首页|New Artificial Intelligence Study Findings Recently Were Reported by Researchers at Department of Computer Sciences and Engineering (Deep Transfer Learning-base d Automated Identification of Bird Song)
New Artificial Intelligence Study Findings Recently Were Reported by Researchers at Department of Computer Sciences and Engineering (Deep Transfer Learning-base d Automated Identification of Bird Song)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Research findings on Machine Learning - Artificial Intelligence are discussed in a new report. According to news repor ting from Gunupur, India, by NewsRx journalists, research stated, "Bird species identification is becoming increasingly crucial for avian biodiversity conservat ion and assisting ornithologists in quantifying the presence of birds in a given area. Convolutional Neural Networks (CNNs) are advanced deep learning algorithm s that have proven to perform well in speech classification." The news correspondents obtained a quote from the research from the Department o f Computer Sciences and Engineering, "However, developing an accurate deep learn ing classifier requires a large amount of data. Such a large amount of data on e ndemic or endangered creatures is frequently difficult to gathered. Also, in som e other fields, such as bioinformatics and robotics, the high cost of data colle ction and expensive annotation limit their progress, so large, well-annotated da ta creating a set is also difficult. A transfer learning method can alleviate ov erfitting concerns in a deep learning model. This feature serves as the inspirat ion for transfer learning, which was created to deal with situations where the d ata are distributed across a variety of functional domains. In this study, the a bility of deep transfer models such as VGG16, VGG19 and InceptionV3 to effective ly extract and discriminate speech signals from different species of birds with high prediction accuracy is explored."
GunupurIndiaAsiaArtificial Intelli genceMachine LearningDepartment of Computer Sciences and Engineering
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