Search results for " classification"

Study and Evaluation of Pre-trained CNN Networks for Cultural Heritage Image Classification

2021

The classification of digital images is an essential task during the restoration and preservation of cultural heritage (CH). In computer vision, cultural heritage classification relies on the classification of asset images regarding a certain task such as type, artist, genre, style identification, etc. CH classification is challenging as various CH asset images have similar colors, textures, and shapes. In this chapter, the aim is to study and evaluate the use of pre-trained deep convolutional neural networks such as VGG16, VGG-19, ResNet50, and Inception-V3 for cultural heritage images classification using transfer learning techniques. The main idea is to start with CNN models previously t…

Multi-criterial approaches for the inventory and the evaluation of traditional cultural landscapes

2008

The Mediterranean environment is characterized by an high variability in ecological features and by a rich biodiversity, whose interaction has generated complex agro-forestry systems. The resulting cultural landscapes can represent a remarkable trait of Italian landscape. Nonetheless, since several decades they are at risk mainly owing to the consequences of cultural intensification, that has turn out in new cultural models, i.e. specialized high density agronomic plantation, or in a progressive abandonment of agricultural land. In order to prevent the degradation or loos of these particular ecosystems, it becomes a priority to adopt measures for their preservation and promotion. Regardless…

ICTV Virus Taxonomy Profile: Cystoviridae

2017

The family Cystoviridae includes enveloped viruses with a tri-segmented dsRNA genome and a double-layered protein capsid. The innermost protein shell is a polymerase complex responsible for genome packaging, replication and transcription. Cystoviruses infect Gram-negative bacteria, primarily plant-pathogenic Pseudomonas syringae strains. This is a summary of the International Committee on Taxonomy of Viruses (ICTV) Report on the taxonomy of the Cystoviridae, which is available at http://www.ictv.global/report/cystoviridae.

A low level image analysis approach to starfish detection

2003

Machine learning in remote sensing data processing

2009

Remote sensing data processing deals with real-life applications with great societal values. For instance urban monitoring, fire detection or flood prediction from remotely sensed multispectral or radar images have a great impact on economical and environmental issues. To treat efficiently the acquired data and provide accurate products, remote sensing has evolved into a multidisciplinary field, where machine learning and signal processing algorithms play an important role nowadays. This paper serves as a survey of methods and applications, and reviews the latest methodological advances in machine learning for remote sensing data analysis.

Dimensionality Reduction Techniques: An Operational Comparison On Multispectral Satellite Images Using Unsupervised Clustering

2006

Multispectral satellite imagery provides us with useful but redundant datasets. Using Dimensionality Reduction (DR) algorithms, these datasets can be made easier to explore and to use. We present in this study an objective comparison of five DR methods, by evaluating their capacity to provide a usable input to the K-means clustering algorithm. We also suggest a method to automatically find a suitable number of classes K, using objective "cluster validity indexes" over a range of values for K. Ten Landsat images have been processed, yielding a classification rate in the 70-80% range. Our results also show that classical linear methods, though slightly outperformed by more recent nonlinear al…

Integration of high and low resolution NDVI data for monitoring vegetation in Mediterranean environments

1998

Abstract The integration of the useful features of high and low spatial and temporal resolution satellite data is a major issue in remote sensing studies. The current work presents the development and testing of a procedure based on classification and regression analysis techniques for generating an NDVI data set with the spatial resolution of Landsat TM images and the temporal resolution of NOAA AVHRR maximum-value composites. The procedure begins with a classification of the high resolution TM data which yields land use references. These are degraded to low spatial resolution in order to produce abundance images comparable with the AVHRR data. Linear regressions are then applied between t…

Not just BLAST nt: WGS database joins the party

2019

AbstractSince its introduction in 1990 and with over 50k citations, the NCBI BLAST family has been an essential tool of in silico molecular biology. The BLAST nt database, based on the traditional divisions of GenBank, has been the default and most comprehensive database for nucleotide BLAST searches and for taxonomic classification software in metagenomics. Here we argue that this is no longer the case. Currently, the NCBI WGS database contains one billion reads (almost five times more than GenBank), and with 4.4 trillion nucleotides, WGS has about 14 times more nucleotides than GenBank. This ratio is growing with time. We advocate a change in the database paradigm in taxonomic classificat…

FABC: Retinal Vessel Segmentation Using AdaBoost

2010

This paper presents a method for automated vessel segmentation in retinal images. For each pixel in the field of view of the image, a 41-D feature vector is constructed, encoding information on the local intensity structure, spatial properties, and geometry at multiple scales. An AdaBoost classifier is trained on 789 914 gold standard examples of vessel and nonvessel pixels, then used for classifying previously unseen images. The algorithm was tested on the public digital retinal images for vessel extraction (DRIVE) set, frequently used in the literature and consisting of 40 manually labeled images with gold standard. Results were compared experimentally with those of eight algorithms as we…

Nursing interventions of choice for the prevention and treatment of suicidal behaviour: The umbrella review protocol

2022

Abstract Aim To determine which interventions, from a nursing perspective, can be considered as the interventions of choice for the prevention and treatment of suicidal behaviour. In this way, the umbrella review attempts to identify nursing interventions from the Nursing Interventions Classification (NIC) taxonomy with evidence for this purpose. Design Descriptive study protocol. Methods This umbrella review will consist of an extensive, systematic search of published systematic reviews and meta‐analyses of studies examining interventions of choice for the prevention and treatment of suicidal behaviour. A systematic search of papers indexed in PubMed, CINAHL, Cochrane Database of Systemati…