Results 51 to 60 of about 75,080 (277)

Enhancing parkinson disease detection through feature based deep learning with autoencoders and neural networks

Scientific Reports
Parkinson’s disease is a neurodegenerative disorder that is associated with aging, leading to the progressive deterioration of certain regions of the brain.
P. Valarmathi, Y. Suganya, K. R. Saranya, S. Shanmuga Priya   +3 more
doaj   +1 more source

TensorQuant - A Simulation Toolbox for Deep Neural Network Quantization

, 2017
Recent research implies that training and inference of deep neural networks (DNN) can be computed with low precision numerical representations of the training/test data, weights and gradients without a general loss in accuracy.
Keuper, Janis, Loroch, Dominik Marek, Pfreundt, Franz-Josef, Wehn, Norbert   +3 more
core   +1 more source

Composite Adaptive Lyapunov-Based Deep Neural Network (Lb-DNN) Controller

, 2023
Recent advancements in adaptive control have equipped deep neural network (DNN)-based controllers with Lyapunov-based adaptation laws that work across a range of DNN architectures to uniquely enable online learning. However, the adaptation laws are based on tracking error, and offer convergence guarantees on only the tracking error without providing ...
Patil, Omkar Sudhir, Griffis, Emily J., Makumi, Wanjiku A., Dixon, Warren E.   +3 more
openaire   +2 more sources

Computational Modeling Meets 3D Bioprinting: Emerging Synergies in Cardiovascular Disease Modeling

Advanced Healthcare Materials, EarlyView.
Emerging advances in three‐dimensional bioprinting and computational modeling are reshaping cardiovascular (CV) research by enabling more realistic, patient‐specific tissue platforms. This review surveys cutting‐edge approaches that merge biomimetic CV constructs with computational simulations to overcome the limitations of traditional models, improve ...
Tanmay Mukherjee, Mehdi Salar Amoli, Sarah Rezapourdamanab, Lama Rita El Shammas, Martin L. Tomov, Emilio A. Mendiola, Vahid Serpooshan, Reza Avazmohammadi   +7 more
wiley   +1 more source

Comparing Hybrid Approaches of Deep Learning for Remaining Useful Life Prognostic of Lithium-Ion Batteries

IEEE Access
Many published journals used hybrid deep learning methods to predict batteries’ remaining useful life by adopting different rationales to select and combine deep learning methods aiming to propose the most accurate prediction model possible.
Anas Tiane, Chafik Okar, Mohamad Alzayed, Hicham Chaoui   +3 more
doaj   +1 more source

Max-Pooling Loss Training of Long Short-Term Memory Networks for Small-Footprint Keyword Spotting

, 2017
We propose a max-pooling based loss function for training Long Short-Term Memory (LSTM) networks for small-footprint keyword spotting (KWS), with low CPU, memory, and latency requirements.
Fu, Gengshen, Mandal, Arindam, Matsoukas, Spyros, Panchapagesan, Sankaran, Raju, Anirudh, Strom, Nikko, Sun, Ming, Tucker, George, Vitaladevuni, Shiv   +8 more
core   +1 more source

Recent Progress on Flexible Multimodal Sensors: Decoupling Strategies, Fabrication and Applications

Advanced Materials, EarlyView.
In this review, we establish a tripartite decoupling framework for flexible multimodal sensors, which elucidates the underlying principles of signal crosstalk and their solutions through material design, structural engineering, and AI algorithms. We also demonstrate its potential applications across environmental monitoring, health monitoring, human ...
Tao Wu, Yu‐Tao Li, Luyu Zhao, Yi Zhang, Zhaojie Zhang, Jian Yuan, Yiwen Wu, Anqi Che, Yuanxiao Ma, Yang Chai, Yeliang Wang   +10 more
wiley   +1 more source

Advanced Design for Weakly Coupled Resonators by Automatic Active Optimization

Advanced Materials Technologies, EarlyView.
An Automatic Active Optimization (AAO) strategy integrates machine learning predictors and genetic algorithms in a closed‐loop workflow. By iteratively expanding its dataset with new discoveries, AAO overcomes the limits of conventional methods. This approach finds superior microstructural designs beyond the initial sample space. We demonstrate this on
Wei Yue, Yuan Gao, Fanping Sui, Jason Wang, Megan Teng, Peggy Tsao, Huicong Deng, Yande Peng, Liwei Lin   +8 more
wiley   +1 more source

Recent Advances of Slip Sensors for Smart Robotics

Advanced Materials Technologies, EarlyView.
This review summarizes recent progress in robotic slip sensors across mechanical, electrical, thermal, optical, magnetic, and acoustic mechanisms, offering a comprehensive reference for the selection of slip sensors in robotic applications. In addition, current challenges and emerging trends are identified to advance the development of robust, adaptive,
Xingyu Zhang, Liao Wu, Shuai He, Zhao Sha, Yuwan Huang, Shuying Wu, Dewei Chu, Chun H. Wang, Shuhua Peng   +8 more
wiley   +1 more source

Learning Deep Embedding with Acoustic and Phoneme Features for Speaker Recognition in FM Broadcasting

IET Biometrics
Text-independent speaker verification (TI-SV) is a crucial task in speaker recognition, as it involves verifying an individual’s claimed identity from speech of arbitrary content without any human intervention.
Xiao Li, Xiao Chen, Rui Fu, Xiao Hu, Mintong Chen, Kun Niu   +5 more
doaj   +1 more source