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Found 17 papers, 0 papers with code
Deep Learning for In-Orbit Cloud Segmentation and Classification in Hyperspectral Satellite Data
The performance of the latest 1D CNN (1D-Justo-LiuNet) and two recent 2D CNNs (nnU-net and 2D-Justo-UNet-Simple) for cloud segmentation and classification is assessed.
Prodromal Diagnosis of Lewy Body Diseases Based on the Assessment of Graphomotor and Handwriting Difficulties
To this date, studies focusing on the prodromal diagnosis of Lewy body diseases (LBDs) based on quantitative analysis of graphomotor and handwriting difficulties are missing.
Exploration of Various Fractional Order Derivatives in Parkinson's Disease Dysgraphia Analysis
Therefore, in this study, we follow up on our previous research, and we aim to explore the utilization of various approaches of fractional order derivative (FD) in the analysis of PD dysgraphia.
Preliminary experiments on thermal emissivity adjustment for face images
In this paper we summarize several applications based on thermal imaging.
Contribution of the Temperature of the Objects to the Problem of Thermal Imaging Focusing
When focusing an image, depth of field, aperture and distance from the camera to the object, must be taking into account, both, in visible and in infrared spectrum.
Face segmentation: A comparison between visible and thermal images
Face segmentation is a first step for face biometric systems.
A Naturalistic Database of Thermal Emotional Facial Expressions and Effects of Induced Emotions on Memory
This work defines a procedure for collecting naturally induced emotional facial expressions through the vision of movie excerpts with high emotional contents and reports experimental data ascertaining the effects of emotions on memory word recognition tasks.
Perceptual Features as Markers of Parkinson's Disease: The Issue of Clinical Interpretability
Up to 90% of patients with Parkinson's disease (PD) suffer from hypokinetic dysathria (HD) which is also manifested in the field of phonation.
Identification of Hypokinetic Dysarthria Using Acoustic Analysis of Poem Recitation
In this work, we analysed the power of conventional speech features quantifying imprecise articulation, dysprosody, speech dysfluency and speech quality deterioration extracted from a specialized poem recitation task to discriminate dysarthric and healthy speech.
Multi-focus thermal image fusion
To the best of our knowledge, this is the first work devoted to multi-focus thermal image fusion.
A multimodal approach for Parkinson disease analysis
Parkinson's disease (PD) is the second most frequent neurodegenerative disease with prevalence among general population reaching 0. 1-1 %, and an annual incidence between 1. 3-2. 0/10000 inhabitants.
A Preliminary Study on Aging Examining Online Handwriting
This paper contributes to this research line analyzing a selected set of online handwriting parameters provided by a healthy group of population aged from 18 to 70 years.
Online handwriting, signature and touch dynamics: tasks and potential applications in the field of security and health
Background: An advantageous property of behavioural signals , e. g. handwriting, in contrast to morphological ones, such as iris, fingerprint, hand geometry, etc., is the possibility to ask a user for a very rich amount of different tasks.
A comparative study of in-air trajectories at short and long distances in online handwriting
Methods In this paper, we will analyze a large set of databases (BIOSECURID, EMOTHAW, PaHaW, Oxygen-Therapy and SALT), which contain a total amount of 663 users and 17951 files.
Thermal hand image segmentation for biometric recognition
In this paper we present a method to identify people by means of thermal (TH) and visible (VIS) hand images acquired simultaneously with a TESTO 882-3 camera.
Towards Robust Voice Pathology Detection
Automatic objective non-invasive detection of pathological voice based on computerized analysis of acoustic signals can play an important role in early diagnosis, progression tracking and even effective treatment of pathological voices.
Voice Pathology Detection Using Deep Learning: a Preliminary Study
This paper describes a preliminary investigation of Voice Pathology Detection using Deep Neural Networks (DNN).
