Search results for " intelligence"
showing 10 items of 6677 documents
Community detection-based deep neural network architectures: A fully automated framework based on Likert-scale data
2020
[EN] Deep neural networks (DNNs) have emerged as a state-of-the-art tool in very different research fields due to its adaptive power to the decision space since they do not presuppose any linear relationship between data. Some of the main disadvantages of these trending models are that the choice of the network underlying architecture profoundly influences the performance of the model and that the architecture design requires prior knowledge of the field of study. The use of questionnaires is hugely extended in social/behavioral sciences. The main contribution of this work is to automate the process of a DNN architecture design by using an agglomerative hierarchical algorithm that mimics th…
Development of a Protocol for CCD Calibration: Application to a Multispectral Imaging System
2005
In this paper we describe in detail a method for calibrating a CCD-based camera. The calibration aims to remove both temporal and systematic noises introduced by the sensor, electronics, and optics after which we can correct the non-linearity of its response. For the non-linearity correction we use a simple and powerful approach consisting on a complementary approach between a polynomial fitting and an LUT based algorithm. The proposed methodology is accurate in the sense that it takes into account individual characteristics of each pixel. In each pixel, systematic noises are measured through acquiring offset images, thermal images, and FlatField images. A rigorous protocol for acquiring th…
High Dynamic Range Spectral Imaging Pipeline For Multispectral Filter Array Cameras
2017
Spectral filter arrays imaging exhibits a strong similarity with color filter arrays. This permits us to embed this technology in practical vision systems with little adaptation of the existing solutions. In this communication, we define an imaging pipeline that permits high dynamic range (HDR)-spectral imaging, which is extended from color filter arrays. We propose an implementation of this pipeline on a prototype sensor and evaluate the quality of our implementation results on real data with objective metrics and visual examples. We demonstrate that we reduce noise, and, in particular we solve the problem of noise generated by the lack of energy balance. Data are provided to the community…
Towards EEG-Based Haptic Interaction within Virtual Environments
2019
International audience; Current virtual environments (VE) enable perceiving haptic stimuli to facilitate 3D user interaction, but lack brain-interfacial contents. Using electroencephalography (EEG), we undertook a feasibility study on exploring event-related potential (ERP) patterns of the user's brain responses during haptic interaction within a VE. The interaction was flying a virtual drone along a curved transmission line to detect defects under the stimuli (e.g., force increase and/or vibrotactile cues). We found that there were variations in the peak amplitudes and latencies (as ERP patterns) of the responses at about 200 ms post the onset of the stimuli. The largest negative peak occu…
The anesthesiologist and end-of-life care
2012
Purpose of review Anesthesiologists may face problematic situations when patients are close to death, in which clinical problems, decision-making processes, and ethical issues are often interconnected and dependent on each of them. The aim of this review is to assess the recent literature regarding the anesthesiological role for advanced cancer patients. Recent findings Palliative sedation in the dying patients, end-of-life problems in the ICU, and pain control in advanced cancer patients have been the subject of recent research. All these issues have shown that anesthesiologist would be expert in the field of pain and symptom control at the end of life. End-of-life care problems are common…
Efficient 3D Deep Learning for Myocardial Diseases Segmentation
2021
Automated myocardial segmentation from late gadolinium enhancement magnetic resonance images (LGE-MRI) is a critical step in the diagnosis of cardiac pathologies such as ischemia and myocardial infarction. This paper proposes a deep learning framework for improved myocardial diseases segmentation. In the first step, we build an encoder-decoder segmentation network that generates myocardium and cavity segmentations from the whole volume, followed by a 3D U-Net based on Shape prior to identifying myocardial infarction and myocardium ventricular obstruction (MVO) segmentations from the encoder-decoder prediction. The proposed network achieves good segmentation performance, as computed by avera…
Deep Learning Predicts Molecular Subtype of Muscle-invasive Bladder Cancer from Conventional Histopathological Slides.
2020
Abstract Background Muscle-invasive bladder cancer (MIBC) is the second most common genitourinary malignancy, and is associated with high morbidity and mortality. Recently, molecular subtypes of MIBC have been identified, which have important clinical implications. Objective In the current study, we tried to predict the molecular subtype of MIBC samples from conventional histomorphology alone using deep learning. Design, setting, and participants Two cohorts of patients with MIBC were used: (1) The Cancer Genome Atlas Urothelial Bladder Carcinoma dataset including 407 patients and (2) our own cohort including 16 patients with treatment-naive, primary resected MIBC. This resulted in a total …
<title>Eye movements during silent and oral reading with stabilized versus free head movement and different eye-trackers</title>
2008
Eye movement research of reading has been done on a battery of eye-tracking setups during last decades. We compared reading data of the same group of six students, their eyes were tracked by a video-based helmet-mounted system with the data sampling frequency of 50 Hz and a setup with a chin-rest at 240 Hz. We found that not only the number of fixations may decrease after reading practice, but so does also the mean duration of fixations. In spite of the short duration of saccades, their distributions and changes in them are similarly reported in the two experimental conditions. Lack of significant correlation in the HED data testifies to the result variability due to measurement technique. …
Visual acuity and contrast sensitivity screening with a new iPad application
2016
We present a new iPad application (app) for a fast assessment of Visual Acuity (VA) and Contrast Sensitivity (CS) whose reliability and agreement was evaluated versus a commercial screening device (Optec 6500). The measurement of VA was programmed in the app in accordance with the Amblyopia Treatment Study protocol. The CS was measured with sinusoidal gratings of four different spatial frequencies: 3, 6, 12 and 18 cpd at the same contrast values of the Functional Acuity Contrast Test (FACT) included in the Optec 6500. Forty-five healthy subjects with monocular corrected visual acuities better than 0.2 logMAR participated in the agreement study. Bland-Altman analyses were performed to assess…
Working Memory, Jumping to Conclusions and Emotion Recognition: a Possible Link in First Episode Psychosis (Fep)
2015
Introduction A large body of literature has demonstrated that people affected by psychotic disorders show deficits in working memory, in Emotion Recognition (ER) and in data-gathering to reach a decision (Jumping To Conclusions – JTC). Aims To investigate a possible correlation between working memory, JTC and ER in FEP. Methods 41 patients and 89 healthy controls completed assessments of working memory using WAIS shortened version, JTC using the 60:40 Beads Task and ER using Degraded Facial Affect Recognition Task. Results According to the literature, cases had poorer performance in working memory tasks (Digit Span: μ7,72 [ds=2,98] vs μ10,14 [ds=3,10], U=865,00, p=0,00; Digit Symbol: μ5,36 …