Results 111 to 120 of about 599,022 (331)

Cu‐Based MOF/TiO2 Composite Nanomaterials for Photocatalytic Hydrogen Generation and the Role of Copper

Advanced Functional Materials, EarlyView.
HKUST‐1/TiO2 composite materials show a very high photocatalytic hydrogen evolution rate which increases as a function of the irradiation time until reaching a plateau and even surpasses the performance of the 1%Pt/TiO2 material after three photocatalytic cycles.
Alisha Khan, Marie Le Pivert, Alireza Ranjbari, Diana Dragoe, Daniel Bahena‐Uribe, Christophe Colbeau‐Justin, Christian Herrero, Dorota Rutkowska‐Zbik, Johnny Deschamps, Hynd Remita   +9 more
wiley   +1 more source

A Data Augmentation Method for Fully Automatic Brain Tumor Segmentation [PDF]

, 2022
Yu Wang, Yarong Ji, Hongbing Xiao
openalex   +1 more source

Align and Augment: Generative Data Augmentation for Compositional Generalization

Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)
This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme under grant agreement No 853459. The authors gratefully acknowledge the computer resources at ARTEMISA, funded by the European Union ERDF and Comunitat Valenciana as well as the technical support provided ...
Cazzaro, Francesco, Locatelli, Davide, Quattoni, Ariadna Julieta   +2 more
openaire   +2 more sources

Lipid Nanoparticles for the Delivery of CRISPR/Cas9 Machinery to Enable Site‐Specific Integration of CFTR and Mutation‐Agnostic Disease Rescue

Advanced Functional Materials, EarlyView.
Lipid nanoparticles (LNPs) are optimized to co‐deliver Cas9‐encoding messenger RNA (mRNA), a single guide RNA (sgRNA) targeting the endogenous cystic fibrosis transmembrane conductance regulator (CFTR) gene, and homologous linear double‐stranded donor DNA (ldsDNA) templates encoding CFTR.
Ruth A. Foley, Paul G. Ayoub, Vrishti Sinha, Colin Juett, Alicia Sanoyca, Emily C. Duggan, Lindsay E. Lathrop, Priyanka Bhatt, Kevin Coote, Beate Illek, Brigitte N. Gomperts, Donald B. Kohn, Steven J. Jonas   +12 more
wiley   +1 more source

Data Augmentation for Semantic Segmentation Using a Real Image Dataset Captured Around the Tsukuba City Hall

, 2023
Yuriko Ueda, Miho Adachi, Junya Morioka, Marin Wada, Ryusuke Miyamoto   +4 more
openalex   +1 more source

Improving Conversational Recommendation Systems via Bias Analysis and Language-Model-Enhanced Data Augmentation [PDF]

, 2023
Xi Wang, Hossein A. Rahmani, Jiqun Liu, Emine Yılmaz   +3 more
openalex   +1 more source

Data Augmentation for Traffic Classification

Data Augmentation (DA) -- enriching training data by adding synthetic samples -- is a technique widely adopted in Computer Vision (CV) and Natural Language Processing (NLP) tasks to improve models performance. Yet, DA has struggled to gain traction in networking contexts, particularly in Traffic Classification (TC) tasks.
Chao Wang, Alessandro Finamore, Pietro Michiardi, Massimo Gallo, Dario Rossi   +4 more
openaire   +2 more sources

Copper‐based Materials for Photo and Electrocatalytic Process: Advancing Renewable Energy and Environmental Applications

Advanced Functional Materials, EarlyView.
Cu‐based catalysts as a cornerstone in advancing sustainable energy technologies are fully reviewed in this manuscript, highlighting their potential in photo‐ and electrocatalysis. It includes metallic copper, copper oxides, copper sulfides, copper halide perovskites, copper‐based metal–organic frameworks (MOFs), and covalent organic frameworks (COFs),
Jéssica C. de Almeida, Yanjie Wang, Thais A. Rodrigues, Paulo H. H. Nunes, Vagner R. de Mendonça, Paulo H. E. Falsetti, Leticia V. Savazi, Tao He, Alexandra V. Bardakova, Aida V. Rudakova, Jie Tian, Alexei V. Emeline, Osmando F. Lopes, Antonio Otavio T. Patrocínio, Jia Hong Pan, Caue Ribeiro, Detlef W. Bahnemann   +16 more
wiley   +1 more source

A systematic review of deep learning data augmentation in medical imaging: Recent advances and future research directions

Healthcare Analytics
Data augmentation involves artificially expanding a dataset by applying various transformations to the existing data. Recent developments in deep learning have advanced data augmentation, enabling more complex transformations.
Tauhidul Islam, Md. Sadman Hafiz, Jamin Rahman Jim, Md. Mohsin Kabir, M.F. Mridha   +4 more
doaj   +1 more source

Effectiveness of data-augmentation on deep learning in evaluating rapid on-site cytopathology at endoscopic ultrasound-guided fine needle aspiration [PDF]

, 2023
Yuki Fujii, Daisuke Uchida, Ryosuke Sato, Taisuke Obata, Akihiro Matsumi, Kazuya Miyamoto, Kosaku Morimoto, Hiroyuki Terasawa, Tatsuhiro Yamazaki, Kazuyuki Matsumoto, Shigeru Horiguchi, Koichiro Tsutsumi, Hironari Kato, Ten Cho, Takayoshi Tanimoto, Akimitsu Ohto, Hirofumi Inoue, Yoshiro Kawahara, Motoyuki Otsuka   +18 more
openalex   +1 more source