to pressures down to 210 GPa.Comment: 5 pages, 3 figure