Zobrazeno 1 - 10
of 121
pro vyhledávání: '"Max Mignotte"'
Publikováno v:
BMC Medical Imaging, Vol 23, Iss 1, Pp 1-11 (2023)
Abstract Background Registration of three-dimensional (3D) knee implant components to radiographic images provides the 3D position of the implants which aids to analyze the component alignment after total knee arthroplasty. Methods We present an auto
Externí odkaz:
https://doaj.org/article/caefae97ca634aa28106bb41fee7b9b9
Autor:
Didier Ndayikengurukiye, Max Mignotte
Publikováno v:
Sensors, Vol 23, Iss 14, p 6450 (2023)
Salient object-detection models attempt to mimic the human visual system’s ability to select relevant objects in images. To this end, the development of deep neural networks on high-end computers has recently achieved high performance. However, dev
Externí odkaz:
https://doaj.org/article/2c9feb4e61f744038b6ed854713fe446
Publikováno v:
Network Neuroscience, Vol 5, Iss 1, Pp 28-55 (2021)
AbstractData-driven parcellations are widely used for exploring the functional organization of the brain, and also for reducing the high dimensionality of fMRI data. Despite the flurry of methods proposed in the literature, functional brain parcellat
Externí odkaz:
https://doaj.org/article/fc9a8fa348904c73af903eeb050d111d
Autor:
Max Mignotte
Publikováno v:
Mathematics, Vol 11, Iss 4, p 986 (2023)
This work presents a Bayesian statistical approach to the saliency map estimation problem. More specifically, we formalize the saliency map estimation issue in the fully automatic Markovian framework. The major and original contribution of the propos
Externí odkaz:
https://doaj.org/article/7151268dd5364cdd9f4f165fcdf6b06f
Autor:
Lazhar Khelifi, Max Mignotte
Publikováno v:
IEEE Access, Vol 8, Pp 126385-126400 (2020)
Deep learning (DL) algorithms are considered as a methodology of choice for remote-sensing image analysis over the past few years. Due to its effective applications, deep learning has also been introduced for automatic change detection and achieved g
Externí odkaz:
https://doaj.org/article/4e16f92dd71e434cbe97a5314a6f1a59
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 13, Pp 588-600 (2020)
In this article, we propose a novel and simple automatic model based on multimodal anomaly feature learning in a residual space, aiming at solving the binary classification problem of temporal change detection (CD) between pairs of heterogeneous remo
Externí odkaz:
https://doaj.org/article/e84f6d6127b14886a67167740702e8a6
Autor:
Didier Ndayikengurukiye, Max Mignotte
Publikováno v:
Journal of Imaging, Vol 8, Iss 4, p 110 (2022)
The effortless detection of salient objects by humans has been the subject of research in several fields, including computer vision, as it has many applications. However, salient object detection remains a challenge for many computer models dealing w
Externí odkaz:
https://doaj.org/article/2ad9394182f74766b9c0382d26ea8fe5
Autor:
Max Mignotte
Publikováno v:
AI, Computer Science and Robotics Technology. 2022:1-20
Statistical methods for automatic change detection, in heterogeneous bitemporal satellite images, remains a challenging research topic in remote sensing mainly because this research field involves the processing of image data with potentially very di
Autor:
Max Mignotte, Lazhar Khelifi
Publikováno v:
International Journal of Image and Data Fusion. 12:99-121
Motion segmentation in dynamic scenes is currently widely dominated by parametric methods based on deep neural networks. The present study explores the unsupervised segmentation approach that can b...
Publikováno v:
Network Neuroscience, Vol 5, Iss 1, Pp 28-55 (2021)
Network Neuroscience
Network Neuroscience
Data-driven parcellations are widely used for exploring the functional organization of the brain, and also for reducing the high dimensionality of fMRI data. Despite the flurry of methods proposed in the literature, functional brain parcellations are