Results 71 to 80 of about 264,274 (268)
Advanced Healthcare Materials, EarlyView.Over half of cancer patients undergo radiotherapy. Laser ablation enabled the synthesis of immiscible Au‐Fe‐B nanoparticles designed as degradable bimodal radiosensitizers for X‐ray radiotherapy (XRT), boron neutron capture therapy (BNCT), and bimodal imaging for X‐ray computed tomography (CT) and magnetic resonance imaging (MRI). These nanosensitizers
Michael Bissoli +15 more
wiley +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 +4 more
doaj +1 more source
Bioinspired Adaptive Sensors: A Review on Current Developments in Theory and Application
Advanced Materials, EarlyView.This review comprehensively summarizes the recent progress in the design and fabrication of sensory‐adaptation‐inspired devices and highlights their valuable applications in electronic skin, wearable electronics, and machine vision. The existing challenges and future directions are addressed in aspects such as device performance optimization ...
Guodong Gong +12 more
wiley +1 more source
A Comprehensive Review of Deep Learning: Architectures, Recent Advances, and Applications
InformationDeep 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 ConferencesA 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
Advanced Materials, EarlyView.AI‐Assisted Workflow for (Scanning) Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling. Abstract (Scanning) transmission electron microscopy ((S)TEM) has significantly advanced materials science but faces challenges in correlating precise atomic structure information with the functional properties of ...
Marc Botifoll +19 more
wiley +1 more source
Deep Learning Techniques for Agronomy Applications
Agronomy, 2019 This editorial introduces the Special Issue, entitled “Deep Learning (DL) Techniques for Agronomy Applications„, of Agronomy. Topics covered in this issue include three main parts: (I) DL-based image recognition techniques for agronomy ...
Chi-Hua Chen +2 more
doaj +1 more source
Oxygen Evolution Reaction Catalysts for Acidic‐Media CO2 Electrolyzers
Advanced Materials, EarlyView.Acidic‐media CO2 electroreduction (CO2R) could decarbonize chemical production, despite relying on rare‐earth elements for anodic oxygen evolution reaction (OER). Transferring the learnings from mature sister technologies (water electrolysis) could accelerate technological development.
Mingcheng Huang, Adnan Ozden
wiley +1 more source
A Survey Study of the Deep Learning for Convolutional Neural Network Architecture [PDF]
BIO Web of ConferencesThe deep learning (DL) computer paradigm has been the industry standard for machine learning (ML) during the past few years. It has gradually become the most widely used computational technique in machine learning.
Mohammed Alkhaldi Tabark +6 more
doaj +1 more source