Relevant bibliographies by topics / Birds – Identification

Academic literature on the topic 'Birds – Identification'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Birds – Identification"

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Zhang, Shanshan, Hong Ying, Gesang Pingcuo, Shuo Wang, Fan Zhao, Yongning Cui, Jian Shi, Hu Zeng, and Xiuli Zeng. "Identification of Potential Metabolites Mediating Bird’s Selective Feeding on Prunus mira Flowers." BioMed Research International 2019 (June 23, 2019): 1–8. http://dx.doi.org/10.1155/2019/1395480.

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In peach orchards, birds severely damage flowers during blossom season, decreasing the fruit yield potential. However, the wild peach species Prunus mira shows intraspecific variations of bird damage, indicating that some of the wild trees have developed strategies to avert bird foraging. Motivated by this observation, we formulated the present study to identify the potential flower metabolites mediating the bird’s selective feeding behavior in P. mira flowers. The birds’ preferred (FG) and avoided (BFT) flowers were collected from wild P. mira trees at three different locations, and their metabolite contents were detected, quantified, and compared. The widely-targeted metabolomics approach was employed to detect a diverse set of 603 compounds, predominantly, organic acids, amino acid derivatives, nucleotide and its derivatives, and flavones. By quantitatively comparing the metabolite contents between FG and BFT, three candidate metabolites, including Eriodictiol 6-C-hexoside 8-C-hexoside-O-hexoside, Luteolin O-hexosyl-O-hexosyl-O-hexoside, and Salvianolic acid A, were differentially accumulated and showed the same pattern across the three sampling locations. Distinctly, Salvianolic acid A was abundantly accumulated in FG but absent in BFT, implying that it may be the potential metabolite attracting birds in some P. mira flowers. Overall, this study sheds light on the diversity of the floral metabolome in P. mira and suggests that the bird’s selective feeding behavior may be mediated by variations in floral metabolite contents.
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Purwaningrum, Medania, Herjuno Ari Nugroho, Machmud Asvan, Karyanti Karyanti, Bertha Alviyanto, Randy Kusuma, and Aris Haryanto. "Molecular techniques for sex identification of captive birds." Veterinary World 12, no. 9 (September 2019): 1506–13. http://dx.doi.org/10.14202/vetworld.2019.1506-1513.

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Background and Aim: Many avian species are considered sexually monomorphic. In monomorphic bird species, especially in young birds, sex is difficult to identify based on an analysis of their external morphology. Accurate sex identification is essential for avian captive breeding and evolutionary studies. Methods with varying degrees of invasiveness such as vent sexing, laparoscopic surgery, steroid sexing, and chromosome inspection (karyotyping) are used for sex identification in monomorphic birds. This study aimed to assess the utility of a non-invasive molecular marker for gender identification in a variety of captive monomorphic birds, as a strategy for conservation. Materials and Methods: DNA was isolated from feather samples from 52 individuals representing 16 species of 11 families indigenous to both Indonesia and elsewhere. We amplified the chromodomain helicase DNA-binding (CHD) gene using polymerase chain reaction with MP, NP, and PF primers to amplify introns with lengths that differ between the CHD-W and the CHD-Z genes, allowing sex discrimination because the W chromosome is exclusively present in females. Results: Molecular bird sexing confirmed 33 females and 19 males with 100% accuracy. We used sequencing followed by alignment on one protected bird species (Probosciger aterrimus). Conclusion: Sex identification may be accomplished noninvasively in birds, because males only have Z sex chromosomes, whereas females have both Z and W chromosomes. Consequently, the presence of a W-unique DNA sequence identifies an individual as female. Sexing of birds is vital for scientific research, and to increase the success rate of conservation breeding programs.
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Griffiths, Richard. "Sex identification in birds." Seminars in Avian and Exotic Pet Medicine 9, no. 1 (January 2000): 14–26. http://dx.doi.org/10.1016/s1055-937x(00)80012-2.

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Sinyo, Bayu A., L. Lambey, F. Kairupan, and J. Keintjem. "KAJIAN WARNA DAN CORAK BULU PADA BURUNG WERIS DI KOTA KOTAMOBAGU SULAWESI UTARA." ZOOTEC 34, no. 1 (February 28, 2014): 124. http://dx.doi.org/10.35792/zot.34.1.2014.3878.

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ABSTRACT STUDY ON FEATHER PATTERN AND COLORS OF “WERIS” BIRDS IN CITY OF KOTAMOBAGU. Mandar bird (Gallirallus) which in local language known as Weris (Minahasa), and Boruit (Kotamobagu) is a bird in the family Rallidae, are a family of birds that have small to medium body size. General habitat of this bird species is swamp, near a river or lake. Weris birds generally breed in densely vegetated areas According Rusila (1994). Identify an issue in the study is the identification of colors and feather patterns, two species weris birds that exist in Kotamobagus (North Sulawesi). The purpose of this study was to obtain date on the diversity of colors and patterns that exist in weris birds of Kotamobagu,Bolaang Mongondow, North Sulawesi. The expected benefits of this research is to provide information on the identification of plumage color and pattern weris birds, useful breeding process.Weris birds in Indonesia consists of several types, based on the results of research conducted in Kotamobagu Bolaang Mongondow North Sulawesi weris got 2 different types of birds that Gallirallus Philipensis and Gallirallus torquatus. Both types of weris birds have different key characters can be seen from theoutside or exterior appearance, that is the difference of colors and patterns. Key words : Weris Birds, Color, and Patterns
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Brom, Tim G. "Microscopic Identification of Feathers and Feather Fragments of Palearctic Birds." Bijdragen tot de Dierkunde 56, no. 2 (1986): 181–204. http://dx.doi.org/10.1163/26660644-05602001.

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Using light microscopy, a method has been developed for the identification of feathers and feather fragments collected after collisions between birds and aircraft. Characters of the downy barbules of feathers are described for 22 orders of birds. The use of a key in combination with the macroscopic method of comparing feathers with bird skins in a museum collection results in identification to order or family level in 97% of the analysed bird strikes. Application of the method to other fields of biological research including taxonomy is discussed.
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Giorgio, Antonella, Salvatore De Bonis, Rosario Balestrieri, Giovanni Rossi, and Marco Guida. "The Isolation and Identification of Bacteria on Feathers of Migratory Bird Species." Microorganisms 6, no. 4 (December 5, 2018): 124. http://dx.doi.org/10.3390/microorganisms6040124.

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Worldwide, bacteria are the most ubiquitous microorganisms, and it has been extensively demonstrated that migratory wild birds can increase bacterial global scale dispersion through long-distance migration and dispersal. The microbial community hosted by wild birds can be highly diverse, including pathogenic strains that can contribute to infections and disease spread. This study focused on feather and plumage bacteria within bird microbial communities. Samples were collected during ornithological activities in a bird ringing station. Bacterial identification was carried out via DNA barcoding of the partial 16S rRNA gene. Thirty-seven isolates of bacteria were identified on the chest feathers of 60 migratory birds belonging to three trans-Saharan species: Muscicapa striata, Hippolais icterina, and Sylvia borin. Our results demonstrate the possibility of bacterial transfer, including pathogens, through bird migration between very distant countries. The data from the analysis of plumage bacteria can aid in the explanation of phenomena such as migratory birds’ fitness or the development of secondary sexual traits. Moreover, these results have deep hygienic–sanitary implications, since many bird species have synanthropic behaviors during their migration that increase the probability of disease spread.
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Torres, Christopher R., Mark A. Norell, and Julia A. Clarke. "Bird neurocranial and body mass evolution across the end-Cretaceous mass extinction: The avian brain shape left other dinosaurs behind." Science Advances 7, no. 31 (July 2021): eabg7099. http://dx.doi.org/10.1126/sciadv.abg7099.

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Birds today are the most diverse clade of terrestrial vertebrates, and understanding why extant birds (Aves) alone among dinosaurs survived the Cretaceous-Paleogene mass extinction is crucial to reconstructing the history of life. Hypotheses proposed to explain this pattern demand identification of traits unique to Aves. However, this identification is complicated by a lack of data from non-avian birds. Here, we interrogate survivorship hypotheses using data from a new, nearly complete skull of Late Cretaceous (~70 million years) bird Ichthyornis and reassess shifts in bird body size across the Cretaceous-Paleogene boundary. Ichthyornis exhibited a wulst and segmented palate, previously proposed to have arisen within extant birds. The origin of Aves is marked by larger, reshaped brains indicating selection for relatively large telencephala and eyes but not by uniquely small body size. Sensory system differences, potentially linked to these shifts, may help explain avian survivorship relative to other dinosaurs.
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Zaugg, Serge, Gilbert Saporta, Emiel van Loon, Heiko Schmaljohann, and Felix Liechti. "Automatic identification of bird targets with radar via patterns produced by wing flapping." Journal of The Royal Society Interface 5, no. 26 (March 10, 2008): 1041–53. http://dx.doi.org/10.1098/rsif.2007.1349.

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Bird identification with radar is important for bird migration research, environmental impact assessments (e.g. wind farms), aircraft security and radar meteorology. In a study on bird migration, radar signals from birds, insects and ground clutter were recorded. Signals from birds show a typical pattern due to wing flapping. The data were labelled by experts into the four classes BIRD, INSECT, CLUTTER and UFO (unidentifiable signals). We present a classification algorithm aimed at automatic recognition of bird targets. Variables related to signal intensity and wing flapping pattern were extracted (via continuous wavelet transform). We used support vector classifiers to build predictive models. We estimated classification performance via cross validation on four datasets. When data from the same dataset were used for training and testing the classifier, the classification performance was extremely to moderately high. When data from one dataset were used for training and the three remaining datasets were used as test sets, the performance was lower but still extremely to moderately high. This shows that the method generalizes well across different locations or times. Our method provides a substantial gain of time when birds must be identified in large collections of radar signals and it represents the first substantial step in developing a real time bird identification radar system. We provide some guidelines and ideas for future research.
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Khatri-Chhetri, Upama, John G. Woods, Ian R. Walker, and P. Jeff Curtis. "Origin identification of migratory pests (European Starling) using geochemical fingerprinting." PeerJ 8 (May 4, 2020): e8962. http://dx.doi.org/10.7717/peerj.8962.

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The European Starling (Sturnidae: Sturnus vulgaris L.) is an invasive bird in North America where it is an agricultural pest. In British Columbia (Canada), the starling population increases in orchards and vineyards in autumn, where they consume and damage ripening fruits. Starlings also cause damage in dairy farms and feedlots by consuming and contaminating food and spreading diseases. Damage can be partly mitigated by the use of scare devices, which can disperse flocks until they become habituated. Large-scale trapping and euthanizing before starlings move to fields and farms could be a practical means of preventing damage, but requires knowledge of natal origin. Within a small (20,831 km2), agriculturally significant portion of south-central British Columbia, the Okanagan-Similkameen region, we used 21 trace elements in bone tissue to discriminate the spatial distribution of juvenile starlings and to reveal the geographic origin of the problem birds in fall. Stepwise discriminant analysis of trace elements classified juveniles to their natal origin (minimum discrimination distance of 12 km) with 79% accuracy. In vineyards and orchards, the majority (55%) of problem birds derive from northern portions of the valley; and the remaining 45% of problem birds were a mixture of local and immigrant/unassigned birds. In contrast, problem birds in dairy farms and feedlots were largely immigrants/unassigned (89%) and 11% were local from northern region of the valley. Moreover, elemental signatures can separate starling populations in the Valley yielding a promising tool for identifying the geographic origin of these migratory birds.
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Yudkin, V. A., and M. A. Grabovski. "QUANTITATIVE METHOD OF ESTIMATE OF AERODROME BIRDS HAZARD RISK." Civil Aviation High TECHNOLOGIES 21, no. 4 (August 28, 2018): 48–59. http://dx.doi.org/10.26467/2079-0619-2018-21-4-48-59.

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The formalized parameters of bird hazard assessment at the aerodrome are presented. The size of total biomass of all birds that are in a zone of aircraft movement reflects the aggregate characteristic of ornithological hazard. This is a dynamic parameter, its dimensionality is kg/hour‧km2. The size of biomass is differentiated on high-altitude layers and the directions of its movement. In addition, it is necessary to estimate activity of each bird species at the aerodrome as component parts of bird hazard. Its dimensionality is individuals/hour‧km2. One more parameter of aerodrome bird hazard in the assessment process of activity of each bird species is the behavior pattern of birds in aerodrome airspace. This parameter will allow to reveal the sources of bird arrivals at the airfield and to detect the causes of it. Assessment of this share is necessary to choose the effective measures to decrease bird strike risk. The birds recording technique at airfield has been designed to obtain quantitative values of main parameters of bird hazard. The birds recording is carried out from the observation points located on the opposite sides of the runway. The birds recording technique is based on visual detection of birds, identification of species, sex and age determination, expert estimate of altitude and direction of their movement. Except the flying birds, the foraging and resting birds on the ground are also considered. The contribution of these birds to the aggregate value of ornithological hazard is bigger than overflying birds. The birds recording technique is described in detail. The norms and frequency of birds recording to obtain data on daily and seasonal dynamics of aerodrome bird hazard are substantiated. The algorithm of processing the results of birds recording and calculation of the main parameters value of bird hazard is stated. Gradations of bird hazard and relevant measures to decrease quantity of birds at airfield are proposed.
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Dissertations / Theses on the topic "Birds – Identification"

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Fox, Elizabeth J. S. "Call-independent identification in birds." University of Western Australia. School of Animal Biology, 2008. http://theses.library.uwa.edu.au/adt-WU2008.0218.

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[Truncated abstract] The identification of individual animals based on acoustic parameters is a non-invasive method of identifying individuals with considerable advantages over physical marking procedures. One requirement for an effective and practical method of acoustic individual identification is that it is call-independent, i.e. determining identity does not require a comparison of the same call or song type. This means that an individuals identity over time can be determined regardless of any changes to its vocal repertoire, and different individuals can be compared regardless of whether they share calls. Although several methods of acoustic identification currently exist, for example discriminant function analysis or spectrographic cross-correlation, none are call-independent. Call-independent identification has been developed for human speaker recognition, and this thesis aimed to: 1) determine if call-independent identification was possible in birds, using similar methods to those used for human speaker recognition, 2) examine the impact of noise in a recording on the identification accuracy and determine methods of removing the noise and increasing accuracy, 3) provide a comparison of features and classifiers to determine the best method of call-independent identification in birds, and 4) determine the practical limitations of call-independent identification in birds, with respect to increasing population size, changing vocal characteristics over time, using different call categories, and using the method in an open population. ... For classification, Gaussian mixture models and probabilistic neural networks resulted in higher accuracy, and were simpler to use, than multilayer perceptrons. Using the best methods of feature extraction and classification resulted in 86-95.5% identification accuracy for two passerine species, with all individuals correctly identified. A study of the limitations of the technique, in terms of population size, the category of call used, accuracy over time, and the effects of having an open population, found that acoustic identification using perceptual linear prediction and probabilistic neural networks can be used to successfully identify individuals in a population of at least 40 individuals, can be used successfully on call categories other than song, and can be used in open populations in which a new recording may belong to a previously unknown individual. However, identity was only able to be determined with accuracy for less than three months, limiting the current technique to short-term field studies. This thesis demonstrates the application of speaker recognition technology to enable call-independent identification in birds. Call-independence is a pre-requisite for the successful application of acoustic individual identification in many species, especially passerines, but has so far received little attention in the scientific literature. This thesis demonstrates that call-independent identification is possible in birds, as well as testing and finding methods to overcome the practical limitations of the methods, enabling their future use in biological studies, particularly for the conservation of threatened species.
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Lau, Hok-nang, and 劉學能. "Identification of novel coronaviruses in dead birds in Hong Kong." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2010. http://hub.hku.hk/bib/B44660108.

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Eakle, Wade Laney 1959. "SONAGRAPHIC IDENTIFICATION OF INDIVIDUAL BREEDING BALD EAGLES (HALIAEETUS LEUCOCEPHALUS) IN ARIZONA." Thesis, The University of Arizona, 1986. http://hdl.handle.net/10150/276369.

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Mead, Reginald Marshall. "A system for automating identification of biological echoes in NEXRAD level II radar data." Thesis, Montana State University, 2009. http://etd.lib.montana.edu/etd/2009/mead/MeadR1209.pdf.

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Since its inception in the mid twentieth century, radar ornithology has provided scientists with new tools for studying the behavior of birds, especially with regards to migration. A number of studies have shown that birds can be detected using a wide variety of radar devices. Generally, these studies have focused on small portable radars that typically have a finer resolution than large weather surveillance radars. Recently, however, a number of researchers have presented qualitative evidence suggesting that birds, or at least migration events, can be identified using large broad scale radars such as the WSR-88D used in the NEXRAD weather surveillance system. This is potentially a boon for ornithologists because NEXRAD data covers a large portion of the country, is constantly being produced, is freely available, and is archived back into the early 1990s. A major obstacle is that identifying birds in NEXRAD data currently requires having a trained technician manually inspect a graphically rendered radar sweep. The immense amount of available data makes manual classification of radar echoes infeasible over any practical span of space or time. In this thesis, a system is presented for automating this process using machine learning techniques. This approach begins with classified training data that has been interpreted by experts or collected from direct observations. The data is preprocessed to ensure quality and to emphasize relevant features. A classifier is then trained using this data and cross validation is used to measure performance. The experiments in this thesis compare neural network, naïve Bayes, and k-nearest neighbor classifiers. Empirical evidence is provided showing that this system can achieve classification accuracies in the 80th to 90th percentile.
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Rogers, Daniel James. "Intraspecific variation in the acoustic signals of birds and one species of frog : implications for the acoustic identification of individuals." Title page, contents and abstract only, 2002. http://web4.library.adelaide.edu.au/theses/09PH/09phr7251.pdf.

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Bibliography: leaves 203-218. This thesis investigated patterns of intraspecific variation in the acoustic signals of a range of vocal animal species with the ultimate objective of demonstrating vocal individuality in these species, focussing on two methods of quantitative song analysis, discriminant function analysis and cross-correlation analysis. Two species were studied: Bibron's toadlet (Pseudophryne bibronii) and Rufous bristlebird (Dasyornis broadbenti).
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Grando, Angélica Paula. "Utilização de tomografia por ressonância magnética nuclear para sexagem de aves silvestres sem dimorfismo sexual." Universidade de São Paulo, 2002. http://www.teses.usp.br/teses/disponiveis/82/82131/tde-07012003-092830/.

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O rápido declínio da vida silvícola do planeta tem levado inúmeros pesquisadores a discutirem diferentes estratégias de conservação, tanto com a manutenção dos animais em seus próprios habitats naturais, como pela propagação em cativeiro. A reprodução de aves em cativeiro é dificultada quando esses animais não apresentam dimorfismo sexual (ausente em muitas espécies, especialmente em psitacídeos), requerendo a realização de métodos de sexagem para a formação de casais. Dessa forma, foi estudado o uso da tomografia por ressonância magnética nuclear (TRMN) para a sexagem de aves silvestres sem dimorfismo sexual, por meio da visualização de seus órgãos reprodutivos. Dez animais da espécie Aratinga leucophthalmus foram anestesiados e submetidos a exames tomográficos. Nas imagens tomográficas adquiridas, pôde-se visualizar os testículos determinando o sexo masculino em aves sexualmente maduras. Entretanto, nas fêmeas, o formato anatômico do ovário esquerdo (provavelmente imaturo) não permitiu que ele fosse caracterizado com precisão por esse método. Para a confirmação dos resultados dos exames tomográficos, foram realizadas análises de polimorfismo de DNA.
The fast decline of wild life on the planet has led innumerable researchers to discuss different conservation strategies by both maintaining animals in their own natural habitat and reproducing in captivity. Reproduction in captivity becomes difficult when these animals do not present sexual dimorphism (absent in many species, specially in psittacines), requiring the use of methods for sex identification to form couples. Thus the use of magnetic resonance imaging (MRI) to identify the sex of birds without sexual dimorphism through the visualization of their reproductive organs has been studied. Ten animals of the Aratinga leucophthalmus species were anaesthetized and subject to tomographic exams. In the tomographic images obtained it was possible to visualize the testicles identifying the male sex in sexually mature birds. However, in the females, the left ovary (possible immaturity) could not be precisely characterized by this method, due to its anatomical shape. To confirm the results of the tomographic exams, analyses of DNA polimorphism were performed.
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Vundavalli, Suveen Kumar, and Sri Rama Srinivasa Varma Danthuluri. "Bird Chirps Annotation UsingTime-Frequency Domain Analysis." Thesis, Blekinge Tekniska Högskola, Institutionen för tillämpad signalbehandling, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-13624.

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There are around 10,426 bird species around the world. Recognizing the bird species for an untrained person is almost impossible either by watching or listening them. In order to identify the bird species from their sounds, there is a need for an application that can detect the bird species from its sound. Time-frequency domain analysis techniques are used to implement the application. We implemented two time-frequency domain feature extraction methods. In feature extraction, a signature matrix which consist of extracted features is created for bird sound signals. A database of signature matrix is created with bird chirps extracted features. We implemented two feature classification methods. They are auto-correlation feature classification method and reference difference feature classification method. An unknown bird chirp is compared with the database to detect the species name. The main aim of the research is to implement the time-frequency domain feature extraction method, create a signature matrix database, implement two feature classification methods and compare them. At last, bird species were identified in the research and the auto-correlation classification method detects the bird species better than the reference difference classification method.
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Zakeri, Masoud. "Automatic bird species identification employing an unsupervised discovery of vocalisation units." Thesis, University of Birmingham, 2017. http://etheses.bham.ac.uk//id/eprint/7833/.

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An automatic analysis of bird vocalisations for the identification of bird species, the study of their behaviour and their means of communication is important for a better understanding of the environment in which we are living and in the context of environmental protection. The high variability of vocalisations within different individuals makes species’ identification challenging for bird surveyors. Hence, the availability of a reliable automatic bird identification system through their vocalisations, would be of great interest to professionals and amateurs alike. A part of this thesis provides a biological survey on the scientific theories of the study of bird vocalisation and corresponding singing behaviours. Another section of this thesis aims to discover a set of element patterns produced by each bird species in a large corpus of the natural field recordings. Also this thesis aims to develop an automatic system for the identification of bird species from recordings. Two HMM based recognition systems are presented in this research. Evaluations have been demonstrated where the proposed element based HMM system obtained a recognition accuracy of over 93% by using 3 seconds of detected signal and over 39% recognition error rate reduction, compared to the baseline HMM system of the same complexity.
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Rizzitelli, Federico. "Design and implementation of BIRDY satellite data and Radiation Payload simulators." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2016.

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Numerical modelling and simulations are needed to develop and test specific analysis methods by providing test data before BIRDY would be launched. This document describes the "satellite data simulator" which is a multi-sensor, multi-spectral satellite simulator produced especially for the BIRDY mission which could be used as well to analyse data from other satellite missions providing energetic particles data in the Solar system.
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Burden, Joanne Jemima Ellen. "Identification and characterisation of a novel intracellular protein that binds the low density lipoprotein (LDL) receptor." Thesis, Imperial College London, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.271420.

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Books on the topic "Birds – Identification"

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Burnie, David. Birds. New York: DK Pub., 2012.

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Irish birds. London: HarperCollins Publishers, 1995.

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Eastern birds. New York: McGraw-Hill, 1988.

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Farrand, John. Western birds. New York: McGraw-Hill, 1988.

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Irish birds. London: HarperCollins, 2004.

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Penny, Meakin, and Goode Douglas, eds. Common birds. Harare, Zimbabwe: Zimbabwe Pub. House, 1994.

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Zim, Herbert S. Birds: A guide to familiar American birds. New York: Golden Press, 1987.

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Seabirds: An identification guide. Boston: Houghton Mifflin Co., 1988.

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Seabirds: An identification guide. London: Christopher Helm, 1989.

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Peter, Harrison. Seabirds, an identification guide. Boston: Houghton Mifflin, 1985.

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Book chapters on the topic "Birds – Identification"

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Lasseck, Mario. "Towards Automatic Large-Scale Identification of Birds in Audio Recordings." In Lecture Notes in Computer Science, 364–75. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-24027-5_39.

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Kale, Vini, and Rajesh Kumar. "Forensic Identification of Birds from Feathers Using Hue and Saturation Histogram." In Communications in Computer and Information Science, 188–95. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-0493-5_17.

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Joly, Alexis, Hervé Goëau, Christophe Botella, Stefan Kahl, Maximillien Servajean, Hervé Glotin, Pierre Bonnet, et al. "Overview of LifeCLEF 2019: Identification of Amazonian Plants, South & North American Birds, and Niche Prediction." In Lecture Notes in Computer Science, 387–401. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-28577-7_29.

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Niemi, Juha, and Juha T. Tanttu. "Automatic Bird Identification for Offshore Wind Farms." In Wind Energy and Wildlife Impacts, 135–51. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-05520-2_9.

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Li, H., J. K. Liu, and Z. R. Lu. "Bird Mating Optimizer in Structural Damage Identification." In Advances in Swarm and Computational Intelligence, 49–56. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-20466-6_5.

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Carvalho, Silvestre, and Elsa Ferreira Gomes. "Automatic Identification of Bird Species from Audio." In Intelligent Information and Database Systems, 41–52. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-73280-6_4.

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Pillai, Sofia K., M. M. Raghuwanshi, and Urmila Shrawankar. "Deep Learning Neural Network for Identification of Bird Species." In Lecture Notes in Networks and Systems, 291–98. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-7150-9_31.

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Villareal Olvera, Toaki Esaú, Caleb Rascón, and Ivan Vladimir Meza Ruiz. "Emotion Based Features of Bird Singing for Turdus migratorius Identification." In Lecture Notes in Computer Science, 521–30. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-45111-9_45.

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Niemi, Juha, and Juha T. Tanttu. "Deep Learning Case Study on Imbalanced Training Data for Automatic Bird Identification." In Deep Learning: Algorithms and Applications, 231–62. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-31760-7_8.

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Surender, M., K. Chandra Shekar, K. Ravikanth, and R. Saidulu. "Automatic Identification of Bird Species from the Image Through the Approaches of Segmentation." In Innovations in Computer Science and Engineering, 203–14. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-7082-3_25.

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Conference papers on the topic "Birds – Identification"

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Bayat, Seda, and Gultekin Isik. "Identification of Aras Birds with Convolutional Neural Networks." In 2020 4th International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT). IEEE, 2020. http://dx.doi.org/10.1109/ismsit50672.2020.9255205.

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Can, Chen, Xiong Yan, and Yan Baoping. "Morphology classification and behaviors identification of birds in scientific video." In 3rd International Conference on Multimedia Technology(ICMT-13). Paris, France: Atlantis Press, 2013. http://dx.doi.org/10.2991/icmt-13.2013.178.

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Karmaker, Debajyoti, Ingo Schiffner, Reuben Strydom, and Mandyam V. Srinivasan. "WHoG: A weighted HoG-based scheme for the detection of birds and identification of their poses in natural environments." In 2016 14th International Conference on Control, Automation, Robotics and Vision (ICARCV). IEEE, 2016. http://dx.doi.org/10.1109/icarcv.2016.7838650.

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Watanabe, Masaji, and Tertia Delia Nova. "Study on Bird Flu Infection Process within a Poultry Farm with Modeling and Simulation." In Modelling, Identification and Control. Calgary,AB,Canada: ACTAPRESS, 2012. http://dx.doi.org/10.2316/p.2012.769-059.

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Blower, Christopher J., and Adam M. Wickenheiser. "The Validation of a Generalized Aerodynamic Model for a Multi-Body Bio-Inspired Wing." In ASME 2013 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/smasis2013-3075.

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Abstract:
Bio-inspiration has introduced new and innovative flow control methods in gust alleviation, maneuverability and stability improvement for morphing aircraft wings. The bio-inspired wing model under consideration imitates the techniques used by birds to manipulate localized air flow through the installation of feather-like panels across the airfoil’s upper and lower surface, replacing the traditional wing’s surface and trailing edge flap. Each flap is designed to rotate into both the airfoil profile and inbound air flow, using a single degree of freedom about their individual hinge points located at 20%, 40%, 60% and 80% of the chord. This wing morphing technique offers flap configurations typically unattainable by traditional aircraft and enables some advantageous maneuvers, including reduced turning radii and aero-braking. Due to the number of potential configurations, a generalized adaptive panel method (APM) has been developed to model the pressure distribution using a series of constant-strength doublets along the airfoil surface. To accommodate for the wake regions generated by the unconventional wing profiles, viscous Computational Fluid Dynamics (CFD) simulations are performed to characterize these regions and identify their outer boundaries. The wake profile geometries are integrated into the APM, and are used to accurately model the aerodynamic influence of the wake. To calculate the drag generated by each configuration, Thwaites’ laminar and Head’s turbulent boundary layer methods are implemented to enable identification of flow transition and separation along the airfoil surface. The integration of these aerodynamic techniques allows the flight characteristics, including the pressure, friction, lift, drag, and moment coefficients, of each morphing airfoil configuration to be calculated. The computed aerodynamic coefficients are validated using experimental data from a 4′×1′×1′ test section in a low speed suction wind tunnel operating over a Reynolds Number range of 150,000–450,000.
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Debnath, Sujoy, Partha Protim Roy, Amin Ahsan Ali, and M. Ashraful Amin. "Identification of bird species from their singing." In 2016 International Conference on Informatics, Electronics and Vision (ICIEV). IEEE, 2016. http://dx.doi.org/10.1109/iciev.2016.7759992.

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Marini, A., A. J. Turatti, A. S. Britto, and A. L. Koerich. "Visual and acoustic identification of bird species." In 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2015. http://dx.doi.org/10.1109/icassp.2015.7178383.

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Ragib, Kazi Md, Raisa Taraman Shithi, Shihab Ali Haq, Md Hasan, Kazi Mohammed Sakib, and Tanjila Farah. "PakhiChini: Automatic Bird Species Identification Using Deep Learning." In 2020 Fourth World Conference on Smart Trends in Systems Security and Sustainablity (WorldS4). IEEE, 2020. http://dx.doi.org/10.1109/worlds450073.2020.9210259.

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Lopes, Marcelo Teider, Alessandro Lameiras Koerich, Carlos Nascimento Silla, and Celso Antonio Alves Kaestner. "Feature set comparison for automatic bird species identification." In 2011 IEEE International Conference on Systems, Man and Cybernetics. IEEE, 2011. http://dx.doi.org/10.1109/icsmc.2011.6083794.

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Sukri, Muhammad Mujjajdid Mohd, Umi Fadlilah, Sharifah Saon, Abd Kadir Mahamad, Mohamad Md Som, and Azmi Sidek. "Bird Sound Identification based on Artificial Neural Network." In 2020 IEEE Student Conference on Research and Development (SCOReD). IEEE, 2020. http://dx.doi.org/10.1109/scored50371.2020.9250746.

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