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Bird Species Image Identification Using Deep Learning

EasyChair Preprint no. 10310

7 pagesDate: May 31, 2023

Abstract

These days, many inexperienced bird watchers have trouble remembering and identifying all the various bird species. Additionally, in order to save and care for diverse bird species, the general public and newly employed rescue team members lack the ability to do so. They have to go through a difficult process to locate large publications like "Birds of the Indian Subcontinent." In this study, we evaluate a deep learning-based AI model that is good at identifying birds from photographs and provide the results. One of the top Deep Learning techniques, Transfer Learning, is used in the study's Simple Web App to recognize photographs. To become more familiar with Google's InceptionV3 model,1000 photos with annotations for each of the 325 different bird species in the dataset. The article presents empirical studies that evaluate different approaches and yield insightful results.

Keyphrases: Bird Identification CNN, deep, ImageNet, InceptionV3, learning

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@Booklet{EasyChair:10310,
  author = {Atharva Kulkarni and Animesh Tade and Suyog Sulke and Sameer Shah and Aparna Pande},
  title = {Bird Species Image Identification Using Deep Learning},
  howpublished = {EasyChair Preprint no. 10310},

  year = {EasyChair, 2023}}
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