Automatic detection of flying bird species using computer vision techniques
Bird population is an important factor that may affect ecology of the an area. The main aim is to create a solution for counting different species of birds present in an area and classify them into categories. There are around 1300 species of birds found in India and there can be chance that a new s...
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Published in | Journal of physics. Conference series Vol. 1362; no. 1; pp. 12112 - 12118 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
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Bristol
IOP Publishing
01.11.2019
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Abstract | Bird population is an important factor that may affect ecology of the an area. The main aim is to create a solution for counting different species of birds present in an area and classify them into categories. There are around 1300 species of birds found in India and there can be chance that a new species which remained unidentified till now. We can calculate the number of bird species available in a locality and keep a track whether any species are in risk of being endangered. Calculating the bird population can help the ecologist to search the problem which may endanger them. Manual labor for counting and searching for new species is time consuming and error prone. In the present work, The method of solution is to create a computer vision system using machine learning techniques or deep learning method for a better accurate results. Automatic Bird detection system is primarily useful in providing optimal bird count in region with counting, the system also classifies the bird based upon its species and features.after detecting the bird, the segregates the data according to the bird's features. This data which is stored in the database can be accessed by scientists, photographers, and also by surveying units as this data provides important information about the number of birds in the area, the type of birds, Their features, and also this data helps scientists in predicting the environmental changes in the particular area by analysing the type of birds visiting the area based upon seasonal changes. |
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AbstractList | Abstract
Bird population is an important factor that may affect ecology of the an area. The main aim is to create a solution for counting different species of birds present in an area and classify them into categories. There are around 1300 species of birds found in India and there can be chance that a new species which remained unidentified till now. We can calculate the number of bird species available in a locality and keep a track whether any species are in risk of being endangered. Calculating the bird population can help the ecologist to search the problem which may endanger them. Manual labor for counting and searching for new species is time consuming and error prone. In the present work, The method of solution is to create a computer vision system using machine learning techniques or deep learning method for a better accurate results. Automatic Bird detection system is primarily useful in providing optimal bird count in region with counting, the system also classifies the bird based upon its species and features.after detecting the bird, the segregates the data according to the bird’s features. This data which is stored in the database can be accessed by scientists, photographers, and also by surveying units as this data provides important information about the number of birds in the area, the type of birds, Their features, and also this data helps scientists in predicting the environmental changes in the particular area by analysing the type of birds visiting the area based upon seasonal changes. Bird population is an important factor that may affect ecology of the an area. The main aim is to create a solution for counting different species of birds present in an area and classify them into categories. There are around 1300 species of birds found in India and there can be chance that a new species which remained unidentified till now. We can calculate the number of bird species available in a locality and keep a track whether any species are in risk of being endangered. Calculating the bird population can help the ecologist to search the problem which may endanger them. Manual labor for counting and searching for new species is time consuming and error prone. In the present work, The method of solution is to create a computer vision system using machine learning techniques or deep learning method for a better accurate results. Automatic Bird detection system is primarily useful in providing optimal bird count in region with counting, the system also classifies the bird based upon its species and features.after detecting the bird, the segregates the data according to the bird’s features. This data which is stored in the database can be accessed by scientists, photographers, and also by surveying units as this data provides important information about the number of birds in the area, the type of birds, Their features, and also this data helps scientists in predicting the environmental changes in the particular area by analysing the type of birds visiting the area based upon seasonal changes. |
Author | Balachandran, Adithya Deenadayalan, G. Jadhav, Sheetal P Vishnuvardhan, R. Vijaya Gopala Rao, M.V. |
Author_xml | – sequence: 1 givenname: R. surname: Vishnuvardhan fullname: Vishnuvardhan, R. organization: Department of Mechatronics engineering, Sri Krishna College of engineering and technology , India – sequence: 2 givenname: G. surname: Deenadayalan fullname: Deenadayalan, G. organization: Department of Mechanical Engineering, Hindustan Institute of Technology and Science , India – sequence: 3 givenname: M.V. surname: Vijaya Gopala Rao fullname: Vijaya Gopala Rao, M.V. organization: Department of Mechanical Engineering, Hindustan Institute of Technology and Science , India – sequence: 4 givenname: Sheetal P surname: Jadhav fullname: Jadhav, Sheetal P organization: Department of Mechanical Engineering, Hindustan Institute of Technology and Science , India – sequence: 5 givenname: Adithya surname: Balachandran fullname: Balachandran, Adithya organization: Department of Mechanical Engineering, Hindustan Institute of Technology and Science , India |
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Copyright | Published under licence by IOP Publishing Ltd 2019. This work is published under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. |
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References | (JPCS_1362_1_012112bib6) 2019; 1 Vishnuvardhan (JPCS_1362_1_012112bib4); 9 Sivakumar (JPCS_1362_1_012112bib3) 2019; 27 O’Brien (JPCS_1362_1_012112bib1) 2008; 18 Niem (JPCS_1362_1_012112bib2) Borhan (JPCS_1362_1_012112bib5) 2019; 1 |
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Snippet | Bird population is an important factor that may affect ecology of the an area. The main aim is to create a solution for counting different species of birds... Abstract Bird population is an important factor that may affect ecology of the an area. The main aim is to create a solution for counting different species of... |
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SubjectTerms | Animal populations Birds Computer vision Counting Deep learning Machine learning Mathematical analysis Physical work Physics Scientists Seasonal variations Vision systems |
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Title | Automatic detection of flying bird species using computer vision techniques |
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