Zobrazeno 1 - 10
of 16
pro vyhledávání: '"Thomas Martinet"'
Autor:
Vishal A. Gracian, Stéphane Galland, Alexandre Lombard, Thomas Martinet, Nicolas Gaud, Hui Zhao, Ansar-Ul-Haque Yasar
Publikováno v:
Autonomous Intelligent Systems, Vol 4, Iss 1, Pp 1-20 (2024)
Abstract The traffic in developing countries presents its own specificity, notably due to the heterogeneous traffic and a weak-lane discipline. This leads to differences in driver behavior between these countries and developed countries. Knowing that
Externí odkaz:
https://doaj.org/article/9f1ae7ece6514253b11dc66b5df7386a
Publikováno v:
PLoS ONE, Vol 19, Iss 6, p e0306218 (2024)
Sleep spindles are one of the prominent EEG oscillatory rhythms of non-rapid eye movement sleep. In the memory consolidation, these oscillations have an important role in the processes of long-term potentiation and synaptic plasticity. Moreover, the
Externí odkaz:
https://doaj.org/article/56203384df4a445fb18c300adb2fdc9f
Autor:
Natalie Thiemann, Svenja Rebecca Sonntag, Marie Kreikenbohm, Giulia Böhmerle, Jessica Stagge, Salvatore Grisanti, Thomas Martinetz, Yoko Miura
Publikováno v:
Diagnostics, Vol 14, Iss 4, p 431 (2024)
The purpose of this study was to investigate the possibility of implementing an artificial intelligence (AI) approach for the analysis of fluorescence lifetime imaging ophthalmoscopy (FLIO) data even with small data. FLIO data, including the fluoresc
Externí odkaz:
https://doaj.org/article/4a1e04a7d3d14fb79d862e816a6f3bdb
Autor:
Alexandra I. Korda, Christina Andreou, Mihai Avram, Heinz Handels, Thomas Martinetz, Stefan Borgwardt
Publikováno v:
Frontiers in Psychiatry, Vol 13 (2022)
Structural MRI studies in first-episode psychosis (FEP) and in clinical high risk (CHR) patients have consistently shown volumetric abnormalities in frontal, temporal, and cingulate cortex areas. The aim of the present study was to employ chaos analy
Externí odkaz:
https://doaj.org/article/85f57af5091d4e60acd1484e12b2edb8
Publikováno v:
IEEE Access, Vol 9, Pp 122254-122273 (2021)
This paper presents ear recognition models constructed with Deep Residual Networks (ResNet) of various depths. Due to relatively limited amounts of ear images we propose three different transfer learning strategies to address the ear recognition prob
Externí odkaz:
https://doaj.org/article/97a471de538a4b4abc2360d3d7257324
Publikováno v:
IEEE Access, Vol 8, Pp 170295-170310 (2020)
This paper employs state-of-the-art Deep Convolutional Neural Networks (CNNs), namely AlexNet, VGGNet, Inception, ResNet and ResNeXt in a first experimental study of ear recognition on the unconstrained EarVN1.0 dataset. As the dataset size is still
Externí odkaz:
https://doaj.org/article/4dd9436fca2c4319af330e37444f8655
Publikováno v:
PLoS ONE, Vol 17, Iss 12, p e0277772 (2022)
Cortical slow oscillations (SOs) and thalamocortical sleep spindles are two prominent EEG rhythms of slow wave sleep. These EEG rhythms play an essential role in memory consolidation. In humans, sleep spindles are categorized into slow spindles (8-12
Externí odkaz:
https://doaj.org/article/d8e6aec92d394e4ba1adef9e691dc6c8
Publikováno v:
PeerJ Computer Science, Vol 7, p e655 (2021)
In this paper we propose two novel deep convolutional network architectures, CovidResNet and CovidDenseNet, to diagnose COVID-19 based on CT images. The models enable transfer learning between different architectures, which might significantly boost
Externí odkaz:
https://doaj.org/article/629439eae21748d291bcd423a67c06bd
Publikováno v:
Mathematics, Vol 10, Iss 12, p 2001 (2022)
Sentiment analysis of news headlines is an important factor that investors consider when making investing decisions. We claim that the sentiment analysis of financial news headlines impacts stock market values. Hence financial news headline data are
Externí odkaz:
https://doaj.org/article/306b7b870a9740a59e751cf2c2c9c444
Publikováno v:
Sensors, Vol 21, Iss 2, p 455 (2021)
This paper explores how well deep learning models trained on chest CT images can diagnose COVID-19 infected people in a fast and automated process. To this end, we adopted advanced deep network architectures and proposed a transfer learning strategy
Externí odkaz:
https://doaj.org/article/560dffe72ab948bc92aa9a662be2e51d