Results 61 to 70 of about 876,297 (223)

Deep neural networks for ultrasound beamforming [PDF]

2017 IEEE International Ultrasonics Symposium (IUS), 2017
We investigate the use of deep neural networks (DNNs) for suppressing off-axis scattering in ultrasound channel data. Our implementation operates in the frequency domain via the short-time Fourier transform. The inputs to the DNN consisted of the separated real and imaginary components (i.e.
Adam C. Luchies, Brett C. Byram
openaire   +2 more sources

Convergence of deep convolutional neural networks

Neural Networks, 2022
arXiv admin note: text overlap with arXiv:2107 ...
Yuesheng Xu, Haizhang Zhang
openaire   +4 more sources

The Construction of Smart Chinese Medicine Cloud Health Platform Based on Deep Neural Networks

International Transactions on Electrical Energy Systems, 2022
In order to improve the efficiency of doctors’ diagnosis and treatment, the state has built a Chinese medicine cloud health platform. However, most medical institutions currently use internal networks, and the technical standards and specifications are ...
Yaofeng Miao, Yuan Zhou
doaj   +1 more source

Learning to Balance Local Losses via Meta-Learning

IEEE Access, 2021
The standard training for deep neural networks relies on a global and fixed loss function. For more effective training, dynamic loss functions have been recently proposed.
Seungdong Yoa, Minkyu Jeon, Youngjin Oh, Hyunwoo J. Kim   +3 more
doaj   +1 more source

Hierarchical Temporal Representation in Linear Reservoir Computing

, 2017
Recently, studies on deep Reservoir Computing (RC) highlighted the role of layering in deep recurrent neural networks (RNNs). In this paper, the use of linear recurrent units allows us to bring more evidence on the intrinsic hierarchical temporal ...
Claudio Gallicchio, Claudio Gallicchio, D Koryakin, D Verstraeten, G Holzmann, H Jaeger, H Jaeger, J Schmidhuber, J Schmidhuber, M Lukoševičius, M Čerňanskỳ, S Otte, Y Xue   +12 more
core   +1 more source

Training Deep Neural Networks with Adaptive Momentum Inspired by the Quadratic Optimization [PDF]

, 2021
Tao Sun, Huaming Ling, Zuoqiang Shi, Dongsheng Li, Bao Wang   +4 more
openalex   +1 more source

Cross-layer transmission realized by light-emitting memristor for constructing ultra-deep neural network with transfer learning ability

Nature Communications
Deep neural networks have revolutionized several domains, including autonomous driving, cancer detection, and drug design, and are the foundation for massive artificial intelligence models.
Zhenjia Chen, Zhenyuan Lin, Ji Yang, Cong Chen, Di Liu, Liuting Shan, Yuanyuan Hu, Tailiang Guo, Huipeng Chen   +8 more
doaj   +1 more source

Optimized Deep Convolutional Neural Networks for Identification of Macular Diseases from Optical Coherence Tomography Images

Algorithms, 2019
Finetuning pre-trained deep neural networks (DNN) delicately designed for large-scale natural images may not be suitable for medical images due to the intrinsic difference between the datasets.
Qingge Ji, Jie Huang, Wenjie He, Yankui Sun   +3 more
doaj   +1 more source

Spiking Neural Networks and Their Applications: A Review

Brain Sciences, 2022
The past decade has witnessed the great success of deep neural networks in various domains. However, deep neural networks are very resource-intensive in terms of energy consumption, data requirements, and high computational costs.
Kashu Yamazaki, Viet-Khoa Vo-Ho, Darshan Bulsara, Ngan Le   +3 more
doaj   +1 more source

Evaluation of Various Open-Set Medical Imaging Tasks with Deep Neural Networks [PDF]

, 2021
Zongyuan Ge, Xin Wang
openalex   +1 more source