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High-efficacy and affordable hyperspectral pancreatic tissue image analysis using near-infrared spectroscopy. [PDF]
J Pathol InformTang Z +10 more
europepmc +1 more source
Deep Learning-Based 3D Reconstruction for Defect Detection in Shipbuilding Sub-Assemblies. [PDF]
Sensors (Basel)Arcano-Bea P +5 more
europepmc +1 more source
Guest Editorial: Computational Intelligence in Dynamic and Uncertain Environments
CAAI Transactions on Intelligence Technology, EarlyView.
Shouyong Jiang
wiley +1 more source
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2020
The study of psychiatric and neurologic disorders typically involves the acquisition of a wide range of different types of data, such as brain images, electronic health records, and mobile phone sensors data. Each type of data has its unique temporal and spatial characteristics, and the process of extracting useful information from them can be very ...
Lopez Pinaya, Walter Hugo +3 more
+5 more sources
The study of psychiatric and neurologic disorders typically involves the acquisition of a wide range of different types of data, such as brain images, electronic health records, and mobile phone sensors data. Each type of data has its unique temporal and spatial characteristics, and the process of extracting useful information from them can be very ...
Lopez Pinaya, Walter Hugo +3 more
+5 more sources
Geometry Regularized Autoencoders
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023A fundamental task in data exploration is to extract low dimensional representations that capture intrinsic geometry in data, especially for faithfully visualizing data in two or three dimensions. Common approaches use kernel methods for manifold learning.
Andres F. Duque +3 more
openaire +2 more sources
Autoencoder in Autoencoder Networks
IEEE Transactions on Neural Networks and Learning SystemsModeling complex correlations on multiview data is still challenging, especially for high-dimensional features with possible noise. To address this issue, we propose a novel unsupervised multiview representation learning (UMRL) algorithm, termed autoencoder in autoencoder networks (AE2-Nets).
Changqing Zhang +5 more
openaire +2 more sources
AE2-Nets: Autoencoder in Autoencoder Networks
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019Learning on data represented with multiple views (e.g., multiple types of descriptors or modalities) is a rapidly growing direction in machine learning and computer vision. Although effectiveness achieved, most existing algorithms usually focus on classification or clustering tasks.
Changqing Zhang, Yeqing Liu, Huazhu Fu
openaire +1 more source
Variational Autoencoders Versus Denoising Autoencoders for Recommendations
2021Recommender systems help users explore new content such as music and news by showing them what they will find potentially interesting. There are many methods and algorithms that can help recommender systems create personalized recommendations.
Khadija Bennouna +4 more
openaire +1 more source