#DeepNeuralNetwork
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seismosocam.bsky.social
In a new #SRL paper, scientists address challenges associated with single-station, three-component seismic localization using a #DeepNeuralNetwork based approach. ⚒️
Single‐Station Three‐Component Seismic Event Localization Using Deep Neural Networks | Seismological Research Letters | GeoScienceWorld
Abstract. Single‐station seismic localization technology enables accurate earthquake location using merely three‐component waveform data from a single
buff.ly
July 3, 2026 at 9:01 PM
currentmedscience.bsky.social
Development of a #DeepNeuralNetwork that significantly outperformed multiple #MachineLearning and #DeepLearning models in diagnosing #ParkinsonsDisease from handwritten spiral and wave images, achieving higher accuracy, sensitivity, and specificity.

Read: doi.org/10.1007/s115...
Deep Learning-Based Diagnostic Model for Parkinson's Disease Using Handwritten Spiral and Wave Images
December 18, 2025 at 6:19 AM
currentmedscience.bsky.social
Scientists developed a #DeepNeuralNetwork model that significantly improves the accuracy of #ParkinsonsDisease diagnosis using handwritten spiral and wave images, outperforming several #MachineLearning and #DeepLearning models. #medsky

Read: link.springer.com/article/10.1...
July 19, 2025 at 2:01 PM
iucrj.iucr.org
Titouan Simonnet et al.: Phase quantification using deep neural network processing of XRD patterns ##CompositeMaterials##ComputationalModeling##DeepNeuralNetwork... ##IUCrhttps://journals.iucr.org/paper?S2052252524006766
Phase quantification using deep neural network processing of XRD patterns
A deep neural network approach to the identification and quantification of powder X-ray diffraction patterns was applied and proved successful for the quantitative description of complex mineralogical assemblages consisting of up to four minerals with different structures, including different space groups, for which data augmentation is not straightforward.
journals.iucr.org
August 13, 2024 at 12:00 AM
lmssolution.bsky.social
Deep neural networks detect and classify faults in power systems efficiently.
zurl.co/CGHQ6
#DeepNeuralNetwork #FaultDetection #PowerSystems #MATLAB #Simulation #MachineLearning #ElectricalEngineering #ControlSystems #EnergyManagement
Deep Neural Network-Based Fault Detection and Classification in Power System | DNN | Fault Detection
Deep Neural Network-Based Fault Detection and Classification in Power System============================================================Join this channel to ...
www.youtube.com
May 28, 2025 at 2:30 AM
lmssolution.bsky.social
Deep neural networks detect and classify faults in power systems efficiently.
zurl.co/29y8z
#DeepNeuralNetwork #FaultDetection #PowerSystems #MATLAB #Simulation #MachineLearning #ElectricalEngineering #ControlSystems #EnergyManagement
Deep Neural Network-Based Fault Detection and Classification in Power System | DNN | Fault Detection
Deep Neural Network-Based Fault Detection and Classification in Power System============================================================Join this channel to ...
www.youtube.com
March 22, 2025 at 2:30 AM
proceedingsieee.bsky.social
Optimizing #deepneuralnetwork is still a challenge, especially on devices with limited resources. This article categorizes and compares various #numbersystems, highlighting how their utilization impacts deep neural network performance and hardware design. bit.ly/3UIeKFr
August 9, 2025 at 11:35 PM
audioxpress.bsky.social
GN Introduces Their Most Advanced Hearing Aid with Dedicated DNN Chip

The new AI powered hearing aids expand GN’s range of Bluetooth LE Audio and Auracast-enabled solutions.
#speechintelligibility #artificialintelligence #deepneuralnetwork
GN Introduces Their Most Advanced Hearing Aid with Dedicated DNN Chip
GN, the Danish manufacturer of prescription and over-the-counter hearing aids, announced their new flagship model ReSound Vivia, powered by a dedicated Deep Neural Network (DNN) chip trained on 13.5 m...
audioxpress.com
February 4, 2025 at 12:40 PM
maximilianpichler.bsky.social
In our new preprint, “Inferring processes within dynamic forest models using hybrid modeling” @ykaber.bsky.social and I present a new hybrid modeling approach for jointly calibrating a DVM with embedded #deepneuralnetwork arxiv.org/abs/2508.01228 1/4
#deeplearning #forestdynamics
August 11, 2025 at 9:02 AM