DNRLCNN: A CNN Framework for Identifying MiRNA-Disease Associations Using Latent Feature Matrix Extraction with Positive Samples.
Sign Up to like & getrecommendations! Published in 2022 at "Interdisciplinary sciences, computational life sciences"
DOI: 10.1007/s12539-022-00509-z
Abstract: Emerging evidence indicates that miRNAs have strong relationships with many human diseases. Investigating the associations will contribute to elucidating the activities of miRNAs and pathogenesis mechanisms, and providing new opportunities for disease diagnosis and drug… read more here.
Keywords: positive samples; latent feature; mirna disease; feature ... See more keywords
Direct Video Frame Interpolation With Multiple Latent Encoders
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Access"
DOI: 10.1109/access.2021.3053695
Abstract: We present a simple but effective video interpolation framework that can be applied to various types of videos including conventional videos and 360° videos. Our main idea is to predict the latent feature of an… read more here.
Keywords: video; frame; latent feature; proposed method ... See more keywords
Direct Edge-to-Edge Many-to-Many Latent Feature Transfer Learning
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2021.3117991
Abstract: Smart cameras that leverage edge-computing (edge cameras) are increasingly being combined with deep neural networks to realize the Artificial Intelligence of Things (AIoT), enabling a smart life with “low-touch services,” such as unmanned stores. However,… read more here.
Keywords: transfer; latent feature; transfer learning; edge edge ... See more keywords
Sample Latent Feature-Associated Low-Rank Subspace Clustering for Hyperspectral Band Selection
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"
DOI: 10.1109/jstars.2024.3435846
Abstract: In recent years, subspace clustering has become increasingly popular and achieved great success in band selection (BS) of hyperspectral imagery. However, current subspace clustering approaches are mostly insufficient in capturing the fine spatial structure and… read more here.
Keywords: band selection; subspace clustering; latent feature; band ... See more keywords
MMLF: Multi-Metric Latent Feature Analysis for High-Dimensional and Incomplete Data
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Transactions on Services Computing"
DOI: 10.1109/tsc.2023.3331570
Abstract: High-dimensional and incomplete (HDI) data are omnipresent in a variety of Big Data-related applications. Latent feature analysis (LFA) is a typical representation learning method that can extract useful yet latent knowledge from HDI data via… read more here.
Keywords: latent feature; dimensional incomplete; hdi; high dimensional ... See more keywords