☆ 4.6 Article

Gray whale detection in satellite imagery using deep learning

REMOTE SENSING IN ECOLOGY AND CONSERVATION (2023)

相关参考文献

注意：仅列出部分参考文献，下载原文获取全部文献信息。

Article Computer Science, Information Systems

Object detection using YOLO: challenges, architectural successors, datasets and applications

Tausif Diwan et al.

Summary: Object detection is a significant problem in computer vision, and deep learning has greatly improved its performance. Object detectors can be categorized into two stage and single stage detectors, with two stage detectors typically achieving higher accuracy and single stage detectors having faster inference time. YOLO, a widely adopted single stage object detection algorithm, has the advantage of faster inference speed. This paper provides a comprehensive review of single stage object detectors, particularly YOLO, and compares them with two stage detectors. It also summarizes different versions of YOLO and their applications, as well as future research directions.

MULTIMEDIA TOOLS AND APPLICATIONS (2023)

添加到收藏夹

Article Marine & Freshwater Biology

Individual North Atlantic right whales identified from space

Matus Hodul et al.

Summary: This study demonstrates that satellite imagery can be used to detect and confirm the presence of the critically endangered North Atlantic right whale. It provides another tool for conservation efforts, especially in areas where visual and acoustic methods are not applicable.

MARINE MAMMAL SCIENCE (2023)

添加到收藏夹

Article Computer Science, Hardware & Architecture

Deep learning based whale detection from satellite imagery

Saakshi Kapoor et al.

Summary: Despite their fascinating and vulnerable status, the exact number of whales in the world's oceans is still uncertain due to inaccessible remote areas. Efforts have been made to conserve whale populations, with signs of recovery seen, but a reliable count is necessary to maintain ecological balance. Recently, very high resolution (VHR) satellite imagery combined with deep learning has shown promise in whale detection, but manual detection by observers and limited satellite data have hindered progress. In this study, a deep learning-based automatic whale detection approach was proposed using a dataset of 6000 whale satellite images, resulting in improved precision, recall, and mean average precision compared to previous methods.

SUSTAINABLE COMPUTING-INFORMATICS & SYSTEMS (2023)

添加到收藏夹

Article Engineering, Marine

A Biologist's Guide to the Galaxy: Leveraging Artificial Intelligence and Very High-Resolution Satellite Imagery to Monitor Marine Mammals from Space

Christin B. Khan et al.

Summary: Monitoring marine mammals through VHR satellites can fill knowledge gaps in their distribution in remote locations. The GAIA initiative aims to leverage satellite imagery, cloud computing, and machine learning to enhance our understanding of cetacean distribution. This paper presents lessons learned, challenges faced, and the vision for the future.

JOURNAL OF MARINE SCIENCE AND ENGINEERING (2023)

添加到收藏夹

Article Marine & Freshwater Biology

Use of satellite imagery to identify southern right whales (Eubalaena australis) on a Southwest Atlantic Ocean breeding ground

Audrey A. Correa et al.

Summary: This study used satellite images to identify southern right whales, finding that VHR satellite images performed best in detecting whales and were able to correlate with aerial survey data. This technique may be an important tool for monitoring right whales, especially in countries with limited research funding.

MARINE MAMMAL SCIENCE (2022)

添加到收藏夹

Article Multidisciplinary Sciences

Whales from space dataset, an annotated satellite image dataset of whales for training machine learning models

Hannah C. Cubaynes et al.

Summary: Monitoring whales in remote areas is crucial for conservation, but using traditional survey platforms is difficult. Very high-resolution satellite imagery shows promise, but accurate automated whale detection systems are lacking. This study presents a dataset of 633 annotated whale objects detected in satellite images, creating a valuable resource for training and testing automatic detection systems. The dataset covers four species across various regions and was captured by different high-resolution satellites.

SCIENTIFIC DATA (2022)

添加到收藏夹

Review Multidisciplinary Sciences

Remote sensing techniques for automated marine mammals detection: a review of methods and current challenges

Esteban N. Rodofili et al.

Summary: Marine mammal surveys are important for conservation efforts, but traditional methods can be costly and disturbing to animals. The use of satellite and unmanned aerial systems (UAS) imagery offers potential solutions, but manual counts are time-consuming. This study reviewed automated methods for detecting marine mammals in satellite and UAS imagery and found that convolutional neural networks (CNN) outperformed statistical methods. However, more research is needed to improve the accuracy of automated counts. Thermal infrared UAS imagery and object-based image analysis (OBIA) are potential future avenues for research. Studies have focused on baleen whales and pinnipeds, with a gap in research on toothed whales, polar bears, sirenians, and mustelids.

PEERJ (2022)

添加到收藏夹

Article Multidisciplinary Sciences

Baleen whale prey consumption based on high-resolution foraging measurements

Matthew S. Savoca et al.

Summary: The study demonstrates that the consumption of krill by whales is much larger than previously thought, with some ecosystems underestimating it by threefold or more. By using 3D whale locations and acoustic measurements of prey density, researchers were able to calculate the prey consumption at daily to annual scales, revealing the significant impact of baleen whales on ecosystem function and nutrient recycling. This suggests that the recovery of baleen whales and their nutrient recycling services could potentially enhance productivity and restore lost ecosystem function caused by 20th century whaling.

NATURE (2021)

添加到收藏夹

Article Chemistry, Analytical

The Potential of Satellite Imagery for Surveying Whales

Caroline Hoeschle et al.

Summary: The emergence of very high-resolution (VHR) satellite imagery has opened up new opportunities in the fields of ecology and conservation biology by providing higher confidence in ground feature detection and identification, as well as broadening the range of research questions possible. While VHR imagery studies have mainly focused on terrestrial environments, there has been incremental progress in using this technology for cetacean detection in the last two decades. Collaborative efforts between biology, computation science, and engineering are necessary to overcome the current challenges and achieve basin-scale marine surveys with VHR satellite imagery.

SENSORS (2021)

添加到收藏夹

Review Environmental Sciences

Estimating the Abundance of Marine Mammal Populations

Philip S. Hammond et al.

Summary: This paper provides an overview of methods for estimating marine mammal population abundance, focusing on pinnipeds, cetaceans, and sirenians. Common methods include extrapolation for pinnipeds and transect surveys for cetaceans and sirenians. Key considerations include defining the population, selecting appropriate methods, and understanding the resources needed for data collection and analysis.

FRONTIERS IN MARINE SCIENCE (2021)

添加到收藏夹

Article Multidisciplinary Sciences

Mapping Arctic cetaceans from space: A case study for beluga and narwhal

Bertrand Charry et al.

Summary: This study successfully detected and classified Arctic narwhals and beluga whales using very high-resolution satellite imagery, contributing to our understanding of Arctic cetacean distribution.

PLOS ONE (2021)

添加到收藏夹

Proceedings Paper Computer Science, Software Engineering

Ship Detection in Optical Sensing Images Based on Yolov5

Yuwen Chen et al.

Summary: Ship detection technology is an important development direction in the field of optical remote sensing image processing. The latest model YOLOv5 has shown promising results in ship detection, indicating its potential application in this field.

TWELFTH INTERNATIONAL CONFERENCE ON GRAPHICS AND IMAGE PROCESSING (ICGIP 2020) (2021)

添加到收藏夹

Article Computer Science, Artificial Intelligence

Deep Learning for Generic Object Detection: A Survey

Li Liu et al.

INTERNATIONAL JOURNAL OF COMPUTER VISION (2020)

添加到收藏夹

Article Geography, Physical

Object detection in optical remote sensing images: A survey and a new benchmark

Ke Li et al.

ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING (2020)

添加到收藏夹

Article Veterinary Sciences

Anthropogenic Threats to Wild Cetacean Welfare and a Tool to Inform Policy in This Area

Christine Nicol et al.

FRONTIERS IN VETERINARY SCIENCE (2020)

添加到收藏夹

Article Computer Science, Artificial Intelligence

A survey of the recent architectures of deep convolutional neural networks

Asifullah Khan et al.

ARTIFICIAL INTELLIGENCE REVIEW (2020)

添加到收藏夹

Article Multidisciplinary Sciences

A comparison of baleen whale density estimates derived from overlapping satellite imagery and a shipborne survey

C. C. G. Bamford et al.

SCIENTIFIC REPORTS (2020)

添加到收藏夹

Article Ecology

Spectral reflectance of whale skin above the sea surface: a proposed measurement protocol

Hannah C. Cubaynes et al.

REMOTE SENSING IN ECOLOGY AND CONSERVATION (2020)

添加到收藏夹

Article Ecology

Boom to bust? Implications for the continued rapid growth of the eastern Australian humpback whale population despite recovery

Michael J. Noad et al.

POPULATION ECOLOGY (2019)

添加到收藏夹

Article Ecology

Drones and convolutional neural networks facilitate automated and accurate cetacean species identification and photogrammetry

Patrick C. Gray et al.

METHODS IN ECOLOGY AND EVOLUTION (2019)

添加到收藏夹

Article Multidisciplinary Sciences

Aerial-trained deep learning networks for surveying cetaceans from satellite imagery

Alex Borowicz et al.

PLOS ONE (2019)

添加到收藏夹

Editorial Material Biochemistry & Molecular Biology

Deep learning for environmental conservation

Aakash Lamba et al.

CURRENT BIOLOGY (2019)

添加到收藏夹

Article Multidisciplinary Sciences

Whale counting in satellite and aerial images with deep learning

Emilio Guirado et al.

SCIENTIFIC REPORTS (2019)

添加到收藏夹

Article Marine & Freshwater Biology

Whales from space: Four mysticete species described using new VHR satellite imagery

Hannah C. Cubaynes et al.

MARINE MAMMAL SCIENCE (2019)

添加到收藏夹

Article Marine & Freshwater Biology

Estimating morphometric attributes of baleen whales with photogrammetry from small UASs: A case study with blue and gray whales

Jonathan D. Burnett et al.

MARINE MAMMAL SCIENCE (2019)

添加到收藏夹

Article Computer Science, Theory & Methods

A survey on Image Data Augmentation for Deep Learning

Connor Shorten et al.

JOURNAL OF BIG DATA (2019)

添加到收藏夹

Article Environmental Sciences

Multi-Resolution Feature Fusion for Image Classification of Building Damages with Convolutional Neural Networks

Diogo Duarte et al.

REMOTE SENSING (2018)

添加到收藏夹

Article Environmental Sciences

Drone Up! Quantifying Whale Behavior From a New Perspective Improves Observational Capacity

Leigh G. Torres et al.

FRONTIERS IN MARINE SCIENCE (2018)

添加到收藏夹

Proceedings Paper Computer Science, Artificial Intelligence

Mask R-CNN

Kaiming He et al.

2017 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV) (2017)

添加到收藏夹

Article Oceanography

MANAGING LEVIATHAN Conservation Challenges for the Great Whales in a Post-Whaling World

Phillip J. Clapham

OCEANOGRAPHY (2016)

添加到收藏夹

Article Multidisciplinary Sciences

Whale, Whale, Everywhere: Increasing Abundance of Western South Atlantic Humpback Whales (Megaptera novaeangliae) in Their Wintering Grounds

Guilherme A. Bortolotto et al.

PLOS ONE (2016)

添加到收藏夹

Review Multidisciplinary Sciences

Deep learning

Yann LeCun et al.

NATURE (2015)

添加到收藏夹

Review Ecology

Whales as marine ecosystem engineers

Joe Roman et al.

FRONTIERS IN ECOLOGY AND THE ENVIRONMENT (2014)

添加到收藏夹

Article Multidisciplinary Sciences

Whales from Space: Counting Southern Right Whales by Satellite

Peter T. Fretwell et al.

PLOS ONE (2014)

添加到收藏夹

Article Multidisciplinary Sciences

Global Coverage of Cetacean Line-Transect Surveys: Status Quo, Data Gaps and Future Challenges

Kristin Kaschner et al.

PLOS ONE (2012)

添加到收藏夹

Article Multidisciplinary Sciences

Monitoring Winter and Summer Abundance of Cetaceans in the Pelagos Sanctuary (Northwestern Mediterranean Sea) Through Aerial Surveys

Simone Panigada et al.

PLOS ONE (2011)

添加到收藏夹

Article Multidisciplinary Sciences

DNA evidence for historic population size and past ecosystem impacts of gray whales

S. Elizabeth Alter et al.

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2007)

添加到收藏夹

© Peeref 2019-2024. All rights reserved.