From 12966abf18fed2c87c18f0d4d7b41f9c6809a83b Mon Sep 17 00:00:00 2001 From: Nathan Hui Date: Wed, 24 Apr 2024 19:40:55 -0700 Subject: [PATCH] fix: Fixes categories --- ...-in-the-peruvian-amazon-using-neural-network-predictions.md | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/_posts/2021-04-30-measuring-bird-presence-in-the-peruvian-amazon-using-neural-network-predictions.md b/_posts/2021-04-30-measuring-bird-presence-in-the-peruvian-amazon-using-neural-network-predictions.md index b6b9631e..25dc7a38 100644 --- a/_posts/2021-04-30-measuring-bird-presence-in-the-peruvian-amazon-using-neural-network-predictions.md +++ b/_posts/2021-04-30-measuring-bird-presence-in-the-peruvian-amazon-using-neural-network-predictions.md @@ -7,8 +7,9 @@ slug: /measuring-bird-presence-in-the-peruvian-amazon-using-neural-network-predi title: Measuring Bird Presence in the Peruvian Amazon Using Neural Network Predictions author: Nathan Hui categories: -- acoustic-species-id - news-and-updates +tags: +- acoustic-species-id --- On April 13th, 2021, the Acoustic Species Identification project lead Jacob Ayers posted a dataset containing the predictions from a Recurrent Neural Network (RNN) trained to estimate the probability of bird presence (global scores) across close to 100,000 audio clips from the Peruvian Amazon. The dataset also contained information about the Audiomoth audio recording devices such as latitudinal and longitudinal coordinates and when each audio clip was created. The Acoustic Species Identification team and its collaborators took on the task of interpreting the dataset and producing different visualizations of their findings.