Results 51 to 60 of about 7,207 (210)

Retinal Vessel Segmentation: A Comprehensive Review From Classical Methods to Deep Learning Advances (1982–2025)

Advanced Intelligent Systems, EarlyView.
Four decades of retinal vessel segmentation research (1982–2025) are synthesized, spanning classical image processing, machine learning, and deep learning paradigms. A meta‐analysis of 428 studies establishes a unified taxonomy and highlights performance trends, generalization capabilities, and clinical relevance.
Avinash Bansal, Jan Kubíček, Jana Bahrová, Alice Varyšová, Martin Augustýnek, Marek Penhaker, Juraj Timkovič   +6 more
wiley   +1 more source

Multimodal Image Guidance in Subthalamic Deep Brain Stimulation for Parkinson's Disease

Annals of Neurology, EarlyView.
Objective Accurate electrode placement and individual stimulation parameters influence the outcomes of subthalamic deep brain stimulation in Parkinson's disease. Neuroimaging‐based models can help evaluate how electrode placement impacts improvement, aiming to reduce the burden of programming.
Patricia Zvarova, Christina van der Linden, Ningfei Li, Konstantin Butenko, Thea Berger, Garance M. Meyer, Ilkem Aysu Sahin, Lukas L. Goede, Bahne H. Bahners, Barbara Hollunder, Till A. Dembek, Andrew R. Pines, Martin Reich, Jens Volkmann, Vincent J. J. Odekerken, Rob M. A. de Bie, Xin Xu, Zhipei Ling, Chen Yao, Andrea A. Kühn, Surjo R. Soekadar, Kerstin Ritter, Michael T. Barbe, Veerle Visser‐Vandewalle, Michael D. Fox, Jan Niklas Petry‐Schmelzer, Nanditha Rajamani, Andreas Horn   +27 more
wiley   +1 more source

Harnessing Generative AI for Sustainable Supply Chains: Lean, Circular and Green Perspectives

Business Strategy and the Environment, EarlyView.
ABSTRACT Generative artificial intelligence is playing a significant role in the transformation of digital ecosystems by reinventing the processes of content generation, process automation, product innovation and customer experience. At the same time that these technologies are becoming more integrated into routine operations, the focus has shifted to ...
Ashutosh Singh, Rsha Alghafes, Judit Petra Koltai, Sushant Kumar Vishnoi   +3 more
wiley   +1 more source

Machine learning‐assisted clone selection for intensified cell culture processes

Biotechnology Progress, EarlyView.
Abstract Intensified fed‐batch processes are becoming increasingly prevalent among biomanufacturers due to their superior space–time yields relative to traditional, non‐intensified fed‐batch processes. However, the shift towards intensified manufacturing has unexpectedly made optimal clone selection more challenging.
Nicolas Wolnick, John Schmitt, Christian Siltanen, Julia Armstrong, Shannon Hendrick, Ariel Atchley, Brandon Downey   +6 more
wiley   +1 more source

Efficient Implementation Of Gmm Based Speaker Verification Using Sorted Gaussian Mixture Model

, 2006
Publication in the conference proceedings of EUSIPCO, Florence, Italy ...
Hamid Reza Sadegh Mohammadi, Rahim Saeidi   +1 more
openaire   +3 more sources

DinoFlow: Self‐supervised pretraining in flow cytometry enables accurate detection of common hematopathological disorders

Cytometry Part B: Clinical Cytometry, EarlyView.
Abstract Flow cytometry is an essential component of routine hematological lab testing. Many computational methods have been proposed for the analysis of flow cytometry data, but most have focused on supervised learning for just one or a few specific disorders.
Brendan O'Fallon, Muir Morrison, Mattia Medina Grespan, Nicholas C. Spies, David P. Ng   +4 more
wiley   +1 more source

FLARE-GMM: an automatic aerosol typing model based on Mie–Raman–fluorescence lidar measurements with LILAS [PDF]

Atmospheric Measurement Techniques
This study presents the development of an automated aerosol typing model utilizing Mie–Raman–fluorescence lidar data collected by LILAS (Lille Lidar for Atmospheric Study), located on the ATOLL (ATmospheric Observations at LiLLe) platform in Lille ...
R. Miri, O. Pujol, Q. Hu, P. Goloub, I. Veselovskii, I. Veselovskii, T. Podvin, F. Ducos   +7 more
doaj   +1 more source

AI‐based localization of the epileptogenic zone using intracranial EEG

Epilepsia Open, EarlyView.
Abstract Artificial intelligence (AI) is rapidly transforming our lives. Machine learning (ML) enables computers to learn from data and make decisions without explicit instructions. Deep learning (DL), a subset of ML, uses multiple layers of neural networks to recognize complex patterns in large datasets through end‐to‐end learning.
Atsuro Daida, Yipeng Zhang, Sotaro Kanai, Richard Staba, Vwani Roychowdhury, Hiroki Nariai   +5 more
wiley   +1 more source

An Electromyographic‐Based Control Using Gaussian Mixture Model on an Upper‐Limb Cable‐Driven Rehabilitation Robot

Advanced Intelligent Systems
Electromyographic (EMG)‐based admittance control by arm force can provide continuous motion control in robot‐assisted rehabilitation. Natural and complex physical human–robot interactions utilizing intelligent EMG‐based interfaces require a computational
Jianlin Zheng, Zhijun Li, Ting Xu, Rong Song   +3 more
doaj   +1 more source

Multi-Day Activity Pattern Inference Using Constrained Gaussian Mixture Model (GMM) Classification

Urban Science
Multi-day travel diaries are often associated with high rates of partial completion, limiting their value for activity-based demand modeling. This paper develops a probabilistic framework that encodes daily activity sequences, clusters them with a ...
Nikhita Kannam, Mahdieh Allahviranloo, Laure Alice Raymonde Vatin   +2 more
doaj   +1 more source