Search results for "Computer Vision"
showing 10 items of 2353 documents
Force/Torque-Sensorless Joint Stiffness Estimation in Articulated Soft Robots
2022
Currently, the access to the knowledge of stiffness values is typically constrained to a-priori identified models or datasheet information, which either do not usually take into ac- count the full range of possible stiffness values or need extensive experiments. This work tackles the challenge of stiffness estimation in articulated soft manipulators, and it proposes an innovative solution adding value to the previous research by removing the necessity for force/torque sensors and generalizing to multi-degree- of-freedom robots. Built upon the theory of unknown input-state observers and recursive least-square algorithms, the solution is independent of the actuator model parameters and its in…
Robust and Decoupled Position and Stiffness Control for Electrically-Driven Articulated Soft Robots
2022
The control of articulated soft robots, i.e. robots with flexible joints and rigid links, presents a challenge due to their in- trinsic elastic elements and nonlinear force-deflection dependency. This letter first proposes a discrete-time delayed unknown input- state observer based on a nominal robot model that reconstructs the total torque disturbance vector, resulting from the imperfect knowledge of the elastic torque characteristic, external torques, and other model uncertainties. Then, it introduces a robust controller, that actively compensates for the estimated uncertainty and allows bounded stability for the tracking of independent link position and joint stiffness reference signals.…
Single-channel speech enhancement using implicit Wiener filter for high-quality speech communication
2022
AbstractSpeech enables easy human-to-human communication as well as human-to-machine interaction. However, the quality of speech degrades due to background noise in the environment, such as drone noise embedded in speech during search and rescue operations. Similarly, helicopter noise, airplane noise, and station noise reduce the quality of speech. Speech enhancement algorithms reduce background noise, resulting in a crystal clear and noise-free conversation. For many applications, it is also necessary to process these noisy speech signals at the edge node level. Thus, we propose implicit Wiener filter-based algorithm for speech enhancement using edge computing system. In the proposed algor…
Non-intrusive speech quality assessment using context-aware neural networks
2022
AbstractTo meet the human perceived quality of experience (QoE) while communicating over various Voice over Internet protocol (VoIP) applications, for example Google Meet, Microsoft Skype, Apple FaceTime, etc. a precise speech quality assessment metric is needed. The metric should be able to detect and segregate different types of noise degradations present in the surroundings before measuring and monitoring the quality of speech in real-time. Our research is motivated by the lack of clear evidence presenting speech quality metric that can firstly distinguish different types of noise degradations before providing speech quality prediction decision. To that end, this paper presents a novel n…
From medical data to simple virtual mock-up of scapulo-humeral joint
2008
The surgical operations of shoulder joint are guided by various principles: osteosynthesis in the case of fracture, osteotomy in order to correct a deformation or to modify the functioning of the joint, or implementation of articular prosthesis. At the end of the twentieth century, many innovations in the domains of biomechanics and orthopedic surgery have been performed. Nevertheless, theoretical and practical problems may appear during the operation (visual field of surgeon is very limited, quality and shape of the bone is variable depending on the patient). Biomechanical criteria of success are defined for each intervention. For example, the installation with success of prosthetic implan…
A Hybrid Neural Network Architecture for Dynamic Scene Understanding
1997
A hyprdid (neural and symbolic) architecture allowing for a deep understanding of moving scenes is described. The architecture is based on a working and effective integration among three levels of representation of data coming out from external sensors.
Estimation of Evapotranspiration by Hargreaves Formula and Remotely Sensed Data in Semi-arid Mediterranean Areas
1997
Abstract A methodology is proposed for estimating evapotranspiration by Hargreaves formula and image analysis of remotely sensed data. At first, for a large sicilian basin (Belice basin), theactualevapotranspiration values are estimated by the energy balance equation, spectral data of two Landsat TM images and ground agrometereological measurements. Then theseactualevapotranspiration estimates and thereferenceevapotranspiration values obtained by a slightly modified Hargreaves formula, which incorporates the outgoing short-wave radiation and an albedo coefficient equal to 0·23, are used for calculating suitable crop coefficients. Finally, the minimum area of each land-use map unit, obtained…
Assessing actual evapotranspiration via surface energy balance aiming to optimize water and energy consumption in large scale pressurized irrigation …
2017
Satellite imagery provides a dependable basis for computational models that aimed to determine actual evapotranspiration (ET) by surface energy balance. Satellite-based models enables quantifying ET over large areas for a wide range of applications, such as monitoring water distribution, managing irrigation and assessing irrigation systems’ performance. With the aim to evaluate the energy and water consumption of a large scale on-turn pressurized irrigation system in the district of Aguas Nuevas, Albacete, Spain, the satellite-based image-processing model SEBAL was used for calculating actual ET. The model has been applied to quantify instantaneous, daily, and seasonal actual ET over high- …
Hypergraph imaging: an overview
2002
Hypergraph theory as originally developed by Berge (Hypergraphe, Dunod, Paris, 1987) is a theory of finite combinatorial sets, modeling lot of problems of operational research and combinatorial optimization. This framework turns out to be very interesting for many other applications, in particular for computer vision. In this paper, we are going to survey the relationship between combinatorial sets and image processing. More precisely, we propose an overview of different applications from image hypergraph models to image analysis. It mainly focuses on the combinatorial representation of an image and shows the effectiveness of this approach to low level image processing; in particular to seg…
Hyperspectral Texture Metrology Based on Joint Probability of Spectral and Spatial Distribution
2021
International audience; Texture characterization from the metrological point of view is addressed in order to establish a physically relevant and directly interpretable feature. In this regard, a generic formulation is proposed to simultaneously capture the spectral and spatial complexity in hyperspectral images. The feature, named relative spectral difference occurrence matrix (RSDOM) is thus constructed in a multireference, multidirectional, and multiscale context. As validation, its performance is assessed in three versatile tasks. In texture classification on HyTexiLa, content-based image retrieval (CBIR) on ICONES-HSI, and land cover classification on Salinas, RSDOM registers 98.5% acc…