Search results for "Ruth"
showing 10 items of 661 documents
New Error Measures to Evaluate Features on Three-Dimensional Scenes
2011
In this paper new error measures to evaluate image features in three-dimensional scenes are proposed and reviewed. The proposed error measures are designed to take into account feature shapes, and ground truth data can be easily estimated. As other approaches, they are not error-free and a quantitative evaluation is given according to the number of wrong matches and mismatches in order to assess their validity
Uncertainties in The S-Sebi Model to Estimate Surface Energy Fluxes Over Natural Grasslands in Brazil
2021
Evapotranspiration (ET) is one of the main fluxes in the global water cycle. In this context, we assessed an operational methodology based on the S-SEBI model to accurately estimate energy fluxes over the natural grasslands of Pampa biome. The S-SEBI performance was investigated considering radiation data from both ERA5 reanalysis and tower flux. Comparisons from satellite-based estimates with in situ measurements were performed with and without energy balance closure (EBC). Results indicated that meteorological inputs have low sensitivity on daily ET estimates. In contrast, the instantaneous components are more affected. The impact in the daily ET is lower when in situ data without EBC are…
Identifying Unreliable Sensors Without a Knowledge of the Ground Truth in Deceptive Environments
2017
This paper deals with the extremely fascinating area of “fusing” the outputs of sensors without any knowledge of the ground truth. In an earlier paper, the present authors had recently pioneered a solution, by mapping it onto the fascinating paradox of trying to identify stochastic liars without any additional information about the truth. Even though that work was significant, it was constrained by the model in which we are living in a world where “the truth prevails over lying”. Couched in the terminology of Learning Automata (LA), this corresponds to the Environment (Since the Environment is treated as an entity in its own right, we choose to capitalize it, rather than refer to it as an “…
Automatic Segmentation of Pulmonary Lobes in Pulmonary CT Images using Atlas-based Unsupervised Learning Network
2020
Pulmonary lobes segmentation of pulmonary CT images is important for assistant therapy and diagnosis of pulmonary disease in many clinical tasks. Recently supervised deep learning methods are applied widely in fast automatic medical image segmentation including pulmonary lobes segmentation of pulmonary CT images. However, they require plenty of ground truth due to their supervised learning scheme, which are always difficult to realize in practice. To address this issue, in this study we extend an existed unsupervised learning network with an extra pulmonary mask constraint to develop a deformable pulmonary lobes atlas and apply it for fast automatic segmentation of pulmonary lobes in pulmon…
Outdoor Scenes Pixel-wise Semantic Segmentation using Polarimetry and Fully Convolutional Network
2019
International audience; In this paper, we propose a novel method for pixel-wise scene segmentation application using polarimetry. To address the difficulty of detecting highly reflective areas such as water and windows, we use the angle and degree of polarization of these areas, obtained by processing images from a polarimetric camera. A deep learning framework, based on encoder-decoder architecture, is used for the segmentation of regions of interest. Different methods of augmentation have been developed to obtain a sufficient amount of data, while preserving the physical properties of the polarimetric images. Moreover, we introduce a new dataset comprising both RGB and polarimetric images…
Robust Principal Component Analysis of Data with Missing Values
2015
Principal component analysis is one of the most popular machine learning and data mining techniques. Having its origins in statistics, principal component analysis is used in numerous applications. However, there seems to be not much systematic testing and assessment of principal component analysis for cases with erroneous and incomplete data. The purpose of this article is to propose multiple robust approaches for carrying out principal component analysis and, especially, to estimate the relative importances of the principal components to explain the data variability. Computational experiments are first focused on carefully designed simulated tests where the ground truth is known and can b…
Automatic Seed Placement for Breast Lesion Segmentation on US Images
2012
Breast lesion boundaries have been mostly extracted by using conventional approaches as a previous step in the development of computer-aided diagnosis systems. Among these, region growing is a frequently used segmentation method. To make the segmentation completely automatic, most of the region growing methods incorporate automatic selection of the seed points. This paper proposes a new automatic seed placement algorithm for breast lesion segmentation on ultrasound images by means of assigning the probability of belonging to a lesion for every pixel depending on intensity, texture and geometrical constraints. The proposal has been evaluated using a set of sonographic breast images with acco…
Weighted Likelihood Function of Multiple Statistical Parameters to Retrieve 2D TRUS-MR Slice Correspondece for Prostate Biopsy
2012
International audience; This paper presents a novel method to identify the 2D axial Magnetic Resonance (MR) slice from a pre-acquired MR prostate volume that closely corresponds to the 2D axial Transrectal Ultrasound (TRUS) slice obtained during prostate biopsy. The shape-context representations of the segmented prostate contours in both the imaging modalities are used to establish point correspondences using Bhattacharyya distance. Thereafter, Chi-square distance is used to find the prostate shape similarities between the MR slices and the TRUS slice. Normalized mutual information and correlation coefficient between the TRUS and MR slices are computed to find the information theoretic simi…
A hybrid framework of multiple active appearance models and global registration for 3D prostate segmentation in MRI.
2012
International audience; Real-time fusion of Magnetic Resonance (MR) and Trans Rectal Ultra Sound (TRUS) images aid in the localization of malignant tissues in TRUS guided prostate biopsy. Registration performed on segmented contours of the prostate reduces computational complexity and improves the multimodal registration accuracy. However, accurate and computationally efficient 3D segmentation of the prostate in MR images could be a challenging task due to inter-patient shape and intensity variability of the prostate gland. In this work, we propose to use multiple statistical shape and appearance models to segment the prostate in 2D and a global registration framework to impose shape restri…
Design of a Generic 3-D Scene Generator for Passive Optical Missions and Its Implementation for the ESA’s FLEX/Sentinel-3 Tandem Mission
2018
During the design phase of a satellite mission, end-to-end mission performance simulator (E2ES) tools allow scientists and engineers evaluating the mission concept, consolidating system technical requirements and analyzing the suitability of the implemented technical solutions and data processing algorithms. The generation of synthetic scenes is one of the core parts of an E2ES, providing scenes (ground truth) as would be observed by satellite instruments and used as reference against simulated retrieved mission products. An appropriate generation of the scene also allows assessing the performance of the ground data processing chain replacing real instrument data before the mission is in or…