Search results for " artificial intelligence"

Feature Dimensionality Reduction for Mammographic Report Classification

2016

The amount and the variety of available medical data coming from multiple and heterogeneous sources can inhibit analysis, manual interpretation, and use of simple data management applications. In this paper a deep overview of the principal algorithms for dimensionality reduction is carried out; moreover, the most effective techniques are applied on a dataset composed of 4461 mammographic reports is presented. The most useful medical terms are converted and represented using a TF-IDF matrix, in order to enable data mining and retrieval tasks. A series of query have been performed on the raw matrix and on the same matrix after the dimensionality reduction obtained using the most useful techni…

Optimizing PolyACO Training with GPU-Based Parallelization

2016

A central part of Ant Colony Optimisation (ACO) is the function calculating the quality and cost of solutions, such as the distance of a potential ant route. This cost function is used to deposit an opportune amount of pheromones to achieve an apt convergence, and in an active ACO implementation a significant part of the runtime is spent in this part of the code. In some cases, the cost function accumulates up towards 94 % in its run time making it a performance bottle neck.

Automated Scenario Generation for Training of Humanitarian Responders in High-Risk Settings

2019

Measuring the agreement between brain connectivity networks.

2016

Investigating the level of similarity between two brain networks, resulting from measures of effective connectivity in the brain, can be of interest from many respects. In this study, we propose and test the idea to borrow measures of association used in machine learning to provide a measure of similarity between the structure of (un-weighted) brain connectivity networks. The measures here explored are the accuracy, Cohen's Kappa (K) and Area Under Curve (AUC). We implemented two simulation studies, reproducing two contexts of application that can be particularly interesting for practical applications, namely: i) in methodological studies, performed on surrogate data, aiming at comparing th…

Distributed Particle Metropolis-Hastings Schemes

2018

We introduce a Particle Metropolis-Hastings algorithm driven by several parallel particle filters. The communication with the central node requires the transmission of only a set of weighted samples, one per filter. Furthermore, the marginal version of the previous scheme, called Distributed Particle Marginal Metropolis-Hastings (DPMMH) method, is also presented. DPMMH can be used for making inference on both a dynamical and static variable of interest. The ergodicity is guaranteed, and numerical simulations show the advantages of the novel schemes.

Multi-agent Systems for Estimating Missing Information in Smart Cities

2019

International audience; Smart cities aim at improving the quality of life of citizens. To do this, numerous ad-hoc sensors need to be deployed in a smart city to monitor the environmental state. Even if nowadays sensors are becoming more and more cheap their installation and maintenance costs increase rapidly with their number. This paper makes an inventory of the dimensions required for designing an intelligent system to support smart city initiatives. Then we propose a multi-agent based solution that uses a limited number of sensors to estimate at runtime missing information in smart cities using a limited number of sensors.

SREP: An Energy Efficient Relay Protocol for Wireless Sensor Networks

2018

While wireless sensor networks continue to break new grounds in applications, favored by technological innovations, energy efficiency continues to stagnate. Duty cycling remains the most popular and effective technique used to improve energy efficiency and thus lifetime of the network. Nevertheless, duty cycling imposes temporary unavailability on the network leading to deterioration of quality of service. To take care of this rather contradicting reality, this paper proposes Sleep Relay Protocol (SREP). Network nodes are divided into sets according to their location and the sets sleep in relay within a duty cycle period. Two set formation algorithms are proposed at initiation of our propos…

Deep Learning-Based Real-Time Object Detection in Inland Navigation

2019

International audience; Semi-autonomous and fully-autonomous systems must have knowledge about the objects in their environment to ensure a safe navigation. Modern approaches implement deep learning techniques to train a neural network for object detection. This project will study the effectiveness of using several promising algorithms such as Faster R-CNN, SSD, and different versions of YOLO, to detect, classify, and track objects in near real-time fluvial domain. Since no dataset is available for this purpose in literature, we first started by annotating a dataset of 2488 images with almost 35 400 annotations for training the convolutional neural network architectures. We made this data s…

Open Set Audio Classification Using Autoencoders Trained on Few Data.

2020

Open-set recognition (OSR) is a challenging machine learning problem that appears when classifiers are faced with test instances from classes not seen during training. It can be summarized as the problem of correctly identifying instances from a known class (seen during training) while rejecting any unknown or unwanted samples (those belonging to unseen classes). Another problem arising in practical scenarios is few-shot learning (FSL), which appears when there is no availability of a large number of positive samples for training a recognition system. Taking these two limitations into account, a new dataset for OSR and FSL for audio data was recently released to promote research on solution…

Full-parallax 3D display from stereo-hybrid 3D camera system

2018

Abstract In this paper, we propose an innovative approach for the production of the microimages ready to display onto an integral-imaging monitor. Our main contribution is using a stereo-hybrid 3D camera system, which is used for picking up a 3D data pair and composing a denser point cloud. However, there is an intrinsic difficulty in the fact that hybrid sensors have dissimilarities and therefore should be equalized. Handled data facilitate to generating an integral image after projecting computationally the information through a virtual pinhole array. We illustrate this procedure with some imaging experiments that provide microimages with enhanced quality. After projection of such microim…