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Transportation agencies strive to keep people and goods moving. Operation and maintenance of transportation infrastructure is key to accomplish their objectives. Intelligent Transportation Systems (ITS) applications rely on massive detection grids that collectively demand significant maintenance resources. Resource constraints force transportation agencies to look for innovative ways to optimize their...
Programs written in unsafe languages like C and C++ often suffer from errors like buffer overflows, dangling pointers, and memory leaks. Dynamic analysis tools like Valgrind can detect these errors, but their overhead — primarily due to the cost of instrumenting every memory read and write — makes them too heavyweight for use in deployed applications and makes testing with them painfully slow. The...
Our objective is to count objects using a single frame from a surveillance camera. We focus on the area where individual object detectors fail, mostly due to clutter, occlusion, or variations in scene due to perspective change. For tackling the counting problem, first the object density is estimated by using ridge regression. Object counts are then estimated by integrating the density over the region...
This paper proposes a Bayesian detector for spectrum sensing in a multi-antenna cognitive radio (CR) network in which no channel state information (CSI) is available. The Bayesian approach for detection necessitates a prior distribution of the CSI in terms of the spatial covariance matrix, and unfortunately it is often improper and cannot be applied directly. We shall introduce the use of the Fractional...
This paper investigates practical strategies for distributing payload across images with content-adaptive steganography and for pooling outputs of a single-image detector for steganalysis. Adopting a statistical model for the detector's output, the steganographer minimizes the power of the most powerful detector of an omniscient Warden, while the Warden, informed by the payload spreading strategy,...
A generalized sequential probability ratio test (GSPRT) is a classical algorithm for binary sequential hypothesis testing. Though it is well-studied in the literature, there has been no optimal design of this test due to the difficulty of choosing its thresholds. In this paper we formulate the binary sequential hypothesis testing as an optimization problem. The latter is non-convex, and finding a...
This paper presents a novel technique of image classification using BOVW model. The entire process first involves feature detection of images using FAST, the choice made in order to speed up the process of detection. Then comes the stage of feature extraction for which FREAK, a binary feature descriptor is employed. K-means clustering is then applied in order to make the bag of visual words. Every...
Silicon photo-multipliers (SiPMs) are currently progressively replacing photo-multipliers tubes (PMTs) in most applications due to their technical advantages, specially in high energy physics experiments. This work describes a system to test photo-detectors in order to calibrate and characterize the parameters generally defined by scientific projects requirements. The system controls and monitors...
Run-time malware detection strategies are efficient and robust, which get more and more attention. In this paper, we use I/O Request Package (IRP) sequences for malware detection. N-gram will be used to analyze IRP sequences for feature extraction. Integrated Negative Selection Algorithm (NSA) and Positive Selection Algorithm (PSA), through a selection of n-gram sequences which only exist in malware...
We present a novel approach towards web video classification and recounting that uses video segments to model an event. This approach overcomes the limitations faced by the classical video-level models such as modeling semantics, identifying informative segments in a video and background segment suppression. We posit that segment-based models are able to identify both the frequently-occurring and...
Identifying arbitrary power grid topologies in real time based on measurements in the grid is studied. A learning based approach is developed: binary classifiers are trained to approximate the maximum a-posteriori probability (MAP) detectors that each identifies the status of a distinct line. An efficient neural network architecture in which features are shared for inferences of all line statuses...
This insulation maintenance guide is applicable to rotating electric machines rated from 35 kVA and higher. The procedures detailed herein may also be useful for insulation maintenance of other types of machines.
Real-time human detection is a challenging task due to appearance variance, occlusion and rapidly changing content; therefore it requires efficient hardware and optimized software. This paper presents a real-time human detection scheme on a Raspberry Pi. An efficient algorithm for human detection is proposed by processing regions of interest (ROI) based upon foreground estimation. Different number...
In this paper we develop statistical detection theory for graph signals. In particular, given two graphs, namely, a background graph that represents an usual activity and an alternative graph that represents some unusual activity, we are interested in answering the following question: To which of the two graphs does the observed graph signal fit the best? To begin with, we assume both the graphs are...
This paper is made up of a series of performance evaluations of computer vision algorithms, namely detectors and descriptors. The OpenCV 3.1 implementations of these algorithms were used for these evaluations. The main purpose behind these evaluations was to determine the best algorithms to use for a UAV guidance system.
This paper presents a robust machine learning based computational solution for human detection. The proposed mechanism is specifically applicable for pose-variant situations in video frames. In order to address the pose variance problem, features are extracted using an improved variant of Histograms of Gradients (HoG) and local Binary Pattern features (LBP). The two feature sets are combined to form...
Vehicle detection is an essential task in an intelligent vehicle. Despite being a well-studied vision problem, it is unclear how well vehicle detectors generalize to new settings. Specifically, this paper studies the generalization capability of vehicle detectors on a U.S. highway dataset. Two types of models are employed in the experimental analysis, a subcategory aggregate channel features model...
By participating in NASA's Undergraduate Student Instrumentation Project (USIP), faculty members from physics and electrical and computer engineering (ECE) mentored 21 students in extracurricular undergraduate research ranging from freshman through seniors, predominantly from the ECE department, but also from other departments in science and engineering.
Microstrip electrodes have been fabricated and combined with one and five suspended 6Li foils positioned within a pressurized, gas-filled chamber to create a suspended foil microstrip neutron detector. This new detector offers a mechanically and electrically robust alternative to multi-wire proportional counters. Incident neutrons are converted into charged-particle reaction products that ionize the...
We present a system for reading out signals from an array of 8 superconducting single photon detectors, which implements a high-performance architecture of multi-channel TDC in programmable logic with resolution guaranteed below 22 ps referred to each single channel. Each one of the 8 channels of the system consists of a detector, an analog conditioning stage, a comparator, and one channel of the...
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