Search results for "Fcm clustering"
showing 5 items of 5 documents
Leveraging Users' Likes in a Video Streaming P2P Platform
2014
This paper investigates how a p2p television platform can take advantage of the presence of frequent channel viewers to grant them a more satisfying service than to less regular spectators. The idea we explore is to learn beforehand about the users' interests, in order to cluster them in groups that display different behaviors; then, the neighborhood creation strategy and video chunk scheduling algorithm of the overlay is altered, with the aim of serving frequent spectators in a privileged manner, providing them with a faster access to the selected channel without overly penalizing less habitual customers. An analytical model is developed, to capture the difference in startup delay that the…
Exudates as Landmarks Identified through FCM Clustering in Retinal Images
2020
The aim of this work was to develop a method for the automatic identification of exudates, using an unsupervised clustering approach. The ability to classify each pixel as belonging to an eventual exudate, as a warning of disease, allows for the tracking of a patient&rsquo
Rings for privacy: An architecture for privacy-preserving user profiling
2014
An interest-aware video streaming platform: Shaping its architecture to better suit users' demands
2014
This paper investigates how a p2p television platform can take advantage of the presence of frequent channel viewers to grant them a more satisfying service than to less regular spectators. The idea we explore is to learn beforehand about the users’ interests, in order to cluster them in groups that display different behaviors; then, the video chunk scheduling algorithm of the p2p overlay is altered, with the aim of serving frequent spectators in a privileged manner, providing them with a faster access to the selected channel. An analytical model is developed, to capture the difference in startup delay that the proposed changes introduce; several additional performance metrics are numerical…
Semi-automatic Brain Lesion Segmentation in Gamma Knife Treatments Using an Unsupervised Fuzzy C-Means Clustering Technique
2016
MR Imaging is being increasingly used in radiation treatment planning as well as for staging and assessing tumor response. Leksell Gamma Knife (R) is a device for stereotactic neuro-radiosurgery to deal with inaccessible or insufficiently treated lesions with traditional surgery or radiotherapy. The target to be treated with radiation beams is currently contoured through slice-by-slice manual segmentation on MR images. This procedure is time consuming and operator-dependent. Segmentation result repeatability may be ensured only by using automatic/semi-automatic methods with the clinicians supporting the planning phase. In this paper a semi-automatic segmentation method, based on an unsuperv…