Search results for "Image"
showing 10 items of 6818 documents
Cloud-based elastic architecture for distributed video encoding: Evaluating H.265, VP9, and AV1
2020
Abstract Areas with social and business impact such as entertainment, healthcare, surveillance, and e-learning would benefit from improvements in video coding and transcoding services. New codecs, such as AV1, are being developed to deal with new demands for high video resolutions with bandwidth constraints and quality requirements. However, these new codecs have high computational requirements and new strategies are needed to accelerate their processing. Cloud computing offers interesting features such as on-demand resource allocation, multitenancy, elasticity, and resiliency among others. Deploying video coding and transcoding services on these infrastructures is suitable because it allow…
Comparison of WSN and IoT approaches for a real-time monitoring system of meal distribution trolleys: A case study
2018
Abstract International regulations determine that food in hospitals and elderly homes must be served at given temperature ranges. However, the real-time surveillance of the meal distribution trolleys along all the institutions facilities, guaranteeing conformity to rules from the instant when all the meals are put in the distribution trolley until they are delivered to the patients, is still a challenge. In this paper, we present a comparison of two approaches based on Wireless Sensor Networks (WSN) and Internet of Things (IoT) technologies for implementing a Real-Time Monitoring System of Meal Distribution Trolleys in a hospital. The performance evaluation results show that the IoT impleme…
SAUCE: A web application for interactive teaching and learning of parallel programming
2017
Abstract Prevalent hardware trends towards parallel architectures and algorithms create a growing demand for graduate students familiar with the programming of concurrent software. However, learning parallel programming is challenging due to complex communication and memory access patterns as well as the avoidance of common pitfalls such as dead-locks and race conditions. Hence, the learning process has to be supported by adequate software solutions in order to enable future computer scientists and engineers to write robust and efficient code. This paper discusses a selection of well-known parallel algorithms based on C++11 threads, OpenMP, MPI, and CUDA that can be interactively embedded i…
A holistic modeling for QoE estimation in live video streaming applications over LTE Advanced technologies with Full and Non Reference approaches
2018
Abstract Current mobile networks are providing high speed access to Internet at a rate of Gigabits per second. In this scenario, traditional services over wired networks are an alternative, in particular those based on live video streaming. But in the transition, different issues should be considered due to the rapid changing network conditions and the limited resources of the mobile devices. These issues should be taken into account to keep a good Quality of Experience (QoE) of the video in terms of a high Mean Opinion Score (MOS), a subjective video quality. Our goal is to estimate and predict this subjective metric in a holistic manner. Thus, we have analyzed and measured different varia…
An efficient hardware implementation of MQ decoder of the JPEG2000
2014
Abstract JPEG2000 is an international standard for still images intended to overcome the shortcomings of the existing JPEG standard. Compared to JPEG image compression techniques, JPEG2000 standard has not only better not only has better compression ratios, but it also offers some exciting features. As it’s hard to meet the real-time requirement of image compression systems by software, it is necessary to implement compression system by hardware. The MQ decoder of the JPEG2000 standard is an important bottleneck for real-time applications. In order to meet the real-time requirement we propose in this paper a novel architecture for a MQ decoder with high throughput which is comparable to tha…
Enabling early sleeping and early data transmission in wake-up radio-enabled IoT networks
2019
Abstract Wireless sensor networks (WSNs) are one of the key enabling technologies for the Internet of things (IoT). In such networks, wake-up radio (WuR) is gaining its popularity thanks to its on-demand transmission feature and overwhelming energy consumption superiority. Despite this advantage, overhearing still occurs when a wake-up receiver decodes the address of a wake-up call (WuC) which is not intended to it, causing a certain amount of extra energy waste in the network. Moreover, long latency may occur due to WuC address decoding since WuCs are transmitted at a very low data rate. In this paper, we propose two schemes, i.e., early sleeping (ES) and early data transmission (EDT), to …
A Predictive Approach for the Efficient Distribution of Agent-Based Systems on a Hybrid-Cloud
2018
International audience; Hybrid clouds are increasingly used to outsource non-critical applications to public clouds. However, the main challenge within such environments, is to ensure a cost-efficient distribution of the systems between the resources that are on/off premises. For Multi Agent Systems (MAS), this challenge is deepened due to irregular workload progress and intensive communication between the agents, which may result in high computing and data transfer costs. Thus, in this paper we propose a generic framework for adaptive cost-efficient deployment of MAS with a special focus on hybrid clouds. The framework is based mainly on the use of a performance evaluation process that con…
Support vector machines in engineering: an overview
2014
This paper provides an overview of the support vector machine SVM methodology and its applicability to real-world engineering problems. Specifically, the aim of this study is to review the current state of the SVM technique, and to show some of its latest successful results in real-world problems present in different engineering fields. The paper starts by reviewing the main basic concepts of SVMs and kernel methods. Kernel theory, SVMs, support vector regression SVR, and SVM in signal processing and hybridization of SVMs with meta-heuristics are fully described in the first part of this paper. The adoption of SVMs in engineering is nowadays a fact. As we illustrate in this paper, SVMs can …
SVM approximation for real-time image segmentation by using an improved hyperrectangles-based method
2003
A real-time implementation of an approximation of the support vector machine (SVM) decision rule is proposed. This method is based on an improvement of a supervised classification method using hyperrectangles, which is useful for real-time image segmentation. The final decision combines the accuracy of the SVM learning algorithm and the speed of a hyperrectangles-based method. We review the principles of the classification methods and we evaluate the hardware implementation cost of each method. We present the combination algorithm, which consists of rejecting ambiguities in the learning set using SVM decision, before using the learning step of the hyperrectangles-based method. We present re…
Fuzzy Clustering of Histopathological Images Using Deep Learning Embeddings
2021
Metric learning is a machine learning approach that aims to learn a new distance metric by increas- ing (reducing) the similarity of examples belonging to the same (different) classes. The output of these approaches are embeddings, where the input data are mapped to improve a crisp or fuzzy classifica- tion process. The deep metric learning approaches regard metric learning, implemented by using deep neural networks. Such models have the advantage to discover very representative nonlinear embed- dings. In this work, we propose a triplet network deep metric learning approach, based on ResNet50, to find a representative embedding for the unsupervised fuzzy classification of benign and maligna…