AIMC Topic: Neural Networks, Computer

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Exactly conservative physics-informed neural networks and deep operator networks for dynamical systems.

Neural networks : the official journal of the International Neural Network Society
We introduce a method for training exactly conservative physics-informed neural networks and physics-informed deep operator networks for dynamical systems, that is, for ordinary differential equations. The method employs a projection-based technique ...

Exploring better sparsely annotated shadow detection.

Neural networks : the official journal of the International Neural Network Society
Sparsely annotated image segmentation has attracted increasing attention due to its low labeling cost. However, existing weakly-supervised shadow detection methods require complex training procedures, and there is still a significant performance gap ...

Personalized multi-head self-attention network for news recommendation.

Neural networks : the official journal of the International Neural Network Society
With the rapid explosion of online news and user population, personalized news recommender systems have proved to be efficient ways of alleviating information overload problems by suggesting information which attracts users in line with their tastes....

Enhancing Arabidopsis thaliana ubiquitination site prediction through knowledge distillation and natural language processing.

Methods (San Diego, Calif.)
Protein ubiquitination is a critical post-translational modification (PTM) involved in diverse biological processes and plays a pivotal role in regulating physiological mechanisms and disease states. Despite various efforts to develop ubiquitination ...

Tackling APOE's structural challenges via in silico modeling in the era of neural networks: Can AlphaFold II help circumvent the problem of lacking full-length protein structure?

Archives of biochemistry and biophysics
The APOE gene, encoding apolipoprotein E, is a predictor of longevity and age-related diseases. Despite numerous genetic studies, the data on molecular mechanisms by which apolipoprotein E affects the human phenotype remain incomplete due to the stru...

IMU Airtime Detection in Snowboard Halfpipe: U-Net Deep Learning Approach Outperforms Traditional Threshold Algorithms.

Sensors (Basel, Switzerland)
Airtime is crucial for high-rotation tricks in snowboard halfpipe performance, significantly impacting trick difficulty, the primary judging criterion. This study aims to enhance the detection of take-off and landing events using inertial measurement...

Calibration of discrete meta-parameters of bamboo flour based on magnitude analysis and BP neural network.

PloS one
In the research and development of technology and equipment for bamboo products deep processing, such as filling, drying, and medicinal use of bamboo flour (BF), the poor compaction and fluidity of BF materials entails the need for accurate discrete ...

Searching Discriminative Regions for Convolutional Neural Networks in Fundus Image Classification With Genetic Algorithms.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Deep convolutional neural networks (CNNs) have been widely used for fundus image classification and have achieved very impressive performance. However, the explainability of CNNs is poor because of their black-box nature, which limits their applicati...

Transfer Learning With Active Sampling for Rapid Training and Calibration in BCI-P300 Across Health States and Multi-Centre Data.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Machine learning and deep learning advancements have boosted Brain-Computer Interface (BCI) performance, but their wide-scale applicability is limited due to factors like individual health, hardware variations, and cultural differences affecting neur...

Structure preservation constraints for unsupervised domain adaptation intracranial vessel segmentation.

Medical & biological engineering & computing
Unsupervised domain adaptation (UDA) has received interest as a means to alleviate the burden of data annotation. Nevertheless, existing UDA segmentation methods exhibit performance degradation in fine intracranial vessel segmentation tasks due to th...