Accurately assessing the medical image segmentation quality of automatically generated predictions is essential for guaranteeing reliability results computer-assisted diagnosis (CAD). Many researchers have studied estimation without labeled ground truths. Recently, a novel idea proposed, which transforms assessment (SQA) into pixel-wise or voxel-wise error map task. However, simple application ...

High dynamic range (HDR) illumination estimation from a single low (LDR) image is significant task in computer vision, graphics, and augmented reality. We present two-stage deep learning-based method to predict an HDR environment map narrow field-of-view LDR image. first learn hybrid parametric representation that sufficiently covers high- low-frequency components the environment. Taking estima...

Landslides are among the most damaging natural hazards in mountainous regions. In this study, landslide hazard zonation was conducted in the Baba Heydar Watershed using logistic statistical regression to determine landslide hazard areas. First, a landslide inventory map was prepared using aerial photograph interpretation and field surveys. Next, ten landslide conditioning factors including alti...

Abstract: In this article we propose a maximal a posteriori (MAP) criterion for model selection in the motif discovery problem and investigate conditions under which the MAP asymptotically gives a correct prediction of model size. We also investigate robustness of the MAP to prior specification and provide guidelines for choosing prior hyper-parameters for motif models based on sensitivity cons...

in response to the demand for soil spatial information, the acquisition of digital auxiliary data and their matching with field soil observations is on the increase. with the harmonization of these data sets, through computer based methods, the so-called digital soil maps are increasingly being found to be as reliable as the traditional soil mapping practices, and with no prohibitive costs. the...

A Kalman/map filtering (KMF)-aided fast normalized cross correlation (FNCC)-based Wi-Fi fingerprinting location sensing system is proposed in this paper. Compared with conventional neighbor selection algorithms that calculate localization results with received signal strength (RSS) mean samples, the proposed FNCC algorithm makes use of all the on-line RSS samples and reference point RSS variati...

Prediction of fold from amino acid sequence of a protein has been an active area of research in the past few years, but the limited accuracy of existing techniques emphasizes the need to develop newer approaches to tackle this task. In this study, we use contact map prediction as an intermediate step in fold prediction from sequence. Contact map is a reduced graph-theoretic representation of pr...

The key challenge in the design of wireless sensor networks is maximizing their lifetime. The information about the amount of available energy in each part of the network is called the energy map and can be useful to increase the lifetime of the network. In this paper, we address the problem of constructing the energy map of a wireless sensor network using prediction-based approaches. We also p...

Being reversible, the watermarking information embedded in audio signals can be extracted while the original audio data can achieve lossless recovery. Currently, the few reversible audio watermarking algorithms are confronted with following problems: relatively low SNR (signal-to-noise) of embedded audio; a large amount of auxiliary embedded location information; and the absence of accurate cap...

Output time prediction is a critical task to a wafer fab (fabrication plant). To further enhance the accuracy of wafer lot output time prediction, the concept of input classification is applied to Chen’s fuzzy back propagation network (FBPN) in this study by pre-classifying input examples with the self-organization map (SOM) classifier before they are fed into the FBPN. Examples belonging to di...