Towards Multi-class Object Detection in Unconstrained Remote Sensing Imagery

Automatic multi-class object detection in remote sensing images in unconstrained scenarios is of high interest for several applications including traffic monitoring and disaster management. The huge variation in object scale, orientation, category, and complex backgrounds, as well as the different camera sensors pose great challenges for current algorithms. In this work, we propose a new method consisting of a novel joint image cascade and feature pyramid network with multi-size convolution kernels to extract multi-scale strong and weak semantic features. These features are fed into rotation-based region proposal and region of interest networks to produce object detections. Finally, rotational non-maximum suppression is applied to remove redundant detections. During training, we minimize joint horizontal and oriented bounding box loss functions, as well as a novel loss that enforces oriented boxes to be rectangular. Our method achieves 68.16% mAP on horizontal and 72.45% mAP on oriented bounding box detection tasks on the challenging DOTA dataset, outperforming all published methods by a large margin (+6% and +12% absolute improvement, respectively). Furthermore, it generalizes to two other datasets, NWPU VHR-10 and UCAS-AOD, and achieves competitive results with the baselines even when trained on DOTA. Our method can be deployed in multi-class object detection applications, regardless of the image and object scales and orientations, making it a great choice for unconstrained aerial and satellite imagery.Comment: ACCV 201

Dexmo: An inexpensive and lightweight mechanical exoskeleton for motion capture and force feedback in VR

We present Dexmo: an inexpensive and lightweight mechanical exoskeleton system for motion capturing and force feedback in virtual reality applications. Dexmo combines multiple types of sensors, actuation units and link rod structures to provide users with a pleasant virtual reality experience. The device tracks the user’s motion and uniquely provides passive force feedback. In combination with a 3D graphics rendered environment, Dexmo provides the user with a realistic sensation of interaction when a user is for example grasping an object. An initial evaluation with 20 participants demonstrate that the device is working reliably and that the addition of force feedback resulted in a significant reduction in error rate. Informal comments by the participants were overwhelmingly positive.This is the accepted manuscript. The final version is available at http://dl.acm.org/citation.cfm?doid=2858036.2858487

Non-Negative Local Sparse Coding for Subspace Clustering

Subspace sparse coding (SSC) algorithms have proven to be beneficial to clustering problems. They provide an alternative data representation in which the underlying structure of the clusters can be better captured. However, most of the research in this area is mainly focused on enhancing the sparse coding part of the problem. In contrast, we introduce a novel objective term in our proposed SSC framework which focuses on the separability of data points in the coding space. We also provide mathematical insights into how this local-separability term improves the clustering result of the SSC framework. Our proposed non-linear local SSC algorithm (NLSSC) also benefits from the efficient choice of its sparsity terms and constraints. The NLSSC algorithm is also formulated in the kernel-based framework (NLKSSC) which can represent the nonlinear structure of data. In addition, we address the possibility of having redundancies in sparse coding results and its negative effect on graph-based clustering problems. We introduce the link-restore post-processing step to improve the representation graph of non-negative SSC algorithms such as ours. Empirical evaluations on well-known clustering benchmarks show that our proposed NLSSC framework results in better clusterings compared to the state-of-the-art baselines and demonstrate the effectiveness of the link-restore post-processing in improving the clustering accuracy via correcting the broken links of the representation graph.Comment: 15 pages, IDA 2018 conferenc

Vascular change and opposing effects of the angiotensin type 2 receptor in a mouse model of vascular cognitive impairment

Our aims were to assess the spatiotemporal development of brain pathology in a mouse model of chronic hypoperfusion using magnetic resonance imaging (MRI), and to test whether the renin-angiotensin system (RAS) can offer therapeutic benefit. For the first time, different patterns of cerebral blood flow alterations were observed in hypoperfused mice that ranged from an immediate and dramatic to a delayed decrease in cerebral perfusion. Diffusion tensor imaging revealed increases in several quantitative parameters in different brain regions that are indicative of white-matter degeneration; this began around 3 weeks after induction of hypoperfusion. While this model may be more variable than previously reported, neuroimaging tools represent a promising way to identify surrogate markers of pathology. Vascular remodelling was observed in hypoperfused mice, particularly in the anterior part of the Circle of Willis. While the angiotensin II receptor type 2 agonist, Compound 21 (C21), did not influence this response, it did promote expansion of the basilar artery in microcoil animals. Furthermore, C21-treated animals exhibited increased brain lymphocyte infiltration, and importantly, C21 had opposing effects on spatial reference memory in hypoperfused and sham mice. These results suggest that the RAS may have a role in vascular cognitive impairment

Requirement of Mouse BCCIP for Neural Development and Progenitor Proliferation

Multiple DNA repair pathways are involved in the orderly development of neural systems at distinct stages. The homologous recombination (HR) pathway is required to resolve stalled replication forks and critical for the proliferation of progenitor cells during neural development. BCCIP is a BRCA2 and CDKN1A interacting protein implicated in HR and inhibition of DNA replication stress. In this study, we determined the role of BCCIP in neural development using a conditional BCCIP knock-down mouse model. BCCIP deficiency impaired embryonic and postnatal neural development, causing severe ataxia, cerebral and cerebellar defects, and microcephaly. These development defects are associated with spontaneous DNA damage and subsequent cell death in the proliferative cell populations of the neural system during embryogenesis. With in vitro neural spheroid cultures, BCCIP deficiency impaired neural progenitor's self-renewal capability, and spontaneously activated p53. These data suggest that BCCIP and its anti-replication stress functions are essential for normal neural development by maintaining an orderly proliferation of neural progenitors

Controlling a magnetic Feshbach resonance with laser light

The capability to tune the strength of the elastic interparticle interaction is crucial for many experiments with ultracold gases. Magnetic Feshbach resonances are a tool widely used for this purpose, but future experiments would benefit from additional flexibility such as spatial modulation of the interaction strength on short length scales. Optical Feshbach resonances offer this possibility in principle, but suffer from fast particle loss due to light-induced inelastic collisions. Here we show that light near-resonant with a molecular bound-to-bound transition can be used to shift the magnetic field at which a magnetic Feshbach resonance occurs. This makes it possible to tune the interaction strength with laser light and at the same time induce considerably less loss than an optical Feshbach resonance would do

Optimization of a high work function solution processed vanadium oxide hole-extracting layer for small molecule and polymer organic photovoltaic cells

We report a method of fabricating a high work function, solution processable vanadium oxide (V2Ox(sol)) hole-extracting layer. The atmospheric processing conditions of film preparation have a critical influence on the electronic structure and stoichiometry of the V2Ox(sol), with a direct impact on organic photovoltaic (OPV) cell performance. Combined Kelvin probe (KP) and ultraviolet photoemission spectroscopy (UPS) measurements reveal a high work function, n-type character for the thin films, analogous to previously reported thermally evaporated transition metal oxides. Additional states within the band gap of V2Ox(sol) are observed in the UPS spectra and are demonstrated using X-ray photoelectron spectroscopy (XPS) to be due to the substoichiometric nature of V2Ox(sol). The optimized V2Ox(sol) layer performance is compared directly to bare indium–tin oxide (ITO), poly(ethyleneoxythiophene):poly(styrenesulfonate) (PEDOT:PSS), and thermally evaporated molybdenum oxide (MoOx) interfaces in both small molecule/fullerene and polymer/fullerene structures. OPV cells incorporating V2Ox(sol) are reported to achieve favorable initial cell performance and cell stability attributes