التفاصيل البيبلوغرافية
| العنوان: |
Earth Camera Network with DAS systems for non-invasive wildlife migration datasets and inter species communication. |
| المؤلفون: |
Dr Bheemaiah Anil K (Kumar) |
| بيانات النشر: |
Zenodo |
| سنة النشر: |
2023 |
| المجموعة: |
Zenodo |
| مصطلحات موضوعية: |
caribou calls, datamining, classification, semiotics |
| الوصف: |
This paper explores the use of machine learning models for understanding and analyzing caribou utterances in the context of conservation and biodiversity. The first section provides an overview of the importance of inter-species communication, specifically focusing on the unique vocalizations of caribou. We discuss the challenges associated with gathering caribou utterance data and present a proposed public dataset of caribou calls and trained utterance models based on observed data. The paper then presents a variety of machine learning models that can be applied to this dataset, including deep learning models such as CNNs and LSTMs, as well as quantum datamining algorithms and sequence-to-sequence algorithms. We discuss potential applications of these models, including the classification of caribou calls and the event-driven triggering of robotics based on caribou calls. The paper also proposes a plan for collecting caribou observation data in the field using Wyze cameras and ATV-based observations. Finally, we suggest future work in the field, including airlifting caribou and creating safe havens for reproduction, as well as scientific consulting on topics such as Miyawaki Pens. Overall, this paper highlights the potential benefits of using machine learning in caribou conservation and biodiversity research, and provides a roadmap for future work in the field. |
| نوع الوثيقة: |
article in journal/newspaper |
| اللغة: |
unknown |
| Relation: |
https://doi.org/10.5281/zenodo.7867542; https://doi.org/10.5281/zenodo.7867543; oai:zenodo.org:7867543 |
| DOI: |
10.5281/zenodo.7867543 |
| الاتاحة: |
https://doi.org/10.5281/zenodo.7867543 |
| Rights: |
info:eu-repo/semantics/openAccess ; Creative Commons Attribution 4.0 International ; https://creativecommons.org/licenses/by/4.0/legalcode |
| رقم الانضمام: |
edsbas.B07927BA |
| قاعدة البيانات: |
BASE |