Search results for "artificial intelligence"
showing 10 items of 6122 documents
Exploiting Data Analytics and Deep Learning Systems to Support Pavement Maintenance Decisions
2021
Road networks are critical infrastructures within any region and it is imperative to maintain their conditions for safe and effective movement of goods and services. Road Management, therefore, plays a key role to ensure consistent efficient operation. However, significant resources are required to perform necessary maintenance activities to achieve and maintain high levels of service. Pavement maintenance can typically be very expensive and decisions are needed concerning planning and prioritizing interventions. Data are key towards enabling adequate maintenance planning but in many instances, there is limited available information especially in small or under-resourced urban road authorit…
A Curvature Based Method for Blind Mesh Visual Quality Assessment Using a General Regression Neural Network
2016
International audience; No-reference quality assessment is a challenging issue due to the non-existence of any information related to the reference and the unknown distortion type. The main goal is to design a computational method to objectively predict the human perceived quality of a distorted mesh and deal with the practical situation when the reference is not available. In this work, we design a no reference method that relies on the general regression neural network (GRNN). Our network is trained using the mean curvature which is an important perceptual feature representing the visual aspect of a 3D mesh. Relatively to the human subjective scores, the trained network successfully asses…
Robust Selective Stereo SLAM without Loop Closure and Bundle Adjustment
2013
This paper presents a novel stereo SLAM framework, where a robust loop chain matching scheme for tracking keypoints is combined with an effective frame selection strategy. The proposed approach, referred to as selective SLAM (SSLAM), relies on the observation that the error in the pose estimation propagates from the uncertainty of the three-dimensional points. This is higher for distant points, corresponding to matches with low temporal flow disparity in the images. Comparative results based on the reference KITTI evaluation framework show that SSLAM is effective and can be implemented efficiently, as it does not require any loop closure or bundle adjustment.
Claves vertebradoras del modelo de justicia en el siglo XXI
2021
The 21st Century presents a dynamic, international, digital, changing, agile, and fast Society, that demands an adequated Justice System. The Incorporation due to Globalization of Keys such a Supranationality, Internationalization, Efficiency, Feminization, Technology, Algorithms and Artificial Intelligence, are involved in the changes of the new look of Justice.
Multi-agent control architecture for RFID cyberphysical robotic systems initial validation of tagged objects detection and identification using Playe…
2016
International audience; The objective of this paper is to describe and validate a multi-agent architecture proposed to control RFID Cyber-Physical Robotic Systems. This environment may contain human operators, robots (mobiles, manipulators, mobile manipulators, etc.), places (workrooms, walls, etc.) and other objects (tables, chairs, etc.). The proposed control architecture is composed of two types of agents dispatched on two levels. We find at the Organization level a Supervisory agent to allow operators to configure, manage and interact with the overall control system. At the Control level, we distinguish the Robots agents, to each robot (mobiles, manipulators or mobile manipulators) is a…
Two-step cross correlation-based algorithm for motion estimation applied to fertilizer granules' motion during centrifugal spreading
2011
Imaging systems are progressing in both accuracy and ro- bustness, and their use in precision agriculture is increasing accordingly. One application of imaging systems is to understand and control the cen- trifugal fertilizing spreading process. Predicting the spreading pattern on the ground relies on an estimation of the trajectories and velocities of ejected granules. The algorithms proposed to date have shown low ac- curacy, with an error rate of a few pixels. But a more accurate estimation of the motion of the granules can be achieved. Our new two-step cross- correlation-based algorithm is based on the technique used in particle image velocimetry (PIV), which has yielded highly accurate…
Use of electronic nose to determine defect percentage in oils. Comparison with sensory panel results
2010
Abstract An electronic nose based on an array of 6 metal oxide semiconductor sensors was used, jointly with linear discriminant analysis (LDA) and artificial neural network (ANN) method, to classify oils containing the five typical virgin olive oil (VOO) sensory defects (fusty, mouldy, muddy, rancid and winey). For this purpose, these defects, available as single standards of the International Olive Council, were added to refined sunflower oil. According to the LDA models and the ANN method, the defected samples were correctly classified. On the other hand, the electronic nose data was used to predict the defect percentage added to sunflower oil using multiple linear regression models. All …
Action simulation in the human brain: Twelve questions
2013
Although the idea of action simulation is nowadays popular in cognitive science, neuroscience and robotics, many aspects of the simulative processes remain unclear from empirical, computational, and neural perspectives. In the first part of the article, we provide a critical review and assessment of action simulation theories advanced so far in the wider literature of embodied and motor cognition. We focus our analysis on twelve key questions, and discuss them in the context of human and (occasionally) primate studies. In the second part of the article, we describe an integrative neuro-computational account of action simulation, which links the neural substrate (as revealed in neuroimaging …
A Performance Evaluation of Fusion Techniques for Spatio-Temporal Saliency Detection in Dynamic Scenes
2013
International audience; Visual saliency is an important research topic in computer vision applications, which helps to focus on regions of interest instead of processing the whole image. Detecting visual saliency in still images has been widely addressed in literature. However, visual saliency detection in videos is more complicated due to additional temporal information. A spatio-temporal saliency map is usually obtained by the fusion of a static saliency map and a dynamic saliency map. The way both maps are fused plays a critical role in the accuracy of the spatio-temporal saliency map. In this paper, we evaluate the performances of different fusion techniques on a large and diverse datas…
Humans and Their Technologies Play the Infinite Game
2019
Technology is increasingly about intuitive use and automation, as is evident to some degree in all the papers published in this issue. Technological--and one could say, even civilizational--progress is made possible by automating necessary but often tedious and tiresome processes. This then frees people's time and energy for a variety of recreational, inspirational, and/or developmental tasks. However, as the automation of society advances, the meaning of work changes and new existential and ethical questions emerge. nonPeerReviewed