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Bird Species Identification Using Deep Learning and Image Processing

EasyChair Preprint no. 8319

6 pagesDate: June 19, 2022


A Bird watching is a recreational activity that can provide relaxation in daily life and promote resilience to face daily challenges. It can also offer health benefits and happiness derived from enjoying nature. Identification of bird and insect’s species is a challenging task often resulting in ambiguous labels. Even professional bird and insect watchers sometimes disagree on thespecies given an image of a bird and insect. It is a difficult problem that pushes the limitsof the visual abilities for both humans and computers. Although different bird and insectspecies share the same basic set of parts, different bird and insect species can vary in shape and appearance. Interclass variance is high due to variation in lighting and background and extreme variation in pose. Neural Network (NN)- Neural network has a gained a great attention. It is known that, mammal’s brain, which consists of many interconnected neurons, that can deal with complex and computational tasks, like face recognition, body motion, and muscles activities control.

Keyphrases: feature extraction, Histogram of Oriented Gradient, image processing, Neural Networking, Test train and accuracy

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Deepthi Jha and Meenakshi Sundaram},
  title = {Bird Species Identification Using Deep Learning and Image Processing},
  howpublished = {EasyChair Preprint no. 8319},

  year = {EasyChair, 2022}}
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