Results 261 to 270 of about 142,397 (310)

Gate‐Align‐SED: Semi‐Supervised Sound Event Detection via Adaptive Feature Gating and Cross‐Task Alignment in Situation Awareness

Advanced Intelligent Systems, EarlyView.
Overview of the proposed Gate‐Align‐SED, including two stages of training: (1) Mean‐Teacher SSL Training; and (2) Enhancer Model Training. In complex real‐world environments such as disaster monitoring, effective sound event detection (SED) is often hindered by the presence of noise and limited labeled data.
Jieli Chen, Li‐Minn Ang, Chee Shen Lim, Kah Phooi Seng, Jeremy Smith   +4 more
wiley   +1 more source

Profiling Co‐Occurrent Morphological Phenotypes and Their Degree of Expression Severity in Vacuolated Cells by Holo‐Tomographic Flow Cytometry and Fractal Analysis

Advanced Intelligent Systems, EarlyView.
HTFC gets 3D refractive index tomograms of flowing cells. Label‐free monocytes are engineered to express patterns of cytoplasmic vacuoles. From the tomogram, an efficient dimensionality reduction is operated. Interpretable features are extracted to classify the expression severity of phenotypes coexisting in each cell, visually represented by a seven ...
Marika Valentino, Giusy Giugliano, Daniele Pirone, Fabrizio Licitra, Fulvia Vitale, Pasquale Memmolo, Lisa Miccio, Massimo D’Agostino, Pietro Ferraro, Vittorio Bianco   +9 more
wiley   +1 more source

Short Paper: Graph Classification with Kernels, Embeddings and Convolutional Neural Networks

, 2019
Monica Golahalli Seenappa, Katerina Potika, Πέτρος Ποτίκας   +2 more
openalex   +2 more sources

ARMARecon: An ARMA Convolutional Filter based Graph Neural Network for Neurodegenerative Dementias Classification

VSS Tejaswi Abburi, Ananya Singhal, Saurabh J. Shigwan, Nitin Kumar   +3 more
openalex   +1 more source

Analysis of Irregular Spatial Data with Machine Learning: Classification of Building Patterns with a Graph Convolutional Neural Network

, 2018
Xiongfeng Yan, Tinghua Ai
openalex   +2 more sources

autoscoRA: Deep Learning to Automate Sharp/van der Heijde Scoring of Radiographic Damage in Rheumatoid Arthritis

Arthritis &Rheumatology, Accepted Article.
Objective Regular imaging by conventional radiography to assess for joint damage is a cornerstone in the management of rheumatoid arthritis (RA). Scoring systems to quantify such damage, such as the widely used Sharp/van der Heijde (SvdH) score, are limited by the requirement of time and experienced staff as well as intra‐ and inter‐rater variability ...
Thomas Deimel, Paul J. Weiser, Martin Urschler, Christian Payer, Peter Mandl, Georg Langs, Daniel Aletaha   +6 more
wiley   +1 more source

Image2Flow: A proof-of-concept hybrid image and graph convolutional neural network for rapid patient-specific pulmonary artery segmentation and CFD flow field calculation from 3D cardiac MRI data. [PDF]

PLoS Comput Biol
Yao T, Pajaziti E, Quail M, Schievano S, Steeden J, Muthurangu V.   +5 more
europepmc   +1 more source

Transfer Learning Approaches in Bioprocess Engineering: Opportunities and Challenges

Biotechnology and Bioengineering, EarlyView.
ABSTRACT Transfer learning (TL) has recently emerged as a promising approach to overcoming one of the key limitations of bioprocess engineering: data scarcity. By leveraging knowledge from one bioprocess to another, TL allows existing models and data sets to be reused efficiently, accelerating process development, improving prediction accuracy, and ...
Daniel Barón Díaz, Anna‐Lena Drommershausen, Alexander Grünberger, Dirk Holtmann   +3 more
wiley   +1 more source

Addressing Small Data Challenges in Biopharmaceutical Development and Manufacturing: A Mini Review of Multi‐Fidelity Techniques

Biotechnology and Bioengineering, EarlyView.
ABSTRACT The growing demand for biopharmaceutical products reflects their effectiveness in medical treatments. However, developing new biopharmaceuticals remains a major bottleneck, often taking up to a decade before market approval. Machine learning (ML) models have the potential to accelerate this process, but their success depends on access to large
Mohammad Golzarijalal, Uwe Aickelin, Ellen Otte   +2 more
wiley   +1 more source

Advances in causal discovery methods for ecological time series

Biological Reviews, EarlyView.
ABSTRACT Recent advances in data collection technologies (e.g. automated sensor networks, satellite remote sensing, and high‐throughput sequencing) have greatly expanded the availability of ecological time series, enabling new opportunities for causal analyses in dynamic ecosystems.
Kenta Suzuki, Masato Yamamichi, Yutaka Osada, Masayuki Ushio, Kohei Nakajima, Hiroshi Masuya, Shohei Shimizu   +6 more
wiley   +1 more source