Encoder–decoder neural networks for predicting future FTIR spectra – application to enzymatic protein hydrolysis
Sign Up to like & getrecommendations! Published in 2022 at "Journal of Biophotonics"
DOI: 10.1002/jbio.202200097
Abstract: In the process of converting food‐processing by‐products to value‐added ingredients, fine grained control of the raw materials, enzymes and process conditions ensures the best possible yield and economic return. However, when raw material batches lack… read more here.
Keywords: neural networks; encoder decoder; networks predicting; decoder neural ... See more keywords
Deep capsule encoder–decoder network for surrogate modeling and uncertainty quantification
Sign Up to like & getrecommendations! Published in 2022 at "International Journal for Numerical Methods in Engineering"
DOI: 10.1002/nme.7228
Abstract: We propose a novel capsule‐based deep encoder–decoder model for surrogate modeling and uncertainty quantification of systems in mechanics from sparse data. The proposed framework is developed by adapting Capsule Network (CapsNet) architecture into an image‐to‐image… read more here.
Keywords: capsule; network; uncertainty; encoder decoder ... See more keywords
Direct attenuation correction of brain PET images using only emission data via a deep convolutional encoder-decoder (Deep-DAC)
Sign Up to like & getrecommendations! Published in 2019 at "European Radiology"
DOI: 10.1007/s00330-019-06229-1
Abstract: To obtain attenuation-corrected PET images directly from non-attenuation-corrected images using a convolutional encoder-decoder network. Brain PET images from 129 patients were evaluated. The network was designed to map non-attenuation-corrected (NAC) images to pixel-wise continuously valued… read more here.
Keywords: pet; pet images; encoder decoder; brain pet ... See more keywords
Code generation from a graphical user interface via attention-based encoder–decoder model
Sign Up to like & getrecommendations! Published in 2022 at "Multimedia Systems"
DOI: 10.1007/s00530-021-00804-7
Abstract: Code generation from graphical user interface images is a promising area of research. Recent progress on machine learning methods made it possible to transform user interface into the code using several methods. The encoder–decoder framework… read more here.
Keywords: user interface; code generation; encoder decoder;
Encoder-decoder based convolutional neural networks for image forgery detection
Sign Up to like & getrecommendations! Published in 2021 at "Multimedia Tools and Applications"
DOI: 10.1007/s11042-020-10158-3
Abstract: Today, images editing software has greatly evolved, thanks to them that the semantic manipulation of images has become easier. On the other hand, the identification of these modifications becomes a very difficult task because the… read more here.
Keywords: based convolutional; encoder decoder; neural networks; convolutional neural ... See more keywords
Deep structured residual encoder-decoder network with a novel loss function for nuclei segmentation of kidney and breast histopathology images
Sign Up to like & getrecommendations! Published in 2022 at "Multimedia Tools and Applications"
DOI: 10.1007/s11042-021-11873-1
Abstract: To improve the process of diagnosis and treatment of cancer disease, automatic segmentation of haematoxylin and eosin (H & E) stained cell nuclei from histopathology images is the first step in digital pathology. The proposed… read more here.
Keywords: histopathology; nuclei segmentation; segmentation; encoder decoder ... See more keywords
Automated Pulmonary Fibrosis Segmentation Using a 3D Multi-Scale Convolutional Encoder-Decoder Approach in Thoracic CT for the Rhesus Macaque with Radiation-Induced Lung Damage
Sign Up to like & getrecommendations! Published in 2020 at "Journal of Signal Processing Systems"
DOI: 10.1007/s11265-020-01605-3
Abstract: To develop an automated pulmonary fibrosis (PF) segmentation methodology using a 3D multi-scale convolutional encoder-decoder approach following the robust atlas-based active volume model in thoracic CT for Rhesus Macaques with radiation-induced lung damage. 152 thoracic… read more here.
Keywords: convolutional encoder; scale convolutional; encoder decoder; segmentation ... See more keywords
Concrete roadway crack segmentation using encoder-decoder networks with range images
Sign Up to like & getrecommendations! Published in 2020 at "Automation in Construction"
DOI: 10.1016/j.autcon.2020.103403
Abstract: Abstract Recently, researchers have utilized DCNN for pixel-wise crack classification through semantic segmentation. Nevertheless, some issues in current DCNN-based roadway crack segmentation are yet to be fully addressed. For example, image pre-processing techniques are often… read more here.
Keywords: crack segmentation; methodology; encoder decoder; roadway crack ... See more keywords
Time-series forecasting of coal-fired power plant reheater metal temperatures using encoder-decoder recurrent neural networks
Sign Up to like & getrecommendations! Published in 2019 at "Energy"
DOI: 10.1016/j.energy.2019.116187
Abstract: Abstract With the increase in renewable energy penetration of electrical grids, coal power stations will be required to operate flexibly rather than functioning as baseload units. During flexible operation of conventional coal-fired stations, thermal stresses… read more here.
Keywords: plant; encoder decoder; metal temperatures; coal ... See more keywords
Data-driven forecasting with model uncertainty of utility-scale air-cooled condenser performance using ensemble encoder-decoder mixture-density recurrent neural networks
Sign Up to like & getrecommendations! Published in 2022 at "Energy"
DOI: 10.1016/j.energy.2021.122030
Abstract: Abstract In the current work, an encoder-decoder mixture-density network (MDN) is developed using recurrent neural networks (RNN) for the prediction of utility-scale air-cooled condenser backpressure. Backpressure has a direct impact on thermal power plant generated… read more here.
Keywords: model; encoder decoder; mixture density; decoder mixture ... See more keywords
DeepPET: A deep encoder–decoder network for directly solving the PET image reconstruction inverse problem
Sign Up to like & getrecommendations! Published in 2019 at "Medical Image Analysis"
DOI: 10.1016/j.media.2019.03.013
Abstract: &NA; The purpose of this research was to implement a deep learning network to overcome two of the major bottlenecks in improved image reconstruction for clinical positron emission tomography (PET). These are the lack of… read more here.
Keywords: deeppet; image; network; encoder decoder ... See more keywords