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Modeling instance-level context and object-object relationships is extremely challenging. It requires reasoning about bounding boxes of different classes, locations etc. Above all, instance-level spatial reasoning inherently requires modeling conditional distributions on previous detections. Unfortunately, our current object detection systems do not have any memory to remember what to condition on!...
A novel wideband dual-polarized magneto-electric dipole unidirectional antenna is proposed in this paper. The antenna is composed of dual-layer magneto-electric (ME)-dipole and two Γ-shaped probes. Its two ports both achieve a common impedance bandwidth of 91.6%(SWR<2). The antenna has excellent performance in isolation, which is more than 15dB, and a high front-to-back ration more than 14.8dB...
In this paper, squeezing and tunneling of spoof surface plasmon polaritons (SSPPs) are realized by introducing an effective epsilon-near-zero (ENZ) material between two plasmonic waveguides constructed from dielectric filled rectangular waveguide etched with deep sub-wavelength periodical transverse slots on the upper wall. This simple design holds great promise in significantly increasing the propagation...
The Characteristic Basis Function Method (CBFM) has been widely used in recent years to solve a variety of electromagnetic scattering problems because it offers a way to direct-solve large problems without the use of iteration, enabling it to not only handle multiple excitation (r.h.s.) problems in an efficient manner, but to also bypass the issues of ill-conditioning as well as generation of preconditioners...
Unmanned aerial vehicle (UAV) swarms provide situation awareness in potential life-threatening tasks such as emergency response, search and rescue, etc. However, most of these scenarios take place in GPS-denied environments, where accurately localizing each UAV is challenging. Heterogeneous UAV swarms, in which only a subset of the drones carry cameras, face the additional challenge of identifying...
E-loc is an indoor localization system, which, through using existing indoor electric wiring, detects occupants' location. While many indoor localization technologies require intensive infrastructural supports, E-loc obtain locations by injecting a signal into the protected earth line of existing residential power network. Caused by human body inside a room, the electromagnetic character changes can...
This paper presents a fast solution of electromagnetic scattering from perfect electric conductors by using a sparfled adaptive cross approximation-multilevel fast adaptive cross approximation (SPACA-MLFACA) algorithm. In the new method, the conventional SPACA and MLFACA is used to deal with the interactions between well-separated blocks with relative small and large size, respectively. As a result,...
In this paper, a phase-gradient metasurface which consists of 7 arcuate cross-shaped metal-medium-metal units with different geometries is designed to realize anomalous reflection at 3GHz with 99% reflection efficiency of both x-polarized and y-polarized waves. The simulation results on near electric field distributions show excellent agreement of the anomalous reflection angle with theoretical analysis...
The order of the characteristic basis functions (CBFs) has an important influence on efficiency and accuracy of the multiple-scattering (MS) characteristic basis functions method (CBFM). When the object under analysis is divided into many blocks, two or three order CBFs may be enough to obtain accurate results. However, if the number of blocks is small, more high order of the CBFs may be required...
In this paper, the fast direct method, Sherman-Morrison-Woodbury formula-based algorithm (SMWA) with adaptive cross approximation (ACA), is extended to solve the volume integral equation (VIE) for analyzing electromagnetic scattering from dielectric materials. Numerical results are given to prove the benefits of the SWMA for speeding up calculation.
Volume integral equation (VIE) is accelerated by an efficient method as the dense impedance matrix of the method of moment (MoM) is rank-deficient. After dividing all Schaubert-Wilton-Glisson (SWG) basis functions into blocks, the sparsified adaptive cross approximation (SPACA) combined with the fast adaptive sampling (FACS) is used to compress the impedance matrix of far-block pairs. With the method,...
We present an approach to utilize large amounts of web data for learning CNNs. Specifically inspired by curriculum learning, we present a two-step approach for CNN training. First, we use easy images to train an initial visual representation. We then use this initial CNN and adapt it to harder, more realistic images by leveraging the structure of data and categories. We demonstrate that our two-stage...
The Sherman-Morrison-Woodbury formula-based algorithm with the adaptive cross approximation-singular value decomposition (ACA-SVD) is applied to accelerate the direct solution of electromagnetic scattering from three dimension (3D) perfect electric conducting (PEC) targets. The hybrid method is adaptive and purely algebraic. Numerical results are presented to demonstrate the efficiency and accuracy...
In this paper we explore the bi-directional mapping between images and their sentence-based descriptions. Critical to our approach is a recurrent neural network that attempts to dynamically build a visual representation of the scene as a caption is being generated or read. The representation automatically learns to remember long-term visual concepts. Our model is capable of both generating novel captions...
We present a co-clustering framework that can be used to discover multiple semantic and visual senses of a given Noun Phrase (NP). Unlike traditional clustering approaches which assume a one-to-one mapping between the clusters in the text-based feature space and the visual space, we adopt a one-to-many mapping between the two spaces. This is primarily because each semantic sense (concept) can correspond...
In this paper, a sparsified multilevel adaptive cross approximation (SMLACA) is proposed to improve the sparsified adaptive cross approximation (SPACA). Compared with the SPACA, the SMLACA can save the CPU time and memory requirement for large targets. Numerical results are presented to validate the SMLACA and demonstrate its merits.
There have been some recent efforts to build visual knowledge bases from Internet images. But most of these approaches have focused on bounding box representation of objects. In this paper, we propose to enrich these knowledge bases by automatically discovering objects and their segmentations from noisy Internet images. Specifically, our approach combines the power of generative modeling for segmentation...
We propose NEIL (Never Ending Image Learner), a computer program that runs 24 hours per day and 7 days per week to automatically extract visual knowledge from Internet data. NEIL uses a semi-supervised learning algorithm that jointly discovers common sense relationships (e.g., "Corolla is a kind of/looks similar to Car", "Wheel is a part of Car") and labels instances of the given...
In recent years, metric learning methods based on pairwise side information have attracted considerable interests, and lots of efforts have been devoted to utilize these methods for visual analysis like content based image retrieval and face identification. When applied to image analysis, these methods merely look on an n1 × n2 image as a vector in Rn1×n2 space and the pixels of the image are considered...
Some new medical applications, such as wireless endoscopy system for the diagnoses of whole human digestive tract and real-time endoscopic image monitoring, demand high speed transmission in wireless body sensor network (WBSN). This paper proposes a heterogeneous high speed wireless body sensor network based on ZIGBEE and single carrier ultra wideband (SC-UWB). Our system can choose high speed mode...
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