Results 41 to 50 of about 144,445 (263)

Sensory-memory interactions via modular structure explain errors in visual working memory

eLife
Errors in stimulus estimation reveal how stimulus representation changes during cognitive processes. Repulsive bias and minimum variance observed near cardinal axes are well-known error patterns typically associated with visual orientation perception ...
Jun Yang, Hanqi Zhang, Sukbin Lim
doaj   +1 more source

Deep learning for mean field optimal transport* [PDF]

ESAIM: Proceedings and Surveys
Mean field control (MFC) problems have been introduced to study social optima in very large populations of strategic agents. The main idea is to consider an infinite population and to simplify the analysis by using a mean field approximation.
Baudelet Sebastian, Frénais Brieuc, Laurière Mathieu, Machtalay Amal, Zhu Yuchen   +4 more
doaj   +1 more source

Application of Artificial Intelligence Automatic Diatom Identification System in Practical Cases [PDF]

Fayixue Zazhi, 2020
Objective To discuss the application of artificial intelligence automatic diatom identification system in practical cases, to provide reference for quantitative diatom analysis using the system and to validate the deep learning model incorporated into ...
ZHOU Yuan-yuan, CAO Yong-jie, YANG Yue, et al
doaj   +1 more source

Synthesis of electric vehicle charging data: A real-world data-driven approach

Communications in Transportation Research
Nowadays, electric vehicles (EVs) are increasingly equipped with advanced onboard devices capable of collecting and recording real-time charging data.
Zhi Li, Zilin Bian, Zhibin Chen, Kaan Ozbay, Minghui Zhong   +4 more
doaj   +1 more source

A dataset to test AI on forensic scenes [PDF]

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
The aim of this article is to describe a dataset derived from crime scenes or fictitious accidents that can be used for artificial intelligence processing. The steps involved in setting up these forensic scenes, the data acquisition chain, classification
H. Daudigny, H. Daudigny, P. Grussenmeyer   +2 more
doaj   +1 more source

Has the Future Started? The Current Growth of Artificial Intelligence, Machine Learning, and Deep Learning

Iraqi Journal for Computer Science and Mathematics, 2022
In the modern era, many terms related to artificial intelligence, machine learning, and deep learning are widely used in domains such as business, healthcare, industries, and military.
Karan Aggarwal, Maad M. Mijwil, Sonia, Abdel-Hameed Al-Mistarehi, Safwan Alomari, Murat Gök, Anas M. Zein Alaabdin, Safaa H. Abdulrhman   +7 more
doaj   +1 more source

Artificial Intelligence, Radiomics, and Deep Learning in Neuro-Oncology [PDF]

Neuro-Oncology Advances, 2020
Besides the histomolecular evaluation of tissue samples obtained from resection or biopsy, neuroimaging forms the basis for the diagnosis of brain cancer. Contrast-enhanced MRI is the method of choice for brain tumor diagnostics, treatment planning, and follow-up.
Galldiks, Norbert, Zadeh, Gelareh, Lohmann, Philipp   +2 more
openaire   +3 more sources

Risk Prediction Models for Recurrence After Curative Treatment of Early‐Stage or Locally Advanced Lung Cancer: A Systematic Review

Aging and Cancer, EarlyView.
This systematic review synthesizes prognostic models for survival and recurrence in resected non‐small cell lung cancer. While many models demonstrate moderate to good discrimination, few are externally validated and reporting quality is variable, limiting clinical applicability and highlighting the need for robust, transparent model development ...
Evangeline Samuel, S. Tissera, E. Paul, J. Zalcberg, R. G. Stirling   +4 more
wiley   +1 more source

Intelligent Tutoring Systems for Adult Learning in STEM Disciplines

New Directions for Adult and Continuing Education, EarlyView.
ABSTRACT Intelligent tutoring systems (ITS) are reshaping adult learning in STEM by providing adaptive, data‐driven instruction across classrooms, workplaces, and informal environments. In the context of ITS, this article compares generative AI, which creates personalized explanations and practice materials, with explainable AI, which focuses on ...
Jill Zarestky, Amanda R. Lager Gleason
wiley   +1 more source

Artificial intelligence, machine learning, and deep learning in liver transplantation

Journal of Hepatology, 2023
Liver transplantation (LT) is a life-saving treatment for individuals with end-stage liver disease. The management of LT recipients is complex, predominantly because of the need to consider demographic, clinical, laboratory, pathology, imaging, and omics data in the development of an appropriate treatment plan.
Mamatha Bhat, Madhumitha Rabindranath, Beatriz Sordi Chara, Douglas A. Simonetto   +3 more
openaire   +2 more sources