Results 81 to 90 of about 267,347 (270)

Deep Learning-Based Predictive Control of Vehicle-to-Grid Onboard Charger Back Stage Models

IEEE Access
To address the insufficient modeling accuracy and slow dynamic response of the Capacitor-Inductor-Inductor-Capacitor (CLLC) resonant converter in Vehicle-to-Grid (V2G) automotive onboard charger, a deep learning-based model predictive control method for ...
Yongquan Zhang, Weidong Xue, Shuaibing Li, Yongqiang Kang, Junmin Zhu, Haiying Dong   +5 more
doaj   +1 more source

Deep Learning: A Review for the Radiation Oncologist

Frontiers in Oncology, 2019
Introduction: Deep Learning (DL) is a machine learning technique that uses deep neural networks to create a model. The application areas of deep learning in radiation oncology include image segmentation and detection, image phenotyping, and radiomic ...
Luca Boldrini, Jean-Emmanuel Bibault, Carlotta Masciocchi, Yanting Shen, Martin-Immanuel Bittner   +4 more
doaj   +1 more source

AI–Guided 4D Printing of Carnivorous Plants–Inspired Microneedles for Accelerated Wound Healing

Advanced Materials, EarlyView.
This work presents an artificial intelligence (AI)‐guided 4D‐printed microneedle platform inspired by carnivorous plants for wound healing. A thermo‐responsive shape memory polymer enables body temperature–triggered self‐coiling for autonomous wound closure.
Hyun Lee, Moon‐Jo Kim, DongEung Kim, Chan Ho Moon, Seojoon Bang, Hyeong Seok Kang, Ju Yeong Gwon, Jong Hwa Seo, Junhyub Jeon, Junhyuk Son, Munwon Lim, Minho Kang, Dong Yun Lee, Donghyun Lim, Jung‐Hoon Park, Gi Doo Cha, Soo‐Hong Lee, Tae‐Sik Jang, Kisuk Yang, Yunho Jeong, Youngho Eom, Hyun‐Do Jung   +21 more
wiley   +1 more source

A Comprehensive Review of Deep Learning: Architectures, Recent Advances, and Applications

Information
Deep learning (DL) has become a core component of modern artificial intelligence (AI), driving significant advancements across diverse fields by facilitating the analysis of complex systems, from protein folding in biology to molecular discovery in ...
Ibomoiye Domor Mienye, Theo G. Swart
doaj   +1 more source

Pragmatic Study of Botnet Attack Detection In An IoT Environment [PDF]

E3S Web of Conferences
A comprehensive search for primary research published between 2014 and 2023 was carried across several databases. Studies that describe the application of machine learning (ML) and deep learning techniques for if they was carried out across several ...
Vennapureddy Rajasree, Srinivasulu T.
doaj   +1 more source

DL-PRO: A novel deep learning method for protein model quality assessment [PDF]

2014 International Joint Conference on Neural Networks (IJCNN), 2014
Computational protein structure prediction is very important for many applications in bioinformatics. In the process of predicting protein structures, it is essential to accurately assess the quality of generated models. Although many single-model quality assessment (QA) methods have been developed, their accuracy is not high enough for most real ...
Son P, Nguyen, Yi, Shang, Dong, Xu
openaire   +2 more sources

Bidirectional Process Prediction in the Laser‐Induced‐Graphene Production Using Blackbox Deep Learning

Advanced Materials Technologies, EarlyView.
This study shows that a lightweight blackbox neural network provides a practical, cost‐effective solution for bidirectional process prediction in laser‐induced graphene (LIG) fabrication. Achieving high predictive performance with minimal overhead, the approach democratizes machine learning (ML) for resource‐limited environments.
Maxim Polomoshnov, Nitheesh M. Nair, Gerardo Hernández‐Sosa, Markus Reischl   +3 more
wiley   +1 more source

Cross‐Scale Hierarchical Targeted Delivery System Based on Small‐Scale Magnetic Robots

Advanced Robotics Research, EarlyView.
This article reviews a cross‐scale hierarchical targeted delivery system that integrates magnetic continuum robots and magnetic microrobots. By combining rapid long‐range navigation with precise microscale targeting, the system overcomes key limitations of single‐scale approaches.
Junjian Zhou, Zhiqiang Chen, Yuanbiao Ma, Zhiqiang Tang, Qianqian Wang   +4 more
wiley   +1 more source

DL-AMC: Deep Learning for Automatic Modulation Classification

Automatic Modulation Classification (AMC) is a signal processing technique widely used at the physical layer of wireless systems to enhance spectrum utilization efficiency. In this work, we propose a fast and accurate AMC system, termed DL-AMC, which leverages deep learning techniques.
Rehman, Faheem Ur, Abbas, Qamar, Shehzad, M. Karam   +2 more
openaire   +2 more sources

Deep learning (DL) Opens New Horizons in Personalized Medicine [PDF]

Biomedical Journal of Scientific & Technical Research, 2018
Although the idea of personalization of patient care dates to the time of Hippocrates, recent advances in diagnostic medical imaging and molecular medicine are gradually transforming health care services, by offering information and diagnostic tools enabling individualized patient management.
openaire   +1 more source