Search results for "artificial intelligence"
showing 10 items of 6122 documents
Autonomous Mooring towards Autonomous Maritime Navigation and Offshore Operations
2020
Bollard is a vital component of mooring system. It is the anchor point for mooring ropes to be fixed in order to secure the vessel or ship. An algorithm that translates the segmented mask of bollard output from masked R-CNN along with bounding box and associated class probability to its corresponding edge coordinate and finally to the single reference point for efficient detection and classification of bollard towards autonomous mooring is presented. At first stage, Mask R-CNN framework is trained with custom built bollard. The model obtained from the training is inferred with real data resulting in instance segment of bollard. The segmented mask obtained contains relatively large amount of…
Color difference threshold of chromostereopsis induced by flat display emission
2015
The study of chromostereopsis has gained attention in the backdrop of the use of computer displays in daily life. In this context, we analyze the illusory depth sense using planar color images presented on a computer screen. We determine the color difference threshold required to induce an illusory sense of depth psychometrically using a constant stimuli paradigm. Isoluminant stimuli are presented on a computer screen, which stimuli are aligned along the blue–red line in the computer display CIE xyY color space. Stereo disparity is generated by increasing the color difference between the central and surrounding areas of the stimuli with both areas consisting of random dots on a black backgr…
Multiframe image restoration in the presence of noisy blur kernel
2009
We wish to recover an original image u from several blurry-noisy versions f k , called frames. We assume a more severe degradation model, in which the image u has been blurred by a noisy (stochastic) point spread function. We consider the problem of restoring the degraded image in a variational framework. Since the recovery of u from one single frame f is a highly ill-posed problem, we formulate two minimization problems based on the multiframe approach proposed for image super-resolution by Marquina-Osher [13]. Several experimental results for image restoration are shown, illustrating that the proposed models give visually satisfactory results.
Variational multiframe restoration of images degraded by noisy (stochastic) blur kernels
2013
This article introduces and explores a class of degradation models in which an image is blurred by a noisy (stochastic) point spread function (PSF). The aim is to restore a sharper and cleaner image from the degraded one. Due to the highly ill-posed nature of the problem, we propose to recover the image given a sequence of several observed degraded images or multiframes. Thus we adopt the idea of the multiframe approach introduced for image super-resolution, which reduces distortions appearing in the degraded images. Moreover, we formulate variational minimization problems with the robust (local or nonlocal) L^1 edge-preserving regularizing energy functionals, unlike prior works dealing wit…
Combining Real-Time Segmentation and Classification of Rehabilitation Exercises with LSTM Networks and Pointwise Boosting
2020
Autonomous biofeedback tools in support of rehabilitation patients are commonly built as multi-tier pipelines, where a segmentation algorithm is first responsible for isolating motion primitives, and then classification can be performed on each primitive. In this paper, we present a novel segmentation technique that integrates on-the-fly qualitative classification of physical movements in the process. We adopt Long Short-Term Memory (LSTM) networks to model the temporal patterns of a streaming multivariate time series, obtained by sampling acceleration and angular velocity of the limb in motion, and then we aggregate the pointwise predictions of each isolated movement using different boosti…
Overview of the Evalita 2014 SENTIment POLarity Classification Task
2014
International audience; English. The SENTIment POLarity Classification Task (SENTIPOLC), a new shared task in the Evalita evaluation campaign , focused on sentiment classification at the message level on Italian tweets. It included three subtasks: subjectivity classification, polarity classification, and irony detection. SENTIPOLC was the most participated Evalita task with a total of 35 submitted runs from 11 different teams. We present the datasets and the evaluation methodology, and discuss results and participating systems. Italiano. Descriviamo modalit a e risultati della campagna di valutazione di sistemi di sentiment analysis (SENTIment POLarity Classification Task), proposta per la …
Drawback of ICA Procedure on EEG: Polarity Indeterminacy at Local Optimization
2008
Independent component analysis (ICA) has been extensively applied to reject artifacts in electroencephalography (EEG) signal processing. The first step is to extract the independent component activations from the electrode records, and then project the desired components back to the electrodes. After the composition of the projected component is analyzed in details under ICA procedure, this study shows that since ICA may extract some source components at the local optimization in high-dimensional EEG signal space, the artificial polarity indeterminacy may happen on the projected component at some electrodes. By numerical simulations, this issue also exhibits that this polarity ambiguity occ…
The Olt River pollution monitoring, using spatial analysis, analityc hierarchy process and technique for order preference by similarity methods
2016
Abstract Environmental pollution is one of the most serious problems of the contemporary world. Chemical industry is one of the major sources of environmental pollutants. Human knowledge and experience is currently focused on the use of assessment methods and techniques before and during the onset of such activities. For instance, it is common to consider the integration of multiple constraining factors and also, taking into account their high complexity and the application of one of the various techniques of Multi-Criteria Decision Making. The purpose of this study is to determine the location of the least and most polluted areas from several sampling points on the Olt River, in Romania. I…
Ionic tactile sensors as promising biomaterials for artificial skin: Review of latest advances and future perspectives
2021
Abstract Ionic tactile sensors (ITS) are an emerging subfield of wearable electronics, capable of mimicking the human skin, including not only the typical anisotropic structure, mechanical behaviour, and tactile functions but even the mechanosensitive ionic channels that are crucial for the human sense of touch. With the rapid development of intelligent technology, such bioinspired materials constitute the core foundation of intelligent systems and are a candidate to be the next generation e-skins, offering a more accurate and evolved biointerface. In the latest years, a wealth of novel ultra-stretchable ITS was proposed, progressively refining the choice of soft materials, including ion ge…
Minimal Absent Words in Rooted and Unrooted Trees
2019
We extend the theory of minimal absent words to (rooted and unrooted) trees, having edges labeled by letters from an alphabet \(\varSigma \) of cardinality \(\sigma \). We show that the set \(\text {MAW}(T)\) of minimal absent words of a rooted (resp. unrooted) tree T with n nodes has cardinality \(O(n\sigma )\) (resp. \(O(n^{2}\sigma )\)), and we show that these bounds are realized. Then, we exhibit algorithms to compute all minimal absent words in a rooted (resp. unrooted) tree in output-sensitive time \(O(n+|\text {MAW}(T)|)\) (resp. \(O(n^{2}+|\text {MAW}(T)|)\) assuming an integer alphabet of size polynomial in n.