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Diyuan Lu
Diyuan Lu
PhD student in Frankfurt institute of advanced studies
Bestätigte E-Mail-Adresse bei fias.uni-frankfurt.de
Titel
Zitiert von
Zitiert von
Jahr
Residual deep convolutional neural network for eeg signal classification in epilepsy
D Lu, J Triesch
arXiv preprint arXiv:1903.08100, 2019
352019
Human-expert-level brain tumor detection using deep learning with data distillation and augmentation
D Lu, N Polomac, I Gacheva, E Hattingen, J Triesch
ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021
152021
Towards Early Diagnosis of Epilepsy from EEG Data
D Lu, S Bauer, V Neubert, LS Costard, F Rosenow, J Triesch
Machine Learning for Healthcare Conference, 80-96, 2020
52020
Residual deep convolutional neural network for eeg signal classification in epilepsy. arXiv 2019
D Lu, J Triesch
arXiv preprint arXiv:1903.08100, 0
5
Energy efficient path planning of autonomous underwater vehicles for environment modeling
D Lu, R Cui, P Wang
2014 International Conference on Multisensor Fusion and Information …, 2014
42014
Staging Epileptogenesis with Deep Neural Networks
D Lu, S Bauer, V Neubert, LS Costard, F Rosenow, J Triesch
Proceedings of the 11th ACM International Conference on Bioinformatics …, 2020
32020
A deep residual neural network based framework for epileptogenesis detection in a rodent model with single-channel EEG recordings
D Lu, S Bauer, V Neubert, LS Costard, F Rosenow, J Triesch
2019 12th International Congress on Image and Signal Processing, BioMedical …, 2019
32019
Diagnosing Epileptogenesis with Deep Anomaly Detection
A Farahat, D Lu, S Bauer, V Neubert, LS Costard, F Rosenow, J Triesch
2022
Multiple Instance Learning for Brain Tumor Detection from Magnetic Resonance Spectroscopy Data
D Lu, G Kurz, N Polomac, I Gacheva, E Hattingen, J Triesch
arXiv preprint arXiv:2112.08845, 2021
2021
P2. Unsupervised anomaly detection for diagnosing brain disorders from EEG recordings–Results from a rodent epilepsy model
A Farahat, D Lu, S Bauer, F Rosenow, J Triesch
Clinical Neurophysiology 132 (8), e1-e2, 2021
2021
FV18 Towards epileptogenesis staging with deep neural networks
D Lu, S Bauer, V Neubert, LS Costard, F Rosenow, J Triesch
Clinical Neurophysiology 131 (4), e231-e232, 2020
2020
Machine learning for healthcare with a focus on the early diagnosis of epilepsy and brain tumor detection
D Lu
Dissertation, Frankfurt am Main, Johann Wolfgang Goethe-Universität, 2022, 0
MULTIPLE INSTANCE-BASED TUMOR DETECTION FROM MAGNETIC RESONANCE SPECTROSCOPY DATA
D Lu, G Kurz, N Polomac, I Gacheva, E Hattingen, J Triesch
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