Results 51 to 60 of about 11,467,392 (329)

An Ensemble Transfer Learning Model for Detecting Stego Images

Applied Sciences, 2023
As internet traffic grows daily, so does the need to protect it. Network security protects data from unauthorized access and ensures their confidentiality and integrity.
Dina Yousif Mikhail, Roojwan Sc Hawezi, Shahab Wahhab Kareem   +2 more
doaj   +1 more source

Active learning-based machine learning approach for enhancing environmental sustainability in green building energy consumption

Scientific Reports
Green building (GB) techniques are essential for reducing energy waste in the construction sector, which accounts for almost 40% of global energy consumption. Despite their importance, challenges such as occupant behavior and energy management gaps often
Shahid Mahmood, Hua-Ping Sun, Amel Ali Alhussan, Asifa Iqbal, El-sayed M. El-kenawy   +4 more
semanticscholar   +1 more source

Machine Learning-Assisted Array Synthesis Using Active Base Element Modeling

IEEE Transactions on Antennas and Propagation, 2021
Array synthesis under practical constraints is a vital design task. Traditional array synthesis methods usually deal with isolated antenna elements without considering mutual coupling (MC) or mounting-platform effects, which results in unacceptable ...
Qi Wu, Weiqi Chen, Chen Yu, Haiming Wang, W. Hong   +4 more
semanticscholar   +1 more source

A Review of Causality for Learning Algorithms in Medical Image Analysis

, 2022
Medical image analysis is a vibrant research area that offers doctors and medical practitioners invaluable insight and the ability to accurately diagnose and monitor disease. Machine learning provides an additional boost for this area.
Vlontzos, Athanasios, Kainz, Bernhard, Rueckert, Daniel   +2 more
core   +1 more source

Modelling stem cell differentiation related processes—A practical overview for biologists

FEBS Letters, EarlyView.
Stem cell differentiation is complex and difficult to control experimentally. This review introduces suitable computational modelling approaches that can support stem cell research, from mechanistic ODE and abstract models to multiscale and deep learning methods.
Ricco Zeegelaar, Xinqi Yan, Lucas F. Jansen Klomp, Stefano Schivo, Janine N. Post   +4 more
wiley   +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, Roengchai Tansuchat, Takaya Yuizono, Van-Nam Huynh   +3 more
doaj   +1 more source

Data efficient machine learning potentials for modeling catalytic reactivity via active learning and enhanced sampling

npj Computational Materials
Simulating catalytic reactivity under operative conditions poses a significant challenge due to the dynamic nature of the catalysts and the high computational cost of electronic structure calculations. Machine learning potentials offer a promising avenue
S. Perego, L. Bonati
semanticscholar   +1 more source

Reconstructing enzyme evolution by protein engineering

FEBS Letters, EarlyView.
Natural enzyme evolution can be retraced by protein engineering methods such as directed evolution, rational design, and ancestral sequence reconstruction. These approaches reveal how enzymes emerged from ligand‐binding scaffolds, developed varying substrate preferences, formed oligomeric complexes, adapted to environmental changes, and evolved novel ...
Lukas Drexler, Markus R. Busch, Reinhard Sterner   +2 more
wiley   +1 more source

Active learning and autonomous learning: an educational experience [PDF]

, 2009
The obtained experience in the active and the autonomous learning tasks execution in the teaching of the subject: Reinforced Concrete Structures and Devices Construction, of the career of Technical Architecture by the Universidad Politécnica de ...
Gómez Soberón, José Manuel Vicente, Gómez Soberón, M. Consolació, Gómez Soberón, Alberto   +2 more
core   +1 more source

Data leakage detection in machine learning code: transfer learning, active learning, or low-shot prompting? [PDF]

PeerJ Computer Science
With the increasing reliance on machine learning (ML) across diverse disciplines, ML code has been subject to a number of issues that impact its quality, such as lack of documentation, algorithmic biases, overfitting, lack of reproducibility, inadequate ...
Nouf Alturayeif, Jameleddine Hassine
doaj   +2 more sources