Bird Species Classification in High-Resolution Images

This post is a summary of my challenge participation in the International Conference on Computer Vision & Image Processing (ICCVIP’18). I was the Winner of this Challenge. This challenge involves a supervised classification of bird species from a set of bird images. What’s the catch ??? Let’s find out.

Relevancy of the Problem

From an ecological and environmental point of view, monitoring bird diversity is an important task. While bird monitoring is a well-established process, the observation is largely carried out manually which is time-consuming, and hence the scalability is low. This has motivated the use of machine learning methods to analyze bird images and sounds, using camera-trap data, recorder data or crowd-sourcing. In this challenge, we pose the bird image classification task, especially for Himalayan birds, based on a limited but a diverse set of crowd-sourced data. Especially, the present challenge involves a fairly low amount of labelled data, and may require transfer learning based approaches for effective classification.

Source: Deep Learning on Medium