A Geometric Theory for Binary Classification of Finite Datasets by DNNs with Relu Activations
Sign Up to like & getrecommendations! Published in 2024 at "Neural Processing Letters"
DOI: 10.1007/s11063-024-11612-1
Abstract: In this paper we investigate deep neural networks for binary classification of datasets from geometric perspective in order to understand the working mechanism of deep neural networks. First, we establish a geometrical result on injectivity… read more here.
Keywords: classification; geometric theory; hidden layers; theory binary ... See more keywords
Prediction of influencing atmospheric conditions for explosion Avoidance in fireworks manufacturing Industry-A network approach.
Sign Up to like & getrecommendations! Published in 2022 at "Environmental pollution"
DOI: 10.1016/j.envpol.2022.119182
Abstract: This research study uses Artificial Neural Networks (ANNs) to predict occupational accidents in Sivakasi firework industries. Atmospheric temperature, pressure and humidity are the causes of explosion during chemical mixing, drying, and pellet making. The Proposed… read more here.
Keywords: hidden layers; atmospheric conditions; prediction; model ... See more keywords
Sex estimation using sternum part lenghts by means of artificial neural networks.
Sign Up to like & getrecommendations! Published in 2019 at "Forensic science international"
DOI: 10.1016/j.forsciint.2019.05.011
Abstract: In addition to the pelvis, cranium and phalanges, the sternum is also used for postmortem sex identification. Bone measurements may be obtained on cadaveric bones. Alternatively, computerized tomography may be used to obtain measurements close… read more here.
Keywords: neural networks; artificial neural; xpl; estimation ... See more keywords
Whole Process Monitoring Based on Unstable Neuron Output Information in Hidden Layers of Deep Belief Network
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Transactions on Cybernetics"
DOI: 10.1109/tcyb.2019.2948202
Abstract: Process monitoring based on deep learning has attracted considerable attention. Generally, several hidden layers exist in the deep-learning model, and only the output information of the last hidden layer neurons extracted by deep learning is… read more here.
Keywords: process monitoring; process; output; hidden layers ... See more keywords
Using Machine Learning for Climate Modelling: Application of Neural Networks to a Slow-Fast Chaotic Dynamical System as a Case Study
Sign Up to like & getrecommendations! Published in 2024 at "Climate"
DOI: 10.3390/cli12110189
Abstract: This paper explores the capabilities of two types of recurrent neural networks, unidirectional and bidirectional long short-term memory networks, to build a surrogate model for a coupled fast–slow dynamic system and predicting its nonlinear chaotic… read more here.
Keywords: system; time; dynamical system; climate ... See more keywords
A Conceptual Exploration of Hidden Spatial Layers: Reading Urban-Breccia
Sign Up to like & getrecommendations! Published in 2024 at "Sustainability"
DOI: 10.3390/su16041625
Abstract: Sustainable urban spaces, from social and cultural perspectives, can be characterized not only by the preservation of the historical cultural structures within them but also by the subjective and collective meanings contributed by the individuals… read more here.
Keywords: visible hidden; hidden layers; breccia; urban breccia ... See more keywords