scholarly journals A SIFT Description Approach for Non-Uniform Illumination and Other Invariants

2021 ◽  
Vol 26 (6) ◽  
pp. 533-539
Author(s):  
Krittachai Boonsivanon ◽  
Worawat Sa-Ngiamvibool
Keyword(s):  
Color Image ◽  
High Sensitivity ◽  
Data Sets ◽  
Morphological Operations ◽  
Uniform Illumination ◽  
Data Set ◽  
Keypoint Detection ◽  
Accuracy And Precision ◽  
Particle Images ◽  
Precision Rate

The new improvement keypoint description technique of image-based recognition for rotation, viewpoint and non-uniform illumination situations is presented. The technique is relatively simple based on two procedures, i.e., the keypoint detection and the keypoint description procedure. The keypoint detection procedure is based on the SIFT approach, Top-Hat filtering, morphological operations and average filtering approach. Where this keypoint detection procedure can segment the targets from uneven illumination particle images. While the keypoint description procedures are described and implemented using the Hu moment invariants. Where the central moments are being unchanged under image translations. The sensitivity, accuracy and precision rate of data sets were evaluated and compared. The data set are provided by color image database with variants uniform and non-uniform illumination, viewpoint and rotation changes. The evaluative results show that the approach is superior to the other SIFTs in terms of uniform illumination, non-uniform illumination and other situations. Additionally, the paper demonstrates the high sensitivity of 100%, high accuracy of 83.33% and high precision rate of 80.00%. Comparisons to other SIFT approaches are also included.

Chato Murciano pig breed: genetic and ethnozoological characterization

2006 ◽  
Vol 38 ◽  
pp. 77-86 ◽  
Author(s):  
B. Peinado ◽  
J.L. Vega-Pla ◽  
M.A. Martínez ◽  
M. Galián ◽  
C. Barba ◽  
...  
Keyword(s):  
Morphological Characterization ◽  
Data Sets ◽  
Large White ◽  
Data Set ◽  
Genetic Studies ◽  
Original Population ◽  
Accuracy And Precision ◽  
Qualitative Variables ◽  
Made In

SummaryThe Chato Murciano is the only surviving breed of pig of those historically farmed in the region of Murcia for their quality meat. At present, it is on the verge of extinction, having a population of only 260 reproductive animals. This paper describes the genetic studies made in the conservation and recovery programme of this breed of pig. A study of the morphological characterization of these animals was carried out first, measuring thirteen quantitative and six qualitative variables in a sample of 24 adult animals, 8 males and 16 females.Subsequently, investigation was made of the consanguinity of the individuals and of the population as well as the future influence of inbreeding in each generation. Finally, the accuracy and precision of the heterozygote-excess method was evaluated using two data sets from the Chato Murciano pig. One data set is an original population and the other is a F3+F4+F5 generation of a line created from mating a Chato Murciano female with a Large White boar as part of an absorption programme based on backcrosses with Chato Murciano boars.

SPSM: A NEW HYBRID DATA CLUSTERING ALGORITHM FOR NONLINEAR DATA ANALYSIS

2009 ◽  
Vol 23 (08) ◽  
pp. 1701-1737 ◽  
Author(s):  
UREERAT WATTANACHON ◽  
CHIDCHANOK LURSINSAP
Keyword(s):  
Clustering Algorithm ◽  
Color Image ◽  
Clustering Algorithms ◽  
Noisy Data ◽  
Second Phase ◽  
Data Sets ◽  
Data Set ◽  
Cluster Distance ◽  
Data Points ◽  
Hybrid Data

Existing clustering algorithms, such as single-link clustering, k-means, CURE, and CSM are designed to find clusters based on predefined parameters specified by users. These algorithms may be unsuccessful if the choice of parameters is inappropriate with respect to the data set being clustered. Most of these algorithms work very well for compact and hyper-spherical clusters. In this paper, a new hybrid clustering algorithm called Self-Partition and Self-Merging (SPSM) is proposed. The SPSM algorithm partitions the input data set into several subclusters in the first phase and, then, removes the noisy data in the second phase. In the third phase, the normal subclusters are continuously merged to form the larger clusters based on the inter-cluster distance and intra-cluster distance criteria. From the experimental results, the SPSM algorithm is very efficient to handle the noisy data set, and to cluster the data sets of arbitrary shapes of different density. Several examples for color image show the versatility of the proposed method and compare with results described in the literature for the same images. The computational complexity of the SPSM algorithm is O(N2), where N is the number of data points.

scholarly journals The high sensitivity of SMOS L-Band vegetation optical depth to biomass

2018 ◽  
Author(s):  
Nemesio J. Rodríguez-Fernández ◽  
Arnaud Mialon ◽  
Stephane Mermoz ◽  
Alexandre Bouvet ◽  
Philippe Richaume ◽  
...  
Keyword(s):  
Land Cover ◽  
Optical Depth ◽  
Large Scale ◽  
Temporal Frequency ◽  
Tree Height ◽  
High Sensitivity ◽  
Data Sets ◽  
Data Set ◽  
Infra Red ◽  
L Band

Abstract. The vegetation optical depth (VOD) measured at microwave frequencies is related to the vegetation water content and provides information complementary to visible/infra-red vegetation indices. This study is devoted to the characterisation of a new VOD data set obtained from SMOS (Soil Moisture and Ocean Salinity) satellite observations at L-band (1.4 GHz). Three different SMOS L-band VOD (L-VOD) data sets (SMOS Level 2, Level 3 and SMOS-IC) were compared with data sets on tree height, visible/infra-red indexes (NDVI, EVI), cumulated precipitation, and above ground biomass (AGB) for the African continent. For all relationships, SMOS-IC showed the lowest dispersion and highest correlation. Overall, we found a strong (R > 0.85) correlation with no clear sign of saturation between L-VOD and four AGB data sets. The relationship linking L-VOD to tree height (R = 0.87) and Baccini's AGB (R = 0.94) was strong and linear. The relationships between L-VOD and three other AGB data sets were linear per land cover class, but with a changing slope depending on the land cover type. For low vegetation classes, the annual mean of L-VOD spans a range from 0 to 0.7 and it is linearly correlation with the amount of the average annual precipitations. SMOS L-VOD showed a higher sensitivity to AGB as compared to NDVI and K/X/C-VOD (VOD measured, respectively, at 19, 10.7, and 6.9 GHz). The results showed that although the spatial resolution of L-VOD is coarse (~ 40 km), the high temporal frequency and sensitivity to AGB makes SMOS L-VOD a very promising index for large scale monitoring of the vegetation status, in particular biomass.

scholarly journals Deep residual detection of radio frequency interference for FAST

2020 ◽  
Vol 492 (1) ◽  
pp. 1421-1431 ◽  
Author(s):  
Zhicheng Yang ◽  
Ce Yu ◽  
Jian Xiao ◽  
Bo Zhang
Keyword(s):  
Radio Frequency ◽  
Large Data ◽  
High Sensitivity ◽  
Original Data ◽  
Training Data ◽  
Radio Frequency Interference ◽  
Data Sets ◽  
Data Set ◽  
Time Required ◽  
Key Steps

ABSTRACT Radio frequency interference (RFI) detection and excision are key steps in the data-processing pipeline of the Five-hundred-meter Aperture Spherical radio Telescope (FAST). Because of its high sensitivity and large data rate, FAST requires more accurate and efficient RFI flagging methods than its counterparts. In the last decades, approaches based upon artificial intelligence (AI), such as codes using convolutional neural networks (CNNs), have been proposed to identify RFI more reliably and efficiently. However, RFI flagging of FAST data with such methods has often proved to be erroneous, with further manual inspections required. In addition, network construction as well as preparation of training data sets for effective RFI flagging has imposed significant additional workloads. Therefore, rapid deployment and adjustment of AI approaches for different observations is impractical to implement with existing algorithms. To overcome such problems, we propose a model called RFI-Net. With the input of raw data without any processing, RFI-Net can detect RFI automatically, producing corresponding masks without any alteration of the original data. Experiments with RFI-Net using simulated astronomical data show that our model has outperformed existing methods in terms of both precision and recall. Besides, compared with other models, our method can obtain the same relative accuracy with fewer training data, thus reducing the effort and time required to prepare the training data set. Further, the training process of RFI-Net can be accelerated, with overfittings being minimized, compared with other CNN codes. The performance of RFI-Net has also been evaluated with observing data obtained by FAST and the Bleien Observatory. Our results demonstrate the ability of RFI-Net to accurately identify RFI with fine-grained, high-precision masks that required no further modification.

The Impact of Site Sample Size on the Reconstruction of Culture Histories

2011 ◽  
Vol 76 (3) ◽  
pp. 547-572 ◽  
Author(s):  
Charles Perreault
Keyword(s):  
Simulated Data ◽  
Archaeological Sites ◽  
Cultural Tradition ◽  
Data Sets ◽  
Data Set ◽  
Rate Of Spread ◽  
Accuracy And Precision ◽  
Historical Processes ◽  
The Impact ◽  
Simulated Data Sets

I examine how our capacity to produce accurate culture-historical reconstructions changes as more archaeological sites are discovered, dated, and added to a data set. More precisely, I describe, using simulated data sets, how increases in the number of known sites impact the accuracy and precision of our estimations of (1) the earliest and (2) latest date of a cultural tradition, (3) the date and (4) magnitude of its peak popularity, as well as (5) its rate of spread and (6) disappearance in a population. I show that the accuracy and precision of inferences about these six historical processes are not affected in the same fashion by changes in the number of known sites. I also consider the impact of two simple taphonomic site destruction scenarios on the results. Overall, the results presented in this paper indicate that unless we are in possession of near-total samples of sites, and can be certain that there are no taphonomic biases in the universe of sites to be sampled, we will make inferences of varying precision and accuracy depending on the aspect of a cultural trait’s history in question.

scholarly journals Reflectance Imaging Spectroscopy (RIS) for Operation Night Watch: Challenges and Achievements of Imaging Rembrandt’s Masterpiece in the Glass Chamber at the Rijksmuseum

Sensors ◽  
2021 ◽  
Vol 21 (20) ◽  
pp. 6855
Author(s):  
Francesca Gabrieli ◽  
John K. Delaney ◽  
Robert G. Erdmann ◽  
Victor Gonzalez ◽  
Annelies van van Loon ◽  
...  
Keyword(s):  
Hyperspectral Image ◽  
Color Image ◽  
Imaging Spectroscopy ◽  
High Sensitivity ◽  
Data Sets ◽  
Paint Sample ◽  
Large Size ◽  
Conservation Plan ◽  
Reflectance Imaging Spectroscopy ◽  
Invasive Techniques

Visible and infrared reflectance imaging spectroscopy is one of the several non-invasive techniques used during Operation Night Watch for the study of Rembrandt’s iconic masterpiece The Night Watch (1642). The goals of this project include the identification and mapping of the artists’ materials, providing information about the painting technique used as well as documenting the painting’s current state and ultimately determining the possible conservation plan. The large size of the painting (3.78 m by 4.53 m) and the diversity of the technical investigations being performed make Operation Night Watch the largest research project ever undertaken at the Rijksmuseum. To construct a complete reflectance image cube at a high spatial resolution (168 µm2) and spectral resolution (2.54 to 6 nm), the painting was imaged with two high-sensitivity line scanning hyperspectral cameras (VNIR 400 to 1000 nm, 2.54 nm, and SWIR 900 to 2500 nm, 6 nm). Given the large size of the painting, a custom computer-controlled 3-D imaging frame was constructed to move each camera, along with lights, across the painting surface. A third axis, normal to the painting, was added along with a distance-sensing system which kept the cameras in focus during the scanning. A total of 200 hyperspectral image swaths were collected, mosaicked and registered to a high-resolution color image to sub-pixel accuracy using a novel registration algorithm. The preliminary analysis of the VNIR and SWIR reflectance images has identified many of the pigments used and their distribution across the painting. The SWIR, in particular, has provided an improved visualization of the preparatory sketches and changes in the painted composition. These data sets, when combined with the results from the other spectral imaging modalities and paint sample analyses, will provide the most complete understanding of the materials and painting techniques used by Rembrandt in The Night Watch.

scholarly journals Predictability analysis of α decay formulae and the α partial half-lives of exotic nuclei

2018 ◽  
Vol 182 ◽  
pp. 02115
Author(s):  
Nabanita Dasgupta-Schubert
Keyword(s):  
Linear Optimization ◽  
Alpha Decay ◽  
Data Sets ◽  
Calibration Data ◽  
Droplet Model ◽  
Data Set ◽  
Α Decay ◽  
Figures Of Merit ◽  
Accuracy And Precision ◽  
Predictability Analysis

We examine the ability of 3 phenomenological alpha decay formulae, the Generalised Liquid Drop Model, the Sobiczewski- Parkhomenko and the Viola-Seaborg-Sobiczewski formulae, to predict the α partial half-lives Tα of 100 exotic alpha radioactive nuclei by the statistical quantification of their accuracy and precision. These quantities were derived using a method based on standard experimental quality assurance wherein the alpha spectroscopic data of 313 well-established alpha decaying nuclei (calibration and test data sets) were used. Experimental masses as well as Finite Range Droplet Model masses were used to compute Qα. Improved coefficients for the three formulae were derived resulting in modified formulae. A simple linear optimization allowed adjustment of the modified formulae for the insufficient statistics of the odd-even and odd-odd decays of the calibration data set, without changing the modified formulae. Relatively better figures of merit for the odd-odd and the SHE were obtained using the modified GLDM formula.

scholarly journals Critical assessment of coiled-coil predictions based on protein structure data

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Dominic Simm ◽  
Klas Hatje ◽  
Stephan Waack ◽  
Martin Kollmar
Keyword(s):  
Binary Classification ◽  
Coiled Coil ◽  
Imbalanced Data ◽  
Data Bank ◽  
Data Sets ◽  
Data Set ◽  
Imbalanced Data Sets ◽  
Protein Motifs ◽  
Accuracy And Precision ◽  
Reliable Performance

AbstractCoiled-coil regions were among the first protein motifs described structurally and theoretically. The simplicity of the motif promises that coiled-coil regions can be detected with reasonable accuracy and precision in any protein sequence. Here, we re-evaluated the most commonly used coiled-coil prediction tools with respect to the most comprehensive reference data set available, the entire Protein Data Bank, down to each amino acid and its secondary structure. Apart from the 30-fold difference in minimum and maximum number of coiled coils predicted the tools strongly vary in where they predict coiled-coil regions. Accordingly, there is a high number of false predictions and missed, true coiled-coil regions. The evaluation of the binary classification metrics in comparison with naïve coin-flip models and the calculation of the Matthews correlation coefficient, the most reliable performance metric for imbalanced data sets, suggests that the tested tools’ performance is close to random. This implicates that the tools’ predictions have only limited informative value. Coiled-coil predictions are often used to interpret biochemical data and are part of in-silico functional genome annotation. Our results indicate that these predictions should be treated very cautiously and need to be supported and validated by experimental evidence.

Choosing Appropriate Taxonomic Units for Ecological Survey and Experimentation: the Response of Aristida to Management and Landscape Factors as an Example.

1997 ◽  
Vol 19 (1) ◽  
pp. 26 ◽  
Author(s):  
S Mcintyre ◽  
PG Filet
Keyword(s):  
Rare Species ◽  
Individual Species ◽  
Data Sets ◽  
Data Set ◽  
Specific Level ◽  
Accuracy And Precision ◽  
Intermediate Unit ◽  
High Level ◽  
Management Recommendations ◽  
Result Management

The use of appropriate taxonomic units to describe herbaceous vegetation is an issue of increasing importance due to developing interest in the effects of grazing and other management on plant diversity in pastures. We use data for the genus Aristida as an example to examine patterns of ecological response to grazing, pasture sowing and landscape position in different taxonomic units. Responses of Aristida at the level of genus, section and species were compared over the gradients. There was strong evidence of differential responses to these factors, both between sections within genus, and between species within sections. The planning and execution of botanical field descriptions involve striking a balance between taxonomic accuracy and precision that will best address the objectives of a particular project. The species of the genus Aristida have a range of ecological responses, the variety of which can not be captured in data sets which record Aristida as a single entity. As a result, management recommendations for the genus in its entirety are likely to be inaccurate. Although data collection might ideally record individual species, this is not always practicable. In any case, there may be many rare species in the data set, with occurrences too low to detect ecological pattern. Delineation of rare species may only be important if diversity issues are being examined. In other circumstances the use of an intermediate unit (e.g. section or species groups) may be appropriate. The latter approach may be required if there are practical limitations to the collection of data at specific level for all groups, or if the research objectives do not require a high level of precision.

High-resolution 3-D and 4-D imaging using wide-field CCD-based microscopy

1993 ◽  
Vol 51 ◽  
pp. 150-151
Author(s):  
Jason R. Swedlow ◽  
Bethe A. Scalettar ◽  
John W. Sedat ◽  
David A. Agard
Keyword(s):  
Fluorescent Proteins ◽  
Three Dimensional ◽  
Numerical Aperture ◽  
High Sensitivity ◽  
Objective Lens ◽  
Data Sets ◽  
Wide Field ◽  
Data Set ◽  
Image Stack ◽  
A Charge

Because of the limited numerical aperture of a light microscope objective lens, every image recorded from a microscope is blurred and therefore degraded. This problem is particularly acute when a full three-dimensional image stack is viewed in projection. The blurred image is a convolution between every light source in an object and the point-spread function (PSF) of the objective lens and can be mathematically calculated or empirically measured. To eliminate blurring, we record three- and four-dimensional images with a charge-coupled device (CCD) -based computerized optical sectioning microscope and mathematically deconvolve out-of-focus photons using the appropriate three-dimensional, empirically measured PSF. The use of the empirical PSF is important because of the presence of a partial confocal effect in a wide field microscope caused by the presence of the field diaphragm. The advantage in this method is that collection and restoration of out-of-focus photons results in high sensitivity and resolution.In order to follow nuclear and chromosome dynamics, we have injected Drosophila melanogaster embryos with various fluorescent proteins and then monitored the distribution of these proteins during mitosis by recording a series of three-dimensional data sets at regular time intervals-- a four dimensional data set.

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