Results 31 to 40 of about 1,248,762 (236)

BIM, machine learning and computer vision techniques in underground construction: Current status and future perspectives

, 2020
The architecture, engineering and construction (AEC) industry is experiencing a technological revolution driven by booming digitisation and automation.
M. Huang, J. Ninić, Qianbing Zhang
semanticscholar   +1 more source

A review of molecular representation in the age of machine learning

WIREs Computational Molecular Science, 2022
Research in chemistry increasingly requires interdisciplinary work prompted by, among other things, advances in computing, machine learning, and artificial intelligence.
Daniel S. Wigh, J. Goodman, A. Lapkin
semanticscholar   +1 more source

Gut microbiome and aging—A dynamic interplay of microbes, metabolites, and the immune system

FEBS Letters, EarlyView.
Age‐dependent shifts in microbial communities engender shifts in microbial metabolite profiles. These in turn drive shifts in barrier surface permeability of the gut and brain and induce immune activation. When paired with preexisting age‐related chronic inflammation this increases the risk of neuroinflammation and neurodegenerative diseases.
Aaron Mehl, Eran Blacher
wiley   +1 more source

An empirical analysis of machine learning frameworks for digital pathology in medical science

Journal of Physics: Conference Series, 2021
Digital pathology is a technology that allows pathological information created from a digital slide to be accessed, handled, and interpreted. Using optical pathology scanners, glass slides are collected and transformed to digitized glass slides that can ...
S.K.B. Sangeetha, R. Dhaya, D. Shah, R. Dharanidharan, K. S. S. Reddy   +4 more
semanticscholar   +1 more source

AAA+ protein unfoldases—the Moirai of the proteome

FEBS Letters, EarlyView.
AAA+ unfoldases are essential molecular motors that power protein degradation and disaggregation. This review integrates recent cryo‐electron microscopy (cryo‐EM) structures and single‐molecule biophysical data to reconcile competing models of substrate translocation.
Stavros Azinas, Marta Carroni
wiley   +1 more source

A Review of Machine Learning and Deep Learning for Object Detection, Semantic Segmentation, and Human Action Recognition in Machine and Robotic Vision

Technologies
Machine vision, an interdisciplinary field that aims to replicate human visual perception in computers, has experienced rapid progress and significant contributions.
Nikoleta Manakitsa, George S. Maraslidis, L. Moysis, G. Fragulis   +3 more
semanticscholar   +1 more source

Subtype‐specific enhancer RNAs define transcriptional regulators and prognosis in breast cancers

Molecular Oncology, EarlyView.
This study employed machine learning methodologies to perform the subtype‐specific classification of RNA‐seq data sets, which are mapped on enhancers from TCGA‐derived breast cancer patients. Their integration with gene expression (referred to as ProxCReAM eRNAs) and chromatin accessibility profiles has the potential to identify lineage‐specific and ...
Aamena Y. Patel, Peyman Zarrineh, Nathnael T. Tuffa, Jigar H. Sheth, Sumitra Mohan, Mudassar Iqbal, Sankari Nagarajan   +6 more
wiley   +1 more source

MLnet report: training in Europe on machine learning [PDF]

, 1999
Machine learning techniques offer opportunities for a variety of applications and the theory of machine learning investigates problems that are of interest for other fields of computer science (e.g., complexity theory, logic programming, pattern ...
Ellebrecht, Mario, Morik, Katharina
core  

Exploiting the structure effectively and efficiently in low rank matrix recovery

, 2018
Low rank model arises from a wide range of applications, including machine learning, signal processing, computer algebra, computer vision, and imaging science.
Absil, Agarwal, Ahmed, Alter, Amelunxen, Beck, Blanchard, Blumensath, Boumal, Boyd, Bunk, Cai, Cai, Cai, Cai, Cai, Cai, Candes, Candes, Candes, Candes, Candes, Candès, Candès, Candès, Candès, Carmon, Chandrasekaran, Chen, Chen, Chen, Chen, Chen, Chen, Chen, Chen, Chen, Combettes, Davenport, Davenport, Ding, Donoho, Fazel, Ge, Ge, Ge, Goldberg, Gross, Hardt, Harrison, Huang, Jaggi, Jain, Jain, Ji, Jin, Keshavan, Kim, Kliesch, Koltchinskii, Krim, Kueng, Lanman, Li, Li, Lin, Ling, Ling, Liu, Liu, Lustig, Ma, Miao, Mishra, Mishra, Mishra, Mobahi, Mu, Negahban, Netrapalli, Ngo, Potter, Qu, Recht, Recht, Schermelleh, Srebro, Strohmer, Sun, Sun, Tanner, Tanner, Tao, Tharrault, Toh, Toh, Tomasi, Tu, Vandereycken, Wang, Wei, Wei, Wei, Wen, WenHuang, Xu, Yi, Zhang, Zhang, Zheng   +109 more
core   +2 more sources

Performance Evaluation of Quantum-Based Machine Learning Algorithms for Cardiac Arrhythmia Classification

Diagnostics, 2023
The electrocardiogram (ECG) is the most common technique used to diagnose heart diseases. The electrical signals produced by the heart are recorded by chest electrodes and by the extremity electrodes placed on the limbs. Many diseases, such as arrhythmia,
Zeynep Ozpolat, M. Karabatak
semanticscholar   +1 more source