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This paper proposes a lane estimation algorithm on roads where lanes are not visible due to fading or bad weather conditions. The proposed algorithm is conducted by utilizing the road width and remained lines on roads. The results indicate that the proposed algorithm can estimate lanes in heavy rains and nights.
Distributed renewable energy generations bring to attention the grid-connected inverter with LCL filter, whose control performance can be largely influenced by filter parameter variations. This paper has proposed a “comprehensive-loop-search, pattern-recognition, key-parameter-scan” method to evaluate the parameter variation influence, especially grid-side inductance and filter capacitance variation,...
Utilization of millimeter-wave bands by next generation mobile networks is expected to make extremely high data rates realizable. However, at such high frequencies, phase noise (PHN) can significantly affect the performance of the communication system. Filter Bank Multi-Carrier systems with Offset Quadrature Amplitude Modulation (FBMC-OQAM) have received increased attention in recent years, but the...
In this paper, we propose the use of multiple Gaussian kernels for distributed nonlinear regression or system identification tasks by a network of nodes. By employing multiple kernels in the estimation process we increase the degree of freedom and thus, the ability to reconstruct nonlinear functions. For this, we extend the so-called KDiCE algorithm, which allows a distributed regression of nonlinear...
Most of the decision fusion techniques developed for the remote sensing applications have the drawback of assuming the conditional independence between the classification results, whereas, usually the correlation exists due to the same measuring instrument or same area under study. Fusion of Correlated Probabilities (FCP) method has a potential to deal with conditional dependence only for two data...
In this paper, distributed Nash equilibrium seeking for multi-agent games, particularly for games where the players' payoff functions are partially coupled, is investigated. To model the (partial, explicit) dependence of the players' payoff functions on the players' actions, an interference graph is introduced. Besides, the players are supposed to be equipped with a communication graph to achieve...
Crowd behaviour analysis is a challenging task in computer vision, mainly due to the high complexity of the interactions between groups and individuals. This task is particularly crucial given the magnitude of manual monitoring required for effective crowd management. Within this context, a key challenge is to conceive a highly generic, fine and context-independent characterisation of crowd behaviours...
The last years have seen a quick rise of digital photography. Plenoptic cameras provide extended capabilities with respect to previous models. Multi-focus cameras enlarge the depth-of-field of the pictures using different focal lengths in the lens composing the array, but questions still arise on how to select and use these lenses. In this work a further insight on the lens selection was made, and...
Different from representation learning models using deep learning to project original feature space into lower density ones, we propose a feature space learning (FSL) model based on a semi-supervised clustering framework. There are three main contributions in our approach: (1) Inspired by Zipf's law and word bursts, the feature space learning processes not only select trusted unlabeled samples and...
This paper presents the results of the depth estimation challenge for dense light fields, which took place at the second workshop on Light Fields for Computer Vision (LF4CV) in conjunction with CVPR 2017. The challenge consisted of submission to a recent benchmark [7], which allows a thorough performance analysis. While individual results are readily available on the benchmark web page http://www...
Learning the dynamics of shape is at the heart of many computer vision problems: object tracking, change detection, longitudinal shape analysis, trajectory classification, etc. In this work we address the problem of statistical inference of diffusion processes of shapes. We formulate a general Itô diffusion on the manifold of deformable landmarks and propose several drift models for the evolution...
In this paper, a nonlinear estimator is developed to estimate the effect of friction on the performance of an ultrasonic motor (USM). Based on the friction model of USM, a friction estimator based compensator is developed for eliminating the effect of friction existing in between the surfaces of stator and rotor of the USM. Then, a proportional plus integral (PI) control strategy with friction estimator...
In this paper we present a mobile application and solution for accurate smart indoor positioning. Smart society applications do normally require user location, specifically, in indoor environments high accuracy can enrich augmented or virtual reality, gaming, in-building guidance or support for ambient assisted living. We use encoded ultrasonic signals and TDMA protocol to obtain fine-grained distance...
Automatic and accurate human upper-body detection and orientation estimation have great practical value in several computer vision applications. Most previous works on human upper-body orientation estimation assume that the human upper-body region is already detected and aligned. However, this is not the case in many real-world scenarios. Additional human detector is essential which is usually much...
Cache policies to minimize the content retrieval cost have been studied through competitive analysis when the miss costs are additive and the sequence of content requests is arbitrary. More recently, a cache utility maximization problem has been introduced, where contents have stationary popularities and utilities are strictly concave in the hit rates. This paper bridges the two formulations, considering...
Rate distortion optimization helps decide the best coding mode and partition to improve coding efficiency, but suffers from serious data dependency and complexity that hinders an efficient hardware encoder implementation. Thus, this paper presents a hardware-friendly fast rate-distortion method and its design. For rate estimation, we propose a context group adaptive entropy based method for more precise...
Given the ever-expanding scale of WiFi deployments in metropolitan areas, we have reached the point where accurate GPS-free outdoor localization becomes possible by relying solely on the WiFi infrastructure. Nevertheless, the existing industrial practices do not seem to have the right implementation to achieve an adequate accuracy, while the academic researches that are mostly attracted by indoor...
The proposed integrated system is based on the methodology and strategy of solving the problem of guaranteed safety and survivability of complex technical object (CTO) functioning, that ensures the timely decision regarding the change of object's operation mode, providing the capacity for manual correction of a set of parameters with the purpose of returning their values to a normal mode. The advantage...
Development of automatic speech recognition (ASR) systems robust to late reverberation action is urgent task. It is well known that a late reverberation reduction algorithm used as ASR pre-processor demands prior estimation of reverberation time. Blind reverberation time measurements are less accurate than ones for known room impulse response (RIR) direct measurements. As result, it is naturally expect...
The objective of this paper is to propose the rule-based algorithmic approach for solving problems of faults influence on the service quality in access networks. In this paper the graph oriented model for network and communication services representation, the rule-based system and corresponding output mechanism, the algorithms for the faults impact analysis based on graph traversal schemes are proposed...
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