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Harnessing the Power of Deep Learning to Save Animals
2017
International Journal of Computer Applications
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system more efficient and optimized .This paper discusses the expansion of deep learning towards the welfare of animal life considering ways to save them and monitoring their count and health conditions ...
Techniques like image classification and object detection can provide plethora of information that can assist in conducting study on various aspects by identifying and classifying these animal species ...
Using deep learning neural network model trained with these collected images and videos can track, pinpoint and even predict the paths of animals, vehicles and poachers, learning more and more as time ...
doi:10.5120/ijca2017915864
fatcat:oshzl7ry5jgk5lxca2utrpwdx4
Phase 4: DCL System Using Deep Learning Approaches for Land-Based or Ship-Based Real-Time Recognition and Localization of Marine Mammals - Distributed Processing and Big Data Applications
[article]
2016
arXiv
pre-print
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Detection-classification for passive acoustics is a data-mining strategy and our goals are aligned with best practices that appeal to the general data mining and machine learning communities where the ...
With this basic deficiency recognized at the forefront, portions of the grant were dedicated to fostering deep-learning by way of international competitions (kaggle.com) meant to attract deep-learning ...
to support large amounts of data required for deep recognition and other advanced technologies. ...
arXiv:1605.00982v2
fatcat:h2yvqur3srhulotr5bju3yoho4
Setting the stage for the machine intelligence era in marine science
2020
ICES Journal of Marine Science
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The rapidly developing machine learning subfield known as deep learning—which applies algorithms (artificial neural networks) inspired by the structure and function of the brain—is able to solve very complex ...
It has significant advantages compared with manual analyses that are labour intensive and require considerable time. ...
Acknowledgements We are grateful to the authors for their enthusiasm and engagement in this initiative. ...
doi:10.1093/icesjms/fsaa084
fatcat:zwzvuhlpmbb7bi2lv6xhtg52lm
Marine Organism Detection and Classification from Underwater Vision Based on the Deep CNN Method
2020
Mathematical Problems in Engineering
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The detection runs with a speed of 17 fps on a GPU, which is applicable to be used for real-time processing. ...
This research is based on the deep convolutional neural network (CNN) to realize the target recognition from underwater vision. ...
framework is named "deep learning." ...
doi:10.1155/2020/3937580
fatcat:qvmvhzauybhafgu5prmaqij2qq
Automated Video Surveillance for the Study of Marine Mammal Behavior and Cognition
2016
Animal Behavior and Cognition
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Advances in boat-based, aerial, and underwater recording platforms provide opportunities to document the behavior of marine mammals and create massive datasets. ...
Systems for detecting and tracking social marine mammals, including dolphins, can provide data to help explain their social dynamics, predict their behavior, and measure the impact of human interference ...
Working with aerial photos, recent advances in deep learning have allowed for even more effective automated identification. ...
doi:10.12966/abc.05.11.2016
fatcat:4pbtwqjxmfamdhfqc7bluktdk4
Fish species recognition using transfer learning techniques
2021
IJAIN (International Journal of Advances in Intelligent Informatics)
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of marine animals. ...
To overcome this problem, we propose a transfer learning technique using a pre-trained model that uses underwater fish images as input and applies a transfer learning technique to detect the fish species ...
Acknowledgment The authors would like to thank the management of VIT University, Vellore, India, and SSN College of Engineering, Chennai India, for funding the respective research labs where the research ...
doi:10.26555/ijain.v7i2.610
fatcat:g7t3j2bddrdhdokcj2jwtqxh7m
Automating the Analysis of Fish Abundance Using Object Detection: Optimizing Animal Ecology With Deep Learning
2020
Frontiers in Marine Science
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Deep learning methods provide a faster, cheaper, and more accurate alternative to manual data analysis methods currently used to monitor and assess animal abundance and have much to offer the field of ...
We produced three models using an object detection framework to detect the target species, an ecologically important fish, luderick (Girella tricuspidata). ...
Although recent advances in deep learning can make image analysis for animal ecology more efficient, there are still some ecological and environmental limitations. ...
doi:10.3389/fmars.2020.00429
fatcat:4bzybb4j3fcvzbsdtwddzewsci
Phase 2: DCL System Using Deep Learning Approaches for Land-based or Ship-based Real-Time Recognition and Localization of Marine Mammals - Machine Learning Detection Algorithms
[article]
2016
arXiv
pre-print
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Two primary goals are to develop transferable technologies for detection and classification in, one: the area of advanced algorithms, such as deep learning and other methods; and two: advanced systems, ...
Overarching goals for this work aim to advance the state of the art for detection, classification and localization (DCL) in the field of bioacoustics. ...
Yann LeCun's group at NYU, is focused on basic research and development for applying deep learning technologies to detect and classify underwater sounds in real-time. ...
arXiv:1605.00972v2
fatcat:pfpynxuubjg6jn3msiq3iqw3p4
Transferring deep knowledge for object recognition in Low-quality underwater videos
2018
Neurocomputing
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Even with the insufficient training set, the transfer framework can well learn a recognition model for the special underwater object recognition task together with the help of data augmentation. ...
In recent years, underwater video technologies allow us to explore the ocean in scientific and noninvasive ways, such as environmental monitoring, marine ecology studies, and fisheries management. ...
Real time object recognition framework 3.1 Offline deep CNN model via transfer learning A key advantage of Deep Learning is its ability of learning stable and robust features from massive amounts of data ...
doi:10.1016/j.neucom.2017.09.044
fatcat:zety2uy5lbhhpd6sabfafyfrdi
Computer Vision and Deep Learning for Fish Classification in Underwater Habitats: A Survey
[article]
2022
arXiv
pre-print
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A promising method to address this problem is the cutting-edge Deep Learning (DL) technology.DL can help marine scientists parse large volumes of video promptly and efficiently, unlocking niche information ...
Finally, we provide insights into the marine habitat monitoring research domain and shed light on what the future of DL for underwater image processing may hold. ...
This facilitates monitoring underwater fish and can advance marine studies concerned with fish ecology. ...
arXiv:2203.06951v2
fatcat:oacfgeo5evanpatgnlq2hhne4y
Automating the analysis of fish abundance using object detection: optimising animal ecology with deep learning
[article]
2019
bioRxiv
pre-print
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Deep learning methods provide a faster, cheaper and more accurate alternative to manual data analysis methods currently used to monitor and assess animal abundance. ...
We produced three models using a MaskR-CNN object detection framework to detect the target species, an ecologically important fish, luderick (Girella tricuspidata). ...
, counting, and describing wild animals in camera-trap 515 images with deep learning. ...
doi:10.1101/805796
fatcat:bvvatkrusfgn3kg66yeyayfeka
Perspectives on individual animal identification from biology and computer vision
2021
Integrative and Comparative Biology
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Here, we review current advances of computer vision identification techniques to provide both computer scientists and biologists with an overview of the available tools and discuss their applications. ...
We conclude by offering recommendations for starting an animal identification project, illustrate current limitations and propose how they might be addressed in the future. ...
Two methods have been widely used for animal identification with deep learning: classification and metric learning. ...
doi:10.1093/icb/icab107
pmid:34050741
pmcid:PMC8490693
fatcat:zp32mrr56fcvda4ubc3r2xotja
Applications for deep learning in ecology
[article]
2018
bioRxiv
pre-print
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A lot of hype has recently been generated around deep learning, a group of artificial intelligence approaches able to break accuracy records in pattern recognition. ...
We also provide guidelines on useful resources and recommendations for ecologists to start adding deep learning to their toolkit. ...
Phase 2: DCL system using deep learning approaches for land-based or ship-based real-time recognition and localization of marine mammals -machine learning detection algorithms. ...
doi:10.1101/334854
fatcat:f35v3u7z5zdjrjccu32uhqwfvu
A Literature Review of Underwater Image Detection
[chapter]
2022
Frontiers in Artificial Intelligence and Applications
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In this paper, first of all introduces the existing research of underwater target image recognition, mainly presents the underwater image recognition technology based on deep learning. ...
Besides, the future development of underwater image recognition technology and its application in wisdom fishery is also discussed, which provides other scholar with some theoretical help and a comprehensive ...
With the emergence of R-CNN, deep learning began to develop rapidly in object recognition and detection, and a group of scholars emerged to apply deep learning to underwater image recognition research, ...
doi:10.3233/faia220009
fatcat:ynod4ci7tvaitnwvgcmljfxix4
Phase 1: DCL System Research Using Advanced Approaches for Land-based or Ship-based Real-Time Recognition and Localization of Marine Mammals - HPC System Implementation
[article]
2016
arXiv
pre-print
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The two primary goals are to develop transferable technologies for detection and classification in: (1) the area of advanced algorithms, such as deep learning and other methods; and (2) advanced systems ...
We aim to investigate advancing the state of the art of detection, classification and localization (DCL) in the field of bioacoustics. ...
NOPP -DCL Stellwagen Bank National Marine Sanctuary, development of pulse train detection, animal vs noise (see example in this report). ...
arXiv:1605.00971v2
fatcat:q2dbjwat6baqxhn632kh4lbpim
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