Search results for "Preprocessor"
showing 10 items of 49 documents
A one class KNN for signal identification: a biological case study
2009
The paper describes an application of a one class KNN to identify different signal patterns embedded in a noise structured background. The problem becomes harder whenever only one pattern is well-represented in the signal; in such cases, one class classifier techniques are more indicated. The classification phase is applied after a preprocessing phase based on a multi layer model (MLM) that provides preliminary signal segmentation in an interval feature space. The one class KNN has been tested on synthetic and real (Saccharomyces cerevisiae) microarray data in the specific problem of DNA nucleosome and linker regions identification. Results have shown, in both cases, a good recognition rate.
Entropy measures, entropy estimators, and their performance in quantifying complex dynamics: Effects of artifacts, nonstationarity, and long-range co…
2017
Entropy measures are widely applied to quantify the complexity of dynamical systems in diverse fields. However, the practical application of entropy methods is challenging, due to the variety of entropy measures and estimators and the complexity of real-world time series, including nonstationarities and long-range correlations (LRC). We conduct a systematic study on the performance, bias, and limitations of three basic measures (entropy, conditional entropy, information storage) and three traditionally used estimators (linear, kernel, nearest neighbor). We investigate the dependence of entropy measures on estimator- and process-specific parameters, and we show the effects of three types of …
Transferability of Deep Learning Algorithms for Malignancy Detection in Confocal Laser Endomicroscopy Images from Different Anatomical Locations of t…
2019
Squamous Cell Carcinoma (SCC) is the most common cancer type of the epithelium and is often detected at a late stage. Besides invasive diagnosis of SCC by means of biopsy and histo-pathologic assessment, Confocal Laser Endomicroscopy (CLE) has emerged as noninvasive method that was successfully used to diagnose SCC in vivo. For interpretation of CLE images, however, extensive training is required, which limits its applicability and use in clinical practice of the method. To aid diagnosis of SCC in a broader scope, automatic detection methods have been proposed. This work compares two methods with regard to their applicability in a transfer learning sense, i.e. training on one tissue type (f…
Geo‐referencing naturalistic driving data using a novel method based on vehicle speed
2013
Naturalistic driving is an experimentation model that allows us to recognise the driving modes observing the driver's behaviour at the wheel of a set of people in natural conditions during long periods of observation. This research methodology aims at increasing the representativeness of the data collected in opposition to data stemming from highly controlled laboratory experiments. However, naturalistic driving research designs produce large volumes of data that are difficult to handle. Thus, it is very important to work with suitable methods for representing and interpreting data, allowing us to observe the variability of the results. The aim of this study is to implement a new methodolog…
A knowledge-based decision support system in bioinformatics: An application to protein complex extraction
2013
Abstract Background We introduce a Knowledge-based Decision Support System (KDSS) in order to face the Protein Complex Extraction issue. Using a Knowledge Base (KB) coding the expertise about the proposed scenario, our KDSS is able to suggest both strategies and tools, according to the features of input dataset. Our system provides a navigable workflow for the current experiment and furthermore it offers support in the configuration and running of every processing component of that workflow. This last feature makes our system a crossover between classical DSS and Workflow Management Systems. Results We briefly present the KDSS' architecture and basic concepts used in the design of the knowl…
Physics, Techniques and Review of Neuroradiological Applications of Diffusion Kurtosis Imaging (DKI)
2016
In recent years many papers about diagnostic applications of diffusion tensor imaging (DTI) have been published. This is because DTI allows to evaluate in vivo and in a non-invasive way the process of diffusion of water molecules in biological tissues. However, the simplified description of the diffusion process assumed in DTI does not permit to completely map the complex underlying cellular components and structures, which hinder and restrict the diffusion of water molecules. These limitations can be partially overcome by means of diffusion kurtosis imaging (DKI). The aim of this paper is the description of the theory of DKI, a new topic of growing interest in radiology. DKI is a higher or…
An extension of the Burrows-Wheeler Transform and applications to sequence comparison and data compression
2005
We introduce a generalization of the Burrows-Wheeler Transform (BWT) that can be applied to a multiset of words. The extended transformation, denoted by E, is reversible, but, differently from BWT, it is also surjective. The E transformation allows to give a definition of distance between two sequences, that we apply here to the problem of the whole mitochondrial genome phylogeny. Moreover we give some consideration about compressing a set of words by using the E transformation as preprocessing.
First results from the PROBA/CHRIS hyperspectral/multiangular satellite system over land and water targets
2005
The Project for On-Board Autonomy (PROBA) platform developed by the European Space Agency was launched on October 22, 2001. The instrument payload includes the Compact High Resolution Imaging Spectrometer (CHRIS). The coupled system provides high spatial resolution hyperspectral/multi-angular data, which represents a new-generation source of information for Earth observation purposes. The first results obtained from the preprocessing (noise removal and geometric/atmospheric correction) of two different datasets, collected over agricultural crops and inland waters, are presented in this letter. In situ measurements are used to assess the quality of the data and to validate the processing alg…
Automatic Segmentation and Enhancement of Pavement Cracks Based on 3D Pavement Images
2019
Pavement cracking is a significant symptom of pavement deterioration and deficiency. Conventional manual inspections of road condition are gradually replaced by novel automated inspection systems. As a result, a great amount of pavement surface information is digitized by these systems with a high resolution. With pavement surface data, pavement cracks can be detected using crack detection algorithms. In this paper, a fully automated algorithm for segmenting and enhancing pavement crack is proposed, which consists of four major procedures. First, a preprocessing procedure is employed to remove spurious noise and rectify the original 3D pavement data. Second, crack saliency maps are segmente…
T-wave alternans analysis improvement by means of curve alignment prior to distance calculation.
2007
Tracking of repolarization instabilities in the ECG, such as T-wave alternans (TWA), has become a popular non-invasive method to assess the vulnerability to malignant arrhythmic events. These instabilities are usually characterized by small amplitude changes and their measurement is difficult due to the presence of noise and artifacts. Several methods have been recently proposed to address this problem. Most of them are based on amplitude analysis of beat-to-beat alternation of the T wave. This paper describes a preprocessing stage intended to be used prior to amplitude analysis and aimed at improving the alignment between consecutive T waves. This increases the accuracy of the difference c…