Results 201 to 210 of about 9,883,756 (332)

High-Performance Deep Learning Systems via DL Sparsity and DL Compiler

Deep learning (DL) has achieved impressive results in many tasks across recognition, decision, and content generation, generating significant economic growth and social benefits. The widespread adoption of DL requires efficient systems that can support large-scale training and reduce the cost of inference.
openaire   +1 more source

Correction: Diagnostic accuracy of deep learning vs. human raters for detecting osteoporotic vertebral compression fractures in routine CT scans. [PDF]

Eur Radiol
Riedel EO, Schinz D, Keicher M, Rühling S, El Husseini M, Pellegrini C, Baum T, Dieckmeyer M, Malagutti L, Seeger I, Walburga AS, Wiestler B, Sollmann N, Löffler MT, Wagner A, Kirschke JS.   +15 more
europepmc   +1 more source

Comparative Analysis of Poly(Ethylene Glycol) (PEG) and Poly(2‐Ethyl‐2‐Oxazoline) (PEtOx) for Organic Solvent‐Free Lipid Nanoparticle Formulations

Angewandte Chemie International Edition, EarlyView.
Organic solvent‐free lipid nanoparticles featuring PEtOx‐based stealth lipids enable efficient mRNA and CRISPR‐Cas9 delivery while exhibiting markedly improved biocompatibility compared with PEG‐based analogues. Their successful ex vivo and in vivo performance, combined with data‐driven formulation optimization, establishes a versatile platform that ...
Michael Streiber, Caroline T. Holick, Lucas Gath, Ekaterina Tsarenko, Vivien Bachmann, Stavroula Litsiou, Lukas Harder, Laura J. Rosenberger, Aleksandar Rusevski, Julian Kimmig, Stephan Culemann, Christian Franke, Claudia Waskow, Stephanie Hoeppener, Stephanie Schubert, Matthias Bros, Oliver Werz, Ivo Nischang, Michael Bauer, Adrian T. Press, Ulrich S. Schubert, Anja Traeger   +21 more
wiley   +1 more source

The Manifestation of the Electrochemical Potential Gradient in the Kinetic Landscapes of Interfacial Electrochemistry

Angewandte Chemie International Edition, EarlyView.
The overpotential constitutes an electrochemical potential difference at the solid–liquid interface, which can manifest itself in different ways. In general, it can not only drive the reaction along the reaction coordinate, but also modulate chemical potentials in the extended environment that shape activation barriers, without necessarily being a ...
Sebastian Z. Oener, Caroline J. Aschendorf, Jody Druce, Francisco Sarabia, Carlos Gomez Rodellar, Mathieu Lizée, Alex Ricardo Silva Olaya, Soumyadip Mondal, Raquel Anastacio Amaral, Hađer Sinanović, Beatriz Roldan Cuenya   +10 more
wiley   +1 more source

OsteoNet-X: A deep residual learning framework for automated osteoporosis detection from knee X-ray images. [PDF]

PLoS One
Sangula SK, Ibrahim SPS.
europepmc   +1 more source

Deep learning radiomics based on preoperative multiparametric MRI in predicting breast cancer recurrence risk. [PDF]

BMC Med Imaging
Gong X, Xu K, Hua M, Zhang Y, Zheng H, Fan S, Wang C, Song J, Zhou C, Bu Y, Wang K, Xu M, Zhang R.   +12 more
europepmc   +1 more source

Advancing Environmental Sustainability: The Role of Artificial Intelligence in Monitoring, Predicting, and Controlling Sulfur Dioxide Emissions

Asia-Pacific Journal of Chemical Engineering, EarlyView.
ABSTRACT Air pollution from sulfur dioxide (SO2) emissions poses significant threats to environmental sustainability, public health, and climate change efforts. Despite advances in monitoring and regulatory frameworks, traditional methods often fall short in accuracy, scalability, and efficiency.
Turkan Kopac
wiley   +1 more source

A multi‐task deep learning–based approach to identify and assess dry root rot disease in chickpea

Applications in Plant Sciences, EarlyView.
Abstract Premise Dry root rot (DRR), an emerging global disease exacerbated by drought, affects a wide range of crops. The disease symptoms are manually scored for large‐scale germplasm screening to identify disease‐resistant varieties and test transgenic lines and other varieties.
Piyush Priya, Joe Johnson, Athimoolam Durgadevi, Navaneeth Vinayachandran, Meghna Pillai, Bharat Maitraya, Muthukumar V. Bagavathiannan, Muthappa Senthil‐Kumar   +7 more
wiley   +1 more source

Petal to the metal: The slow road to automating large‐scale phenology labeling for herbarium specimens

Applications in Plant Sciences, EarlyView.
Abstract Premise Herbarium specimens represent critical historical records of plant phenology, yet automating annotation of reproductive structures remains challenging given the diversity of floral morphologies, specimen age and quality, and image quality.
Erin L. Grady, Raphael LaFrance, Daijiang Li, Russell Dinnage, Ellen G. Denny, John Deck, Robert P. Guralnick   +6 more
wiley   +1 more source

Bridging the performance-efficiency gap: a resource-efficient hybrid DL-ML framework for jackfruit disease detection. [PDF]

Front Artif Intell
Turjy RCD, Farid FA, Bijoy MHI, Bappy SP, Sohel A, Uddin J, Abdul Karim HB.   +6 more
europepmc   +1 more source