Results 111 to 120 of about 212,585 (307)
Artificial Intelligence for Bone: Theory, Methods, and Applications
Advanced Intelligent Discovery, EarlyView.Advances in artificial intelligence (AI) offer the potential to improve bone research. The current review explores the contributions of AI to pathological study, biomarker discovery, drug design, and clinical diagnosis and prognosis of bone diseases. We envision that AI‐driven methodologies will enable identifying novel targets for drugs discovery. The
Dongfeng Yuan +3 more
wiley +1 more source
Prediction of Multivariate Chaotic Time Series using GRU, LSTM and RNN
Sakarya University Journal of Computer and Information SciencesChaotic systems are identified as nonlinear, deterministic dynamic systems that are exhibit sensitive to initial values. Some chaotic equations modeled from daily events involve time information and generate chaotic time series that are sequential data ...
Osman Eldoğan, Gülyeter Öztürk
doaj +1 more source
, 2014 Sequence prediction and classification are ubiquitous and challenging problems in machine learning that can require identifying complex dependencies between temporally distant inputs. Recurrent Neural Networks (RNNs) have the ability, in theory, to cope with these temporal dependencies by virtue of the short-term memory implemented by their recurrent ...
Koutník, Jan +3 more
openaire +2 more sources
Deep Learning‐Assisted Design of Mechanical Metamaterials
Advanced Intelligent Discovery, EarlyView.This review examines the role of data‐driven deep learning methodologies in advancing mechanical metamaterial design, focusing on the specific methodologies, applications, challenges, and outlooks of this field. Mechanical metamaterials (MMs), characterized by their extraordinary mechanical behaviors derived from architected microstructures, have ...
Zisheng Zong +5 more
wiley +1 more source
Comparative Analysis of Data Visualization and Deep Learning Models in Air Quality Forecasting
Sakarya University Journal of Computer and Information SciencesThis study utilizes air pollution data from the Continuous Monitoring Center of the Ministry of Environment, Urbanization, and Climate Change in Turkey to predict various pollutants using three advanced deep learning approaches: LSTM (Long Short-Term ...
Bihter Daş, Damla Mengus
doaj +1 more source
Prosodic Break Prediction with RNNs
, 2016 Prosodic breaks prediction from text is a fundamental task to obtain naturalness in text to speech applications. In this work we build a data-driven break predictor out of linguistic features like the Part of Speech (POS) tags and forward-backward word distance to punctuation marks, and to do so we use a basic Recurrent Neural Network (RNN) model to ...
Pascual de la Puente, Santiago +1 more
openaire +2 more sources
Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook
Advanced Intelligent Discovery, EarlyView.Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang +4 more
wiley +1 more source
Advanced Intelligent Discovery, EarlyView.Flexible tactile sensors have considerable potential for broad application in healthcare monitoring, human–machine interfaces, and bioinspired robotics. This review explores recent progress in device design, performance optimization, and intelligent applications. It highlights how AI algorithms enhance environmental adaptability and perception accuracy
Siyuan Wang +3 more
wiley +1 more source
MultiModal Emotional Recognition by Artificial Intelligence and its Application in Psychology [PDF]
Majallah-i dānishgāh-i ̒ulūm-i pizishkī-i ArākIntroduction: Nowadays, the use of artificial intelligence and machine learning has impacted all fields of study. Utilizing these methods for identifying individuals' emotions through integrating audio, text, and image data has shown higher accuracy than
Seyed Sadegh Hosseini +1 more
doaj
An Optimized Hybrid Deep Learning Approach for Accurate Fruit Image Classification
JOIV: International Journal on Informatics VisualizationThe field of fruit classification in computer and machine vision is growing rapidly. However, numerous deep learning approaches have been introduced for image classification, but they often encounter challenges that must be addressed.
Hasanain H. Razzaq +3 more
doaj +1 more source