Khorsheed, May Sadiq Karim, AbdulAmir Abdullah
Published in
Open Engineering
Electrocardiogram (ECG) recognition systems now play a leading role in the early detection of cardiovascular diseases. However, the explanation of judgments made by deep learning models in these systems is prominent for clinical acceptance. This article reveals the effect of transfer learning in ECG recognition systems on decision precision. This a...
Boyer, M.D. Scotti, F. Gajaraj, V.
Published in
Nuclear Fusion
Deep learning approaches have been applied to images of C III emission in the lower divertor of DIII-D to develop models for estimating the level of detachment and magnetic configuration (X-point location and strike point radial location). The poloidal distance from the target to the C III emission front is used to represent the level of detachment...
Guitouni, Zied Maize, Sirine Zrigui, Mounir Machhout, Mohsen
Published in
Physica Scripta
The secure distribution of keys is essential to ensuring the privacy and integrity of data in Internet of Things (IoT) systems. Quantum Key Distribution (QKD) protocols, such as BB84, use principles from quantum mechanics to establish secure communication channels. However, errors that occur during the transmission of qubits can compromise the reli...
Kulkarni, Vikram Nemade, Bhushankumar Patel, Shreyaskumar Patel, Keyur Velpula, Srikanth
Published in
Frontiers in Psychiatry
Schild, Leona Zang, Jana Flügel, Till Weiss, Deike Schlaefer, Alexander Latus, Sarah
Published in
Current Directions in Biomedical Engineering
A deformation of the hard palate can occur in spinal muscular atrophy and leads to problems with feeding and swallowing in early childhood. An objective analysis of the palatal changes is therefore desirable for early treatment initiation. In this study, we investigate a deep learning approach to automatically detect deformation in endoscopic image...
zikuda, michal
Tato bakalářská práce se zabývá možnými přístupy pro tvorbu ϥD modelů stromů, využitím fotogrammetrie a neuronových sítí. Teoretická část popisuje základní principy fotogrammetrie a neuronových sítí, se zaměřením na konvoluční neuronové sítě, které se využívají k analýze obrazových dat. Praktická část obsahuje postup pro aproximaci modelů stromů vy...
Giuseppi, Alessandro Menegatti, Danilo Pietrabissa, Antonio
Published in
Machine Learning: Science and Technology
Chaos detection is the problem of identifying whether a series of measurements is being sampled from an underlying set of chaotic dynamics. The unavoidable presence of measurement noise significantly affects the performance of chaos detectors, as discerning chaotic dynamics from stochastic signals becomes more challenging. This paper presents a com...
fencl, roman
Má bakalářská práce se zabývá segmentací obrazu pomocí konvolučních neuronových sítí. Nejprve popisuji problematiku počítačového vidění a konvolučních neuronových sítí, jejich vrstvy a průběh trénování. Následně představuji různé modely používané pro segmentaci a popisuji možnost využití předtrénovaných enkodérů VGG16 a ResNet50. Zabývám se použitý...
Yang, Richard Chen, Ding Yang, Qingping Qiu, Yang Wang, Fang
Published in
International Journal of Metrology and Quality Engineering
COVID-19 has spread rapidly worldwide in the past three years, triggering partial and full lockdowns globally. The successful control of the COVID-19 pandemic on a global scale depended heavily upon the accurate detection of COVID-19. However, the main diagnostic tests for COVID-19 have some significant limitations, e.g. the major nucleic acid (RT-...
Lai, Yuebo Liu, Bing
Published in
Measurement Science and Technology
Efficient and precise identification of road pavement cracks contributes to better evaluation of road conditions. In practical road maintenance and safety assessment, traditional manual crack detection methods are time-consuming, physically demanding, and highly subjective. In addition, crack recognition based on image processing techniques lacks r...
