Search results for "artificial intelligence"

Expliquer le comportement de robots distants à des utilisateurs humains : une approche orientée-agent

2020

With the widespread use of Artificial Intelligence (AI) systems, understanding the behavior of intelligent agents and robots is crucial to guarantee smooth human-agent collaboration since it is not straightforward for humans to understand the agent’s state of mind. Recent studies in the goal-driven Explainable AI (XAI) domain have confirmed that explaining the agent’s behavior to humans fosters the latter’s understandability of the agent and increases its acceptability. However, providing overwhelming or unnecessary information may also confuse human users and cause misunderstandings. For these reasons, the parsimony of explanations has been outlined as one of the key features facilitating …

Improving IoT Communications Based on Smart Routing Algorithms

2018

International audience; Due to the recorded success by Internet of Things (IoT) technology, more and more domains use it as a communications and exchange network such as e-health, smart cities, vehicles, etc. IoT don’t stop integrating an important number of components and objects that are characterized by their complexity and heterogeneity. Such constraints make the existing routings protocols unsuitable for IoT communications. To accomplish all the expected tasks and satisfy the user services, it is important to guarantee a quality of communication that answers to the requirements of the various applications in terms of data and processing (availability, integrity, efficiency, etc.). The …

Temporal-range estimation of multiple objects: evidence for an early bottleneck.

2011

When making parallel time-to-contact (TTC) estimates of two approaching objects, the two respective TTC estimates interfere with one another in an asymmetric fashion. The TTC of the later-arriving object is systematically overestimated, while the estimated TTC for the first-arriving object is as accurate as in a condition presenting only a single object. This asymmetric interference points to a processing bottleneck that could be due to early (e.g., during the estimation of the TTC from the optic flow) or late (e.g., during the timing of the response or the motor execution) constraints in the TTC estimation process. We used a Sperling-like prediction-motion task to differentiate between the…

Local Distance and Dempster-Dhafer for Multi-Focus Image Fusion

2022

This work proposes a new method of fusion image using Dempster-Shafer theory and local variability (DST-LV). This method takes into account the behaviour of each pixel with its neighbours. It consists in calculating the quadratic distance between the value of the pixel I (x, y) of each point and the value of all the neighbouring pixels. Local variability is used to determine the mass function defined in DempsterShafer theory. The two classes of Dempster-Shafer theory studied are : the fuzzy part and the focused part. The results of the proposed method are significantly better when comparing them to results of other methods.

Accelerometry - Simple, but challenging

2017

Depth-of-Field of the Accommodating Eye

2014

Our eyes project information from a three-dimensional world to a basically two-dimensional surface, corresponding to the photoreceptor plane in the retina. In theory, only one plane or surface of world can be in focus at one time. However, the eye exhibits a certain tolerance to out-of-focus images, a feature that is known as depth-of-focus (DOF). The corresponding distance range in which the objects are seen “clearly” is known as depth-of-field (DOFi). Although DOF and DOFi refer to an interval of distances or a dioptric range in the image and object space, respectively, both parameters define a similar concept and are usually interchangeable. This article will mainly refer to DOFi because…

Geostatistical computing of acoustic maps in the presence of barriers

2009

Acoustic maps are the main diagnostic tools used by authorities for addressing the growing problem of urban acoustic contamination. Geostatistics models phenomena with spatial variation, but restricted to homogeneous prediction regions. The presence of barriers such as buildings introduces discontinuities in prediction areas. In this paper we investigate how to incorporate information of a geographical nature into the process of geostatistical prediction. In addition, we study the use of a Cost-Based distance to quantify the correlation between locations.

Discriminating and simulating actions with the associative self-organising map

2015

We propose a system able to represent others’ actions as well as to internally simulate their likely continuation from a partial observation. The approach presented here is the first step towards a more ambitious goal of endowing an artificial agent with the ability to recognise and predict others’ intentions. Our approach is based on the associative self-organising map, a variant of the self-organising map capable of learning to associate its activity with different inputs over time, where inputs are processed observations of others’ actions. We have evaluated our system in two different experimental scenarios obtaining promising results: the system demonstrated an ability to learn discrim…

A Robust Multi Stage Technique for Image Binarization of Degraded Historical Documents

2017

International audience; Document image binarization is a central problem in many document analysis systems. Indeed, it represents one of the basic challenges, especially in case of historical documents analysis. In this paper, we propose a novel robust multi stage framework that combines different existing document image thresholding methods for the purpose of getting a better binarization result. CLAHE technique is introduced to significantly enhance contrast in some poor images. The proposed method then uses a hybrid algorithm to partition image into foreground and background. A special procedure is finally applied in order to remove small noise and correct characters morphology. Experime…

Construction of quality indicators based on pre-established goals: application to a colombian public university

2020

This study creates indicators of adequacy and excellence based on multiple-criteria decision-making (MCDM) methods and fuzzy logic. The calculation of indicators presents two main difficulties: The nature of the data (numerical, interval, and linguistic values are mixed) and the objective of each criterion (which does not have to reach either the maximum or the minimum). A method is proposed, based on similarity measures with predetermined ideals, that is capable of overcoming these difficulties to provide easy-to-interpret information about the quality of the alternatives. To illustrate the usefulness of this proposed method, it has been applied to data collected from students across nine …