A novel two-enhancive aspect module in convolutional neural networks for multivariate time series classification DOI
Hong Qiu, Zhang Qia, Renfang Wang

и другие.

Expert Systems with Applications, Год журнала: 2024, Номер unknown, С. 125755 - 125755

Опубликована: Ноя. 1, 2024

Язык: Английский

Estimation of powder factor in mine blasting: feasibility of tree-based predictive models DOI Creative Commons
Danial Jahed Armaghani,

Mohammad Hayati,

Ehsan Momeni

и другие.

Multiscale and Multidisciplinary Modeling Experiments and Design, Год журнала: 2025, Номер 8(2)

Опубликована: Янв. 15, 2025

Язык: Английский

Процитировано

1

A three layer stacked multimodel transfer learning approach for deep feature extraction from Chest Radiographic images for the classification of COVID-19 DOI
Baijnath Kaushik, Akshma Chadha, Abhigya Mahajan

и другие.

Engineering Applications of Artificial Intelligence, Год журнала: 2025, Номер 147, С. 110241 - 110241

Опубликована: Фев. 25, 2025

Язык: Английский

Процитировано

1

Emotion Analysis AI Model for Sensing Architecture Using EEG DOI Creative Commons
Seungyeul Ji, Mi Kyoung Kim, Han Jong Jun

и другие.

Applied Sciences, Год журнала: 2025, Номер 15(5), С. 2742 - 2742

Опубликована: Март 4, 2025

The rapid advancement of artificial intelligence (AI) has spurred innovation across various domains—information technology, medicine, education, and the social sciences—and is likewise creating new opportunities in architecture for understanding human–environment interactions. This study aims to develop a fine-tuned AI model that leverages electroencephalography (EEG) data analyse users’ emotional states real time apply these insights architectural spaces. Specifically, SEED dataset—an EEG-based emotion recognition resource provided by BCMI laboratory at Shanghai Jiao Tong University—was employed fine-tune ChatGPT classifying three (positive, neutral, negative). Experimental results demonstrate model’s effectiveness differentiating based on EEG signals, although limited number participants confines our findings proof concept. Furthermore, assess feasibility proposed approach contexts, we integrated into 360° virtual reality (VR) setting, where it showed promise real-time adaptive design. By combining AI-driven biometric analysis with user-centred design, this foster sustainable built environments respond dynamically human emotions. underscore potential enhancing occupant experiences provide foundational future investigations human–space

Язык: Английский

Процитировано

0

Pre-transplant and transplant parameters predict long-term survival after hematopoietic cell transplantation using machine learning DOI
Panagiotis G. Asteris, Amir H. Gandomi, Danial Jahed Armaghani

и другие.

Transplant Immunology, Год журнала: 2025, Номер unknown, С. 102211 - 102211

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

0

Fine-tuning pre-trained networks with emphasis on image segmentation: A multi-network approach for enhanced breast cancer detection DOI
Parviz Ghafariasl, Masoomeh Zeinalnezhad, Shing I. Chang

и другие.

Engineering Applications of Artificial Intelligence, Год журнала: 2024, Номер 139, С. 109666 - 109666

Опубликована: Ноя. 18, 2024

Язык: Английский

Процитировано

1

A novel two-enhancive aspect module in convolutional neural networks for multivariate time series classification DOI
Hong Qiu, Zhang Qia, Renfang Wang

и другие.

Expert Systems with Applications, Год журнала: 2024, Номер unknown, С. 125755 - 125755

Опубликована: Ноя. 1, 2024

Язык: Английский

Процитировано

1