Spatially aligning medical images from different modalities remains a challenging task, especially for intraoperative applications that require fast and robust algorithms. We propose a weakly-supervised, label-driven formulation for learning 3D voxel correspondence from higher-level label correspondence, thereby bypassing classical intensity-based image similarity measures. During training, a c...

The extended Kalman filter (EKF) is considered one of the most effective methods for both nonlinear state estimation and parameter estimation (e.g., learning the weights of a neural network). Recently, a number of derivative free alternatives to the EKF for state estimation have been proposed. These include the Unscented Kalman Filter (UKF) [1, 2], the Central Difference Filter (CDF) [3] and th...

Recent works in multispectral image processing advocate the employment of vector approaches for this class of signals. Vector processing operators that involve the minimization of a suitable error criterion have been proposed and shown appropriate for this task. In this framework, two main classes of vector processing filters have been reported in the literature. Astola et al. (1990) introduce ...

Average annual loss (AAL) is traditionally used as the basis of assessing flood risk and evaluating mitigation measures. This research presents an improved implementation to estimate building-specific AAL, with hazard a building represented by Gumbel extreme value distribution. AAL then calculated integrating area under overall loss-exceedance probability curve using trapezoidal Riemann sums. c...

The performance of user cooperation that results when users forward packets for each other in a multiaccess network is compared to that of dedicated-relay cooperation which results from using a dedicated wireless relay when the users do not cooperate. Using the total transmit and processing power consumed at all nodes as a cost metric, the outage probabilities achieved by dynamic decode-and-for...

Grass composition was assessed by plot method (1 m2; n= 1,749) in three habitats (dry deciduous-DDF, moist deciduous-MDF, and thorn forest-TF) at Mudumalai Tiger Reserve, southern India across different seasons from Jan 2004 to Dec 2007. The grass species richness availability (per cent composition) varied significantly with habitats. Seventy-four of grasses sedges were recorded all habitats, a...

We aim to solve the problem of consistent Decentralised Data Fusion (DDF) with particle filters by a transformation of the sample statistics to a different representation that maintains an accurate summary of the particles. Two methodologies are proposed. The first method is a transformation of the particle representation to a Gaussian Mixture Model (GMM). The second algorithm approximates the ...

Subjective accommodation refractive error models are essential for implementing adaptive vision correction devices that utilize varifocal optics. This article describes compact empirical of subjective accommodative errors in subjects with advanced presbyopia. The based on measurements from fifteen presbyopes over the age 45 using commercially available focus-tunable eyeglasses under three diffe...

Recent advances in unsupervised domain adaptation (UDA) techniques have witnessed great success cross-domain computer vision tasks, enhancing the generalization ability of data-driven deep learning architectures by bridging distribution gaps. For UDA-based object detection methods, majority them alleviate bias inducing domain-invariant feature generation via adversarial strategy. However, their...

Diffusion Magnetic Resonance Imaging (MRI) is used to (noninvasively) study neuronal fibers in the brain white matter. Reconstructing fiber paths from such data (tractography problem) is relevant in particular to study the connectivity between two given cerebral regions. Fiber-tracking models rely on how water molecules diffusion is represented in each MRI voxel. The Diffusion Spectrum Imaging ...