Results 51 to 60 of about 977,116 (306)
Materials & Design, 2022 The simultaneous optimization of competing properties is a challenge of machine learning based materials design. We proposed a domain knowledge constrained active learning loop for the design of high entropy alloys with optimized strength and ductility ...
Hongchao Li +5 more
doaj +1 more source
Incorporating Active Learning into Machine Learning Techniques for Sensory Evaluation of Food
International Journal of Computational Intelligence Systems, 2020 The sensory evaluation of food quality using a machine learning approach provides a means of measuring the quality of food products. Thus, this type of evaluation may assist in improving the composition of foods and encouraging the development of new ...
Nhat-Vinh Lu +3 more
doaj +1 more source
OBOE: Collaborative Filtering for AutoML Model Selection
, 2019 Algorithm selection and hyperparameter tuning remain two of the most challenging tasks in machine learning. Automated machine learning (AutoML) seeks to automate these tasks to enable widespread use of machine learning by non-experts.
Akimoto, Yuji +3 more
core +1 more source
Streaming Machine Learning and Online Active Learning for Automated Visual Inspection.
IFAC-PapersOnLine, 2022 Quality control is a key activity performed by manufacturing companies to verify product conformance to the requirements and specifications. Standardized quality control ensures that all the products are evaluated under the same criteria. The decreased cost of sensors and connectivity enabled an increasing digitalization of manufacturing and provided ...
Rožanec, Jože M. +4 more
openaire +2 more sources
Scientific Reports, 2021 Machine learning is widely applied in drug discovery research to predict molecular properties and aid in the identification of active compounds. Herein, we introduce a new approach that uses model-internal information from compound activity predictions ...
Raquel Rodríguez-Pérez +1 more
doaj +1 more source
ARO-The Scientific Journal of Koya University, 2023 Technology has dominated a huge part of human life. Furthermore, technology users use language continuously to express feelings and sentiments about things.
Soran S. Badawi
doaj +1 more source
Enzyme activity from machine learning [PDF]
Science, 2019 Enzyme Engineering Enzymes are very efficient catalysts for biochemical reactions, which are increasingly important for industrial applications. However, incomplete knowledge of the key factors that induce their catalytic properties limits our ability to engineer new enzymes with new properties. Bonk et al.
openaire +1 more source
Using human brain activity to guide machine learning [PDF]
Scientific Reports, 2018 AbstractMachine learning is a field of computer science that builds algorithms that learn. In many cases, machine learning algorithms are used to recreate a human ability like adding a caption to a photo, driving a car, or playing a game. While the human brain has long served as a source ofinspirationfor machine learning, little effort has been made to
Fong, Ruth C. +2 more
openaire +5 more sources
Liquid biopsy epigenetics: establishing a molecular profile based on cell‐free DNA
Molecular Oncology, EarlyView.Cell‐free DNA (cfDNA) fragments in plasma from cancer patients carry epigenetic signatures reflecting their cells of origin. These epigenetic features include DNA methylation, nucleosome modifications, and variations in fragmentation. This review describes the biological properties of each feature and explores optimal strategies for harnessing cfDNA ...
Christoffer Trier Maansson +2 more
wiley +1 more source
Active Learning for Dialogue Act Classification [PDF]
, 2011 Active learning techniques were employed for classification of dialogue acts over two dialogue corpora, the English human-human Switchboard corpus and the Spanish human-machine Dihana corpus.
Gambäck, Björn +2 more
core +1 more source