Title : IDENTIFY THE BEEHIVE SOUND USING DEEP LEARNING
Author : G.Prabhakar, N.Savitha, Ameena nasreen
Abstract :
Flowers are necessary to purge the dreary air. The life cycle of flowering plants includes many stages, such as pollination, fertilization, blooming, seed development, dispersal, and germination. Approximately 75% of all blooming plants are pollinated by honeybees. Honeybee populations are steadily declining due to threats to their natural habitats from environmental pollution, climate change, the destruction of natural landscapes, and other factors. Consequently, some scholars are working to find a solution. Variations in recordings of beehive noises may be found using acoustic categorization. To distinguish bee sounds from non-beehive noises, we use deep learning techniques—specifically, Sequential Neural Network, Convolutional Neural Network, and Recurrent Neural Network—to the recorded sounds in this study. We also compare the deep learning methods with other well-known non-deep learning methods, such as Random Forest, Naïve Bayes, Support Vector Machine, and Decision Tree. Th
