Results 51 to 60 of about 7,263 (222)

AUTO GMM-SAMT: An Automatic Object Tracking System for Video Surveillance in Traffic Scenarios

EURASIP Journal on Image and Video Processing, 2011
A complete video surveillance system for automatically tracking shape and position of objects in traffic scenarios is presented. The system, called Auto GMM-SAMT, consists of a detection and a tracking unit.
Quast Katharina, Kaup André
doaj  

Interactive Prompt‐Guided Robotic Grasping for Arbitrary Objects Based on Promptable Segment Anything Model and Force‐Closure Analysis

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
A laser pointer‐guided robotic grasping method for arbitrary objects based on promptable segment anything model and force‐closure analysis is presented. Grasp generation methods based on force‐closure analysis can calculate the optimal grasps for objects through their appearances. However, the limited visual perception ability makes robots difficult to
Yan Liu, Yaxin Liu, Ruiqing Han, Kai Zheng, Yufeng Yao, Ming Zhong   +5 more
wiley   +1 more source

CytoScan: Automated Detection of Technical Anomalies for Cytometry Quality Control

Cytometry Part A, EarlyView.
ABSTRACT Studies evaluating cellular phenotypes by cytometry techniques are increasingly facing analytical challenges due to the multitudes of samples and parameters that are evaluated concurrently. Spurious technical effects resulting from a lack of standardization can affect marker distributions and further complicate multi‐sample analyses.
Tim R. Mocking, Felix Zwolle, Yejin Park, Angèle Kelder, Yvan Saeys, Jacqueline Cloos, Sofie van Gassen, Costa Bachas   +7 more
wiley   +1 more source

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

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

Segmentation d’image par la méthode GMM (Gaussian Mixture Model)

, 2022
e travail effectué et présenté dans ce mémoire se situe dans le domaine du traitement d’images en général et la segmentation d’images en particulier. La segmentation d’images est généralement l’étape la plus importante dans le processus d’analyse d’images. Dans notre projet de fin d’étude nous avons travaillés sur les images médicales cérébrales d’IRM,
Haddouche, Marwa, Rahmani, Ikhlasse
openaire   +1 more source

Complex Versus Parsimonious Site‐Based Stochastic Ground Motion Models: Which One Is Better?

Earthquake Engineering &Structural Dynamics, EarlyView.
ABSTRACT Stochastic ground motion models (GMMs) provide a probabilistic representation of seismic input and are increasingly important for uncertainty quantification (UQ) in earthquake engineering. This study focuses on site‐based stochastic GMMs, which learn the statistical features of selected datasets of seismic records and generate statistically ...
Maijia Su, Mayssa Dabaghi, Marco Broccardo   +2 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

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

Early Feasibility of Registration of Micro‐PET/CT Scans to Annotated 3D Specimen Models

Head &Neck, EarlyView.
ABSTRACT Background Intraoperative 18F‐fluorodeoxyglucose (18F‐FDG) micro‐positron emission tomography/computed tomography (micro‐PET/CT) is an emerging modality for margin assessment. Prior to clinical use, micro‐PET/CT margin distances must be correlated with gold‐standard histopathology.
Joaquin Austerlitz, Andreja Radevic, Ashtyn McAdoo, Kyrionna Golliday, Cheng Ye, Daniel Fabbri, Adam J. Rosenberg, Marcus Balanky, Anas Alabkaa, Kim A. Ely, Mitra Mehrad, Spencer Roark, Eben Rosenthal, Michael C. Topf   +13 more
wiley   +1 more source