Results 51 to 60 of about 52,284 (313)

Deep Learning–Assisted Differentiation of Four Peripheral Neuropathies Using Corneal Confocal Microscopy

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Peripheral neuropathies contribute to patient disability but may be diagnosed late or missed altogether due to late referral, limitation of current diagnostic methods and lack of specialized testing facilities. To address this clinical gap, we developed NeuropathAI, an interpretable deep learning–based multiclass classification ...
Chaima Ben Rabah, Ioannis N. Petropoulos, Mark Stettner, Maryam Ferdousi, Uazman Alam, Nathan Efron, Ahmed Serag, Rayaz A. Malik   +7 more
wiley   +1 more source

Improving neural networks by preventing co-adaptation of feature detectors [PDF]

, 2012
When a large feedforward neural network is trained on a small training set, it typically performs poorly on held-out test data. This "overfitting" is greatly reduced by randomly omitting half of the feature detectors on each training case.
Hinton, Geoffrey E., Krizhevsky, Alex, Salakhutdinov, Ruslan R., Srivastava, Nitish, Sutskever, Ilya   +4 more
core   +1 more source

A self‐supervised causal feature reinforcement learning method for non‐invasive hemoglobin prediction

IET Image Processing
Anemia (hemoglobin (Hb) 
Linquan Xu, Yuwen Chen, Songmei Lu, Kunhua Zhong, Yujie Li, Bin Yi   +5 more
doaj   +1 more source

Convolutional Neural Networks–Based Image Analysis for the Detection and Quantification of Neutrophil Extracellular Traps

Cells, 2020
Over a decade ago, the formation of neutrophil extracellular traps (NETs) was described as a novel mechanism employed by neutrophils to tackle infections.
Aneta Manda-Handzlik, Krzysztof Fiok, Adrianna Cieloch, Edyta Heropolitanska-Pliszka, Urszula Demkow   +4 more
doaj   +1 more source

SACNet: Shuffling atrous convolutional U‐Net for medical image segmentation

IET Image Processing, 2023
Medical images exhibit multi‐granularity and high obscurity along boundaries. As representative work, the U‐Net and its variants exhibit two shortcomings on medical image segmentation: (a) they expand the range of reception fields by applying addition or
Shaofan Wang, Yukun Liu, Yanfeng Sun, Baocai Yin   +3 more
doaj   +1 more source

Recent Advancements in Bulk Processing of Rare‐Earth‐Free Hard Magnetic Materials and Related Multiscale Simulations

Advanced Engineering Materials, EarlyView.
This article provides an overview of recent advancements in bulk processing of rare‐earth‐free hard magnetic materials. It also addresses related simulation approaches at different scales. The research on rare‐earth‐free magnetic materials has increased significantly in recent years, driven by supply chain issues, environmental and social concerns, and
Daniel Scheiber, Andrea Bachmaier
wiley   +1 more source

Searching for Exoplanets Using Artificial Intelligence

, 2017
In the last decade, over a million stars were monitored to detect transiting planets. Manual interpretation of potential exoplanet candidates is labor intensive and subject to human error, the results of which are difficult to quantify. Here we present a
Griffith, Caitlin A., Palafox, Leon, Pearson, Kyle A.   +2 more
core   +1 more source

Real‐time vehicle detection using segmentation‐based detection network and trajectory prediction

IET Computer Vision
The position of vehicles is determined using an algorithm that includes two stages of detection and prediction. The more the number of frames in which the detection network is used, the more accurate the detector is, and the more the prediction network ...
Nafiseh Zarei, Payman Moallem, Mohammadreza Shams   +2 more
doaj   +1 more source

Functional Materials for Environmental Energy Harvesting in Smart Agriculture via Triboelectric Nanogenerators

Advanced Functional Materials, EarlyView.
This review explores functional and responsive materials for triboelectric nanogenerators (TENGs) in sustainable smart agriculture. It examines how particulate contamination and dirt affect charge transfer and efficiency. Environmental challenges and strategies to enhance durability and responsiveness are outlined, including active functional layers ...
Rafael R. A. Silva, Giulio Fatti, Emanuel Carlos, Guilherme Ferreira, Sumita Goswami, Suman Nandy, Luiz H. C. Mattoso, Elvira Fortunato, Caio G. Otoni, Rodrigo Martins   +9 more
wiley   +1 more source

English Conversational Telephone Speech Recognition by Humans and Machines

, 2017
One of the most difficult speech recognition tasks is accurate recognition of human to human communication. Advances in deep learning over the last few years have produced major speech recognition improvements on the representative Switchboard ...
Audhkhasi, Kartik, Cui, Xiaodong, Dimitriadis, Dimitrios, Hall, Phil, Kurata, Gakuto, Lim, Lynn-Li, Picheny, Michael, Ramabhadran, Bhuvana, Roomi, Bergul, Saon, George, Sercu, Tom, Thomas, Samuel   +11 more
core   +1 more source