Abstract

Advancements in technology, particularly in the field of artificial intelligence (AI), have opened new avenues for solving complex biological and ecological challenges. Among these, deep learning has emerged as a powerful tool for image-based classification tasks. Convolutional Neural Networks (CNNs), a subset of deep learning algorithms, are especially effective in recognizing patterns and extracting features from images. This capability makes CNNs highly suitable for applications in bird species identification. By leveraging deep learning techniques, researchers and conservationists can automate the identification process, reducing human effort and significantly improving accuracy.