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This paper presents an integrated neural regularization method in fully-connected neural networks that jointly combines the cutting edge of regularization techniques; Dropout [1] and DropConnect [2]. With a small number of data set, trained feed-forward networks tend to show poor prediction performance on test data which has never been introduced while training. In order to reduce the overfitting,...
Noise and variability in accelerometer data collected using smart devices obscure accurate human activity recognition. In order to tackle the degradation of the triaxial accelerometer data caused by noise and individual user differences, we propose a statistical noise reduction method using total variation minimization to attenuate the noise mixed in the magnitude feature vector generated from triaxial...
Quadrotor unmanned aerial vehicles (UAVs) have seen a surge of use in various applications due to its structural simplicity and high maneuverability. However, conventional control methods using joysticks prohibit novices from getting used to maneuvering quadrotors in short time. In this paper, we suggest the use of a wearable device, such as a smart watch, as a new remote-controller for a quadrotor...
In this paper, we present an approach to Multi-Object Tracking (MOT) that is based on the Ensemble Kalman Filter (EnKF). The EnKF is a standard algorithm for data assimilation in high-dimensional state spaces that is mainly used in geosciences, but has so far only attracted little attention for object tracking problems. In our approach, the Optimal Subpattern Assignment (OSPA) distance is used for...
The centralized Kalman filter can be implemented in such a way that the required calculations can be distributed over multiple nodes in a network, each of which processes only the locally acquired sensor data. The main downside of this implementation is that it requires each distributed sensor node to communicate with the fusion center in every time step so as to compute the optimal state estimate...
Many applications demand proper design and implementation of 0-1 binary compressive sensing (CS) measurement matrices. This paper presents a construction method for such binary CS measurement matrices by training a convolutional neural network (CNN) with 0-1 weights. The desired CS performance of resultant binary measurement matrices can be achieved by designing a proper CNN training procedure. For...
Granger causality is proposed to fuse stock prices and social media sentiment information for stock market prediction. Sentiment extraction is performed on the Twitter data from major stock companies. Analysis shows that authoritative user's sentiment affects the other users after an event with the lag of 3 days. The prediction is performed for Twitter and stock data from four companies. The sentiment...
With the aim of providing a fast and effective segmentation method based on the flood-fill algorithm, in this study, we propose a new approach to segment a 3D point cloud gained by a 3D multi-channel laser range sensor into different objects. First, we divide the point cloud into two groups: ground and nonground points. Next, we segment clusters in each scanline dataset from the group of nonground...
This study explores the non-parametric estimation of a shape boundary from noisy points in 2D when the sensor characteristics are known. As the underlying shape information is not known, the offered algorithm estimates points on the shape boundary by using the statistics of the subsets of point cloud data. The novel approach proposed in this paper is able to find corner points in a local geometry...
The autonomous navigation of unmanned aerial vehicles (UAVs) require a lot of sensing modalities to improve their cruise efficiency. This paper presents a system for autonomous navigation and path planning of UAVs in GPS-denied environment based on the fusion of geo-registered 3D point clouds with proprioceptive sensors (IMU, odometry and barometer) and the 2D Google maps. The contributions of this...
INS and GNSS integrated systems have become widespread as a result of low-cost MEMS inertial sensor technology. However, the accuracy of computed velocity and orientation is not sufficient for some applications, e.g. performance and technique monitoring and evaluation in sports. Significant accuracy improvements can be made by post-mission data processing. The approach is based on fixed-lag Rauch-Tung-Striebel...
This paper proposes a novel joint probabilistic data association (JPDA) filter for joint target tracking and track maintenance in the presence of unknown detection probability and clutter rate. The proposed algorithm consists of two main parts: (1) the standard JPDA filter with a Poisson point process birth model for multi-object state estimation; and (2) a multi-Bernoulli filter for detection probability...
In recent years, the usage of unmanned aircraft systems (UAS) for security-related purposes has increased, ranging from military applications to different areas of civil protection. The deployment of UAS can support security forces in achieving an enhanced situational awareness. However, in order to provide useful input to a situational picture, sensor data provided by UAS has to be integrated with...
Geospatial Intelligence analysis involves the combination of multi-source information expressed in logical form (as sentences or statements), computational form (as numerical models of physics or other processes), and sensor data (as measurements from transducers). Each of these forms has its own way to describe uncertainty or error: e.g., frequency models, algorithmic truncation, floating point roundoff,...
Up to the present day, GPS signals are the key component in almost all outdoor navigation tasks of robotic platforms. To obtain the platform pose, comprising the position as well as the orientation, and receive information at a higher frequency, the GPS signals are commonly used in a GPS-corrected inertial navigation system (INS). The GPS is a critical single point of failure, especially for autonomous...
This paper presents a connectivity control algorithm of a multi-agent system. The connectivity of the multi-agent system can be represented by the second smallest eigenvalue λ2 of the Laplacian matrix LG and it is also referred to as algebraic connectivity. Unlike many of the existing connectivity control algorithms which adapt convex optimization technique to maximize algebraic connectivity, we first...
We investigate methods to define a probabilistic logic and their application to multi-source fusion problems in geospatial decision support systems1. We begin with a discussion of augmenting propositional calculus with probabilities. Given a set of sentences, S, each with a known probability, the problem is to determine the probability of a query sentence that is a disjunction of literals appearing...
Millimeter wave (MMW) readily penetrates fabrics, thus it can be used to detect objects concealed under clothing. A passive MMW imaging system can operate as a stand-off type sensor that scans people away from the system. However, the image often suffers from low image quality due to the diffraction limit and low signal level. In the paper, we discuss four image interpolation methods to recognize...
This paper presents a new line based 6-DOF monocular algorithm that uses the iSAM2, a point-based Graph SLAM approach. We extend iSAM2 to minimize the reprojection error of the line features to solve the line-based SLAM problem. A specific line representation is exploited that combines the Plücker Coordinates and the Cayley representation. The Plücker Coordinates are used for the 3D line projection...
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