Search results for "Intelligence"
showing 10 items of 6959 documents
Optical See-Through Head-Mounted Displays With Short Focal Distance: Conditions for Mitigating Parallax-Related Registration Error
2020
Optical see-through (OST) augmented reality head-mounted displays are quickly emerging as a key asset in several application fields but their ability to profitably assist high precision activities in the peripersonal space is still sub-optimal due to the calibration procedure required to properly model the user's viewpoint through the see-through display. In this work, we demonstrate the beneficial impact, on the parallax-related AR misregistration, of the use of optical see-through displays whose optical engines collimate the computer-generated image at a depth close to the fixation point of the user in the peripersonal space. To estimate the projection parameters of the OST display for a …
Fast Implementation of Double-coupled Nonnegative Canonical Polyadic Decomposition
2019
Real-world data exhibiting high order/dimensionality and various couplings are linked to each other since they share some common characteristics. Coupled tensor decomposition has become a popular technique for group analysis in recent years, especially for simultaneous analysis of multi-block tensor data with common information. To address the multiblock tensor data, we propose a fast double-coupled nonnegative Canonical Polyadic Decomposition (FDC-NCPD) algorithm in this study, based on the linked CP tensor decomposition (LCPTD) model and fast Hierarchical Alternating Least Squares (Fast-HALS) algorithm. The proposed FDCNCPD algorithm enables simultaneous extraction of common components, i…
A Microcalcification Detection System in Mammograms based on ANN Clustering
2018
Breast cancer is one of the leading causes to women mortality in the world. Clustered microcalcifications (MCs) in mammograms can be an important early sign of breast cancer, the detection is important to prevent and treat the disease. In this work, we present a novel method for the detection of MCs in mammograms which consists of regions of Interest (ROIs) segmentation, based on a spatial filter that allows the detection of small and large microcalcifications, clustering and classification of MCs by Artificial Neural Network. The system has been tested on a public dataset of digital images and compared with previous approaches. The results demonstrate that the proposed approach could achie…
Mesh Visual Quality Assessment Metrics: A Comparison Study
2017
3D graphics technologies have known a developed progress in the last years, and several processing operations can be applied on 3D meshes such as watermarking, compression, simplification and so forth. Mesh visual quality assessment becomes an important issue to evaluate the visual appearance of the 3D shape after specific modifications. Several metrics have been proposed in this context, from the classical distance-based metrics to the perceptual-based metrics which include perceptual information about the human visual system. In this paper, we propose to study the performance of several mesh visual quality metrics. First, the comparison is conducted regardless the distortion types neither…
IWILDS'20
2020
Web search is one of the most ubiquitous online activities and often used for learning purposes, i.e., to extend one's knowledge or skills about certain topics or procedures. The importance of learning as an outcome of Web search has been recognized in research at the intersection of information retrieval, human-computer interaction, psychology, and educational sciences. Search as Learning (SAL) research examines relationships between querying, navigation, and reading behavior during Web search and the resulting learning outcomes, and how they can be measured, predicted, and supported. IWILDS aims to provide a platform to the interdisciplinary SAL community, with the objective to bring toge…
Automation Inner Speech as an Anthropomorphic Feature Affecting Human Trust: Current Issues and Future Directions
2021
This paper aims to discuss the possible role of inner speech in influencing trust in human–automation interaction. Inner speech is an everyday covert inner monolog or dialog with oneself, which is essential for human psychological life and functioning as it is linked to self-regulation and self-awareness. Recently, in the field of machine consciousness, computational models using different forms of robot speech have been developed that make it possible to implement inner speech in robots. As is discussed, robot inner speech could be a new feature affecting human trust by increasing robot transparency and anthropomorphism.
Evaluation of the registration of temporal series of contrast-enhanced perfusion magnetic resonance 3D images of the liver.
2011
The registration of 2D and 3D images is one of the key tasks in medical image processing and analysis. Accurate registration is a crucial preprocessing step for many tasks; consequently, the evaluation of its accuracy becomes necessary. Unfortunately, this is a difficult task, especially when no golden pattern (true result) is available and when the signal values may have changed between successive images to be registered. This is the case this paper deals with: we have a series of 3D images, magnetic resonance images (MRI) of the liver and adjacent areas that have to be registered. They have been taken while a contrast is diffused through the liver tissue, so intensity of each observed poi…
An Architecture for Telenoid Robot as Empathic Conversational Android Companion for Elderly People
2015
In Human-Humanoid Interaction (HHI), empathy is the crucial key in order to overcome the current limitations of social robots. In facts, a principal defining characteristic of human social behaviour is empathy. The present paper presents a robotic architecture for an android robot as a basis for natural empathic human-android interaction. We start from the hypothesis that the robots, in order to become personal companions need to know how to empathic interact with human beings. To validate our research, we have used the proposed system with the minimalistic humanoid robot Telenoid. We have conducted human-robot interactions test with elderly people with no prior interaction experience with …
Color illusions also deceive CNNs for low-level vision tasks: Analysis and implications.
2019
The study of visual illusions has proven to be a very useful approach in vision science. In this work we start by showing that, while convolutional neural networks (CNNs) trained for low-level visual tasks in natural images may be deceived by brightness and color illusions, some network illusions can be inconsistent with the perception of humans. Next, we analyze where these similarities and differences may come from. On one hand, the proposed linear eigenanalysis explains the overall similarities: in simple CNNs trained for tasks like denoising or deblurring, the linear version of the network has center-surround receptive fields, and global transfer functions are very similar to the human …
Individualizing deep dynamic models for psychological resilience data
2020
ABSTRACTDeep learning approaches can uncover complex patterns in data. In particular, variational autoencoders (VAEs) achieve this by a non-linear mapping of data into a low-dimensional latent space. Motivated by an application to psychological resilience in the Mainz Resilience Project (MARP), which features intermittent longitudinal measurements of stressors and mental health, we propose an approach for individualized, dynamic modeling in this latent space. Specifically, we utilize ordinary differential equations (ODEs) and develop a novel technique for obtaining person-specific ODE parameters even in settings with a rather small number of individuals and observations, incomplete data, an…