An effective deep learning model for grading abnormalities in retinal fundus images using variational auto‐encoders
Sign Up to like & getrecommendations! Published in 2022 at "International Journal of Imaging Systems and Technology"
DOI: 10.1002/ima.22785
Abstract: Diabetic retinopathy (DR) and Diabetic Macular Edema (DME) are severe diseases that affect the eyes due to damage in blood vessels. Computer‐aided automated grading will help clinicians conduct disease diagnoses at ease. Experiments of automated… read more here.
Keywords: learning model; abnormalities retinal; images using; deep learning ... See more keywords
Structural damage identification based on unsupervised feature-extraction via Variational Auto-encoder
Sign Up to like & getrecommendations! Published in 2020 at "Measurement"
DOI: 10.1016/j.measurement.2020.107811
Abstract: Abstract Structural health monitoring (SHM) is a practical tool for assessing the safety and system performance of existing structures. And structural damage identification has become the core of a SHM system. However, how to extract… read more here.
Keywords: structural damage; damage identification; auto encoder; variational auto ... See more keywords
Decoding regulatory structures and features from epigenomics profiles: a Roadmap-ENCODE Variational Auto-Encoder (RE-VAE) model.
Sign Up to like & getrecommendations! Published in 2019 at "Methods"
DOI: 10.1016/j.ymeth.2019.10.012
Abstract: The development of chromatin immunoprecipitation (ChIP) with massively parallel DNA sequencing (ChIP-seq) technologies has promoted generation of large-scale epigenomics data, providing us unprecedented opportunities to explore the landscape of epigenomic profiles at scales across both… read more here.
Keywords: histone marks; auto encoder; variational auto; vae model ... See more keywords
scVAE: variational auto-encoders for single-cell gene expression data
Sign Up to like & getrecommendations! Published in 2020 at "Bioinformatics"
DOI: 10.1093/bioinformatics/btaa293
Abstract: MOTIVATION Models for analysing and making relevant biological inferences from massive amounts of complex single-cell transcriptomic data typically require several individual data-processing steps, each with their own set of hyperparameter choices. With deep generative models… read more here.
Keywords: single cell; gene expression; variational auto; auto encoders ... See more keywords
Using a Vertical-Stream Variational Auto-Encoder to Generate Segment-Based Images and Its Biological Plausibility for Modelling the Visual Pathways
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2018.2885006
Abstract: Human beings have a strong capability to identify objects in different viewpoints. Unlike computer vision that requires sufficient training samples in various scales and rotations, biological visual systems can efficiently recognize objects in diverse spatial… read more here.
Keywords: stream variational; segment based; variational auto; auto encoder ... See more keywords
Temporal Variational Auto-Encoders for Semi-Supervised Remaining Useful Life and Fault Diagnosis
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3174860
Abstract: Deep Learning has seen an incredible popularity surge in recent years mostly due to the state-of-the-art results obtained by neural networks. Nevertheless, within the Prognostics and Health Management community, even though its application in research… read more here.
Keywords: auto encoders; useful life; semi supervised; remaining useful ... See more keywords
Self-Supervised Variational Auto-Encoders
Sign Up to like & getrecommendations! Published in 2021 at "Entropy"
DOI: 10.3390/e23060747
Abstract: Density estimation, compression, and data generation are crucial tasks in artificial intelligence. Variational Auto-Encoders (VAEs) constitute a single framework to achieve these goals. Here, we present a novel class of generative models, called self-supervised Variational… read more here.
Keywords: variational auto; auto encoders; self supervised; supervised variational ... See more keywords
Using EfficientNet-B7 (CNN), Variational Auto Encoder (VAE) and Siamese Twins’ Networks to Evaluate Human Exercises as Super Objects in a TSSCI Images
Sign Up to like & getrecommendations! Published in 2023 at "Journal of Personalized Medicine"
DOI: 10.3390/jpm13050874
Abstract: In this article, we introduce a new approach to human movement by defining the movement as a static super object represented by a single two-dimensional image. The described method is applicable in remote healthcare applications,… read more here.
Keywords: auto encoder; encoder vae; super objects; variational auto ... See more keywords