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We study the problem of single-image depth estimation for images in the wild. We collect human annotated surface normals and use them to help train a neural network that directly predicts pixel-wise depth. We propose two novel loss functions for training with surface normal annotations. Experiments on NYU Depth, KITTI, and our own dataset demonstrate that our approach can significantly improve the...
In this paper we propose event goodput, i.e., the fraction of events which may be successfully managed by a system, as a relevant metric to describe the performance of battery powered real-time sensor networks. Unlike other performance metrics as response, completion, maximum lateness times, all representing fundamental, but different, figures of merit for the description of the behavior of real-time...
Camera-enabled sensors deployed for visual monitoring will cover a region of the target field, providing information for many innovative applications based on wireless sensing. Actually, some areas of the monitored field may have more relevance than others, according to the characteristics of the applications, which may indicate that such areas need better coverage to avoid blind spots and achieve...
The increase in the use of mobile devices from the first decade of this century has enabled users to perform several activities previously only possible through personal computers. However, the use of these devices is impacted by their known computational limitations, such as data processing, RAM memory, storage, and energy autonomy limitations. Considering this context, to measure the impact of the...
Cognitive radio networks (CRNs) enable secondary users (SU) to make use of licensed spectrum without interfering with the signal generated by primary users (PUs). To avoid such interference, the SU is required to sense the medium for a period of time and eventually use it only if the band is perceived to be idle. In this context, the encryption process is carried out for the SU requests prior to their...
The problem of coverage in three-dimensional (3D) wireless sensor networks is challenging and hard. In this paper, we focus on the problem of k-coverage of a 3D field of interest (FoI), where every point is covered by at least k sensors. First, we propose three sensor placement strategies to guarantee k-coverage of a 3D FoI. Second, we compute the corresponding sensor density. Third, we investigate...
The paper summarizes basic rules in the design of simple, low cost sensors based on chaotic dynamics, moreover to analyze the influence of the window comparators on the accuracy and precision of these sensors. We show that the comparator blocks in the circuit for determining the time-in-window parameters can be a significant source of errors that can be easily overlooked. A new version of chaotic...
This study focuses on multimodal artifact metrics and proposes a technique based on multimodal biometric systems that are a type of biometric identification systems. It is expected that this technique can aid in verifying the authenticity of each artifact in a more accurate manner and in increasing the level of difficulty involved in counterfeiting when compared to those of existing artifact metric...
This paper describes the design and setup of different measuring systems for the calibration of commercial voltage and current transformer test sets for non-conventional instrument transformers. The calibration systems are recently developed at the national metrology institutes VSL, PTB, METAS and TUBITAK within the frame of the European project “FUTURE GRID — Non-conventional voltage and current...
With the constant increase in the number of interconnected devices in today networks, and the high demand of adaptiveness, more and more computations can be designed according to self-organisation principles. In this context, a key building block for large-scale system coordination, called gradient, is used to estimate distances in a fully-distributed way: it is the basis for a vast variety of higher...
The paper describes the MANET Cognitive Radio test bed. The proposed architecture consists of a number of CR nodes connected to the RF Switch Matrix, and enables simulation, scenario definition and management. Proposed procedures for Opportunistic Spectrum Access in MANET CR are described as well and chosen results of simulations obtained during laboratory tests are presented. The performance of these...
Node compromising is still the most hard attack in Wireless Sensor Networks (WSNs). It affects key distribution which is a building block in securing communications in any network. The weak point of several roposed key distribution schemes in WSNs is their lack of resilience to node compromising attacks. When a node is compromised, all its key material is revealed leading to insecure communication...
The fusion of hyperspectral and multispectral images is a crucial task nowadays for it allows the extraction of relevant information from the fused image. Fusion consists of the combination of the spectral information of the hypespectral image (h) and the spatial information of the multispectral image (m). The fused image (f) has both good spatial and spectral information. In this paper we suggest...
Multitemporal Hyperspectral (HS) images can be used in Change Detection (CD) to identify and discriminate among different kinds of change due to the fine sampling of the spectrum by HS sensors. In this work we propose a novel method for unsupervised multiple CD in multitemporal HS data based on binary Spectral Change Vectors (SCVs) and an agglomerative hierarchical clustering. First, we perform binary...
The design of intelligent powered wheelchairs has traditionally focused heavily on providing effective and efficient navigation assistance. Significantly less attention has been given to the end-user's preference between different assistance paradigms. It is possible to include these subjective evaluations in the design process, for example by soliciting feedback in post-experiment questionnaires...
The advent of widely available photo collections covering broad geographic areas has spurred significant advances in large-scale urban scene modeling. While much emphasis has been placed on reconstruction and visualization, the utility of such models extends well beyond. Specifically, these models should support a wide variety of reasoning tasks (or queries), and thus enable advanced scene study....
Radio environment maps can be a powerful tool for achieving efficient context-aware resource allocation in 5G heterogeneous networks. In this paper, we consider an heterogeneous network formed by a traditional cellular network and a wireless sensor network. The role of the wireless sensor network is to estimate the radio environment map of the cell using a geostatistical interpolation technique named...
A large amount of information is continuously generated in intensive health care. An analysis of these data streams can supply valuable insights to improve the monitoring of the patients. The volume, frequency and complexity of data, which come unlabeled, make their analysis a challenging task. Machine learning (ML) techniques have been successfully employed for mining data streams to extract useful...
Applications like environmental sensing, and health and activity sensing, are supported by networks of devices (nodes) that send periodic packet transmissions over the wireless channel to a sink node. We look at simple abstractions that capture the following commonalities of such networks (a) the nodes send periodically sensed information that is temporal and must be delivered in a timely manner,...
Recently, there have been a large number of proposals for IoT middleware solutions. In addition, a few recent studies have surveyed and qualitatively evaluated these IoT middleware proposals against functional and non-functional features. A quantitative evaluation is also needed to complement these existing qualitative studies and provide a more in-depth perspective of the state of the art. This paper...
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