Suchergebnisse - "Biomedical signal processing and control"

HiFuse: Hierarchical multi-scale feature fusion network for medical image classification von Huo, Xiangzuo, Sun, Gang, Tian, Shengwei, Wang, Yan, Yu, Long, Long, Jun, Zhang, Wendong, Li, Aolun

“… Effective fusion of global and local multi-scale features is crucial for medical image classification. Medical images have many noisy, scattered features, …”
Volltext

Speech emotion recognition with deep convolutional neural networks von Issa, Dias, Fatih Demirci, M., Yazici, Adnan

“… •Sound files are represented effectively by combining various features.•The framework sets the new SOTA on two datasets for speech emotion recognition.•For the …”
Volltext

Transformers in medical image segmentation: A review von Xiao, Hanguang, Li, Li, Liu, Qiyuan, Zhu, Xiuhong, Zhang, Qihang

“… Transformer is a model relying entirely on self-attention which has a wide range of applications in the field of natural language processing. Researchers are …”
Volltext

Deep learning for motor imagery EEG-based classification: A review von Al-Saegh, Ali, Dawwd, Shefa A., Abdul-Jabbar, Jassim M.

“… The availability of large and varied Electroencephalogram (EEG) datasets, rapidly advances and inventions in deep learning techniques, and highly powerful and …”
Volltext

Application of deep learning techniques for detection of COVID-19 cases using chest X-ray images: A comprehensive study von Nayak, Soumya Ranjan, Nayak, Deepak Ranjan, Sinha, Utkarsh, Arora, Vaibhav, Pachori, Ram Bilas

“… The emergence of Coronavirus Disease 2019 (COVID-19) in early December 2019 has caused immense damage to health and global well-being. Currently, there are …”
Volltext

Speech emotion recognition using deep 1D & 2D CNN LSTM networks von Zhao, Jianfeng, Mao, Xia, Chen, Lijiang

“… We aimed at learning deep emotion features to recognize speech emotion. Two convolutional neural network and long short-term memory (CNN LSTM) networks, one 1D …”
Volltext

MFCC-based Recurrent Neural Network for automatic clinical depression recognition and assessment from speech von Rejaibi, Emna, Komaty, Ali, Meriaudeau, Fabrice, Agrebi, Said, Othmani, Alice

“… •A deep Recurrent Neural Network based framework for depression recognition from speech.•A robust approach that outperforms the state-of-art approaches on …”
Volltext

Attention Res-UNet with Guided Decoder for semantic segmentation of brain tumors von Maji, Dhiraj, Sigedar, Prarthana, Singh, Munendra

“… [Display omitted] •Guided decoder supervises the learning process and produces improved features.•Weighted guided loss improves the prediction capabilities of …”
Volltext

A review of feature extraction and performance evaluation in epileptic seizure detection using EEG von Boonyakitanont, Poomipat, Lek-uthai, Apiwat, Chomtho, Krisnachai, Songsiri, Jitkomut

“… •Detailed mathematical description of features and their physical interpretations relevant to epileptic seizure detection are provided.•Performance of each …”
Volltext

Automated Atrial Fibrillation Detection using a Hybrid CNN-LSTM Network on Imbalanced ECG Datasets von Petmezas, Georgios, Haris, Kostas, Stefanopoulos, Leandros, Kilintzis, Vassilis, Tzavelis, Andreas, Rogers, John A, Katsaggelos, Aggelos K, Maglaveras, Nicos

“… •The hybrid CNN-LSTM approach provides the best combination of performance (sensitivity, specificity) in comparison with all previous relevant studies.•The …”
Volltext

An IoT-based framework for early identification and monitoring of COVID-19 cases von Otoom, Mwaffaq, Otoum, Nesreen, Alzubaidi, Mohammad A., Etoom, Yousef, Banihani, Rudaina

“… •Early Identification or Prediction of COVID-19 cases.•Real-time Monitoring of COVID-19.•Treatment Response of COVID-19 confirmed cases.•An IoT-based Framework …”
Volltext

A fully automated deep learning-based network for detecting COVID-19 from a new and large lung CT scan dataset von Rahimzadeh, Mohammad, Attar, Abolfazl, Sakhaei, Seyed Mohammad

“… [Display omitted] •We introduce and share a new and large dataset of original CT scans.•We introduce a fully automated system for detecting COVID-19 cases that …”
Volltext

Breast mass segmentation in ultrasound with selective kernel U-Net convolutional neural network von Byra, Michal, Jarosik, Piotr, Szubert, Aleksandra, Galperin, Michael, Ojeda-Fournier, Haydee, Olson, Linda, O’Boyle, Mary, Comstock, Christopher, Andre, Michael

“… •Convolutional neural networks can efficiently segment breast masses in ultrasound.•Segmentation network's receptive field can be adjusted with an attention …”
Volltext

A deep learning outline aimed at prompt skin cancer detection utilizing gated recurrent unit networks and improved orca predation algorithm von Zhang, Li, Zhang, Jian, Gao, Wenlian, Bai, Fengfeng, Li, Nan, Ghadimi, Noradin

“… •The proposed strategy improves skin cancer diagnosis and patient outcomes.•Gated Recurrent Unit Network optimized by Orca predation Algorithm is used as a …”
Volltext

A review on EMG-based motor intention prediction of continuous human upper limb motion for human-robot collaboration von Bi, Luzheng, Feleke, Aberham -->Genetu, Guan, Cuntai

“… Electromyography (EMG) signal is one of the widely used biological signals for human motor intention prediction, which is an essential element in human-robot …”
Volltext

Iterative reconstruction of low-dose CT based on differential sparse von Lu, Siyu, Yang, Bo, Xiao, Ye, Liu, Shan, Liu, Mingzhe, Yin, Lirong, Zheng, Wenfeng

“… •Focuses on how to reduce the radiation dose of CT and ensure CT's imaging quality.•Proposes a discriminative sparse transform iterative reconstruction …”
Volltext

An efficient multi-scale CNN model with intrinsic feature integration for motor imagery EEG subject classification in brain-machine interfaces von Roy, Arunabha M.

“… •An efficient multi-scale CNN(MS-CNN) model has been proposed with intrinsic feature integration for motor imagery EEG subject classification in brain-machine …”
Volltext

Intra- and inter-epoch temporal context network (IITNet) using sub-epoch features for automatic sleep scoring on raw single-channel EEG von Seo, Hogeon, Back, Seunghyeok, Lee, Seongju, Park, Deokhwan, Kim, Tae, Lee, Kyoobin

“… •IITNet extracts representative features at a sub-epoch level from raw single-channel EEG.•Intra- and inter-epoch temporal contexts are captured in multiple …”
Volltext

Deep neural network with generative adversarial networks pre-training for brain tumor classification based on MR images von Ghassemi, Navid, Shoeibi, Afshin, Rouhani, Modjtaba

“… •Presenting an unsupervised pretraining method to overcome overfitting using GAN.•The unsupervised pretraining allow using of similar unlabeled datasets.•This …”
Volltext

Endoscope image mosaic based on pyramid ORB von Zhang, Ziyan, Wang, Lixiao, Zheng, Wenfeng, Yin, Lirong, Hu, Rongrong, Yang, Bo

“… •The key to endoscopic image mosaics success is the accuracy of image registration and fusion.•This paper uses the Gaussian Pyramid to improve the simple …”
Volltext