Jellytoring: Real-Time Jellyfish Monitoring Based on Deep Learning Object Detection

During the past decades, the composition and distribution of marine species have changed due to multiple anthropogenic pressures. Monitoring these changes in a cost-effective manner is of high relevance to assess the environmental status and evaluate the effectiveness of management measures. In particular, recent studies point to a rise of jellyfish populations on a global scale, negatively affecting diverse marine sectors like commercial fishing or the tourism industry. Past monitoring efforts using underwater video observations tended to be time-consuming and costly due to human-based data processing. In this paper, we present Jellytoring, a system to automatically detect and quantify different species of jellyfish based on a deep object detection neural network, allowing us to automatically record jellyfish presence during long periods of time. Jellytoring demonstrates outstanding performance on the jellyfish detection task, reaching an F1 score of 95.2%; and also on the jellyfish quantification task, as it correctly quantifies the number and class of jellyfish on a real-time processed video sequence up to a 93.8% of its duration. The results of this study are encouraging and provide the means towards a efficient way to monitor jellyfish, which can be used for the development of a jellyfish early-warning system, providing highly valuable information for marine biologists and contributing to the reduction of jellyfish impacts on humans.

• Publication year

  2020

• Venue

  Italian National Conference on Sensors

• Publication date

  2020-03-01

• Fields of study

  Medicine, Computer Science, Environmental Science

• Identifiers
  DOI 10.3390/s20061708PMID 32204330PMCID 7146330
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

• Mask R-CNN

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  2020cited by this paper
• Deep Learning vs. Traditional Computer Vision

  2019cited by this paper
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  2019cited by this paper
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  2018cited by this paper
• A convolutional neural network for detecting sea turtles in drone imagery

  2018cited by this paper
• JellyMonitor: automated detection of jellyfish in sonar images using neural networks

  2018cited by this paper
• Automated Analysis of Marine Video with Limited Data

  2018cited by this paper
• Sanity Checks for Saliency Maps

  2018cited by this paper
• Trade-offs between sampling effort and data quality in habitat monitoring

  2018cited by this paper
• Identifying animal species in camera trap images using deep learning and citizen science

  2018cited by this paper
• Machine learning for image based species identification

  2018cited by this paper
• Improving Deep Learning using Generic Data Augmentation

  2017cited by this paper
• Applications of machine learning in animal behaviour studies

  2017cited by this paper
• Обнаружение транспортных средств на изображениях загородных шоссе на основе метода Single shot multibox Detector

  2017cited by this paper
• Deep Learning on Underwater Marine Object Detection: A Survey

  2017cited by this paper
• Soft-NMS — Improving Object Detection with One Line of Code

  2017cited by this paper
• Mask R-CNN

  2017cited by this paper
• Feature Pyramid Networks for Object Detection

  2016cited by this paper
• Coral Reef Fish Detection and Recognition in Underwater Videos by Supervised Machine Learning: Comparison Between Deep Learning and HOG+SVM Methods

  2016cited by this paper
• Image-Based Monitoring of Jellyfish Using Deep Learning Architecture

  2016cited by this paper
• Towards automatic wild animal monitoring: Identification of animal species in camera-trap images using very deep convolutional neural networks

  2016cited by this paper
• Accelerating fish detection and recognition by sharing CNNs with objectness learning

  2016cited by this paper
• R-FCN: Object Detection via Region-based Fully Convolutional Networks

  2016cited by this paper
• Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning

  2016cited by this paper
• Plankton classification with deep convolutional neural networks

  2016cited by this paper
• Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

  2015cited by this paper
• You Only Look Once: Unified, Real-Time Object Detection

  2015cited by this paper
• Deep Residual Learning for Image Recognition

  2015influential reference
• Rethinking the Inception Architecture for Computer Vision

  2015cited by this paper
• Fast accurate fish detection and recognition of underwater images with Fast R-CNN

  2015cited by this paper
• SSD: Single Shot MultiBox Detector

  2015cited by this paper
• Fast R-CNN

  2015influential reference
• Going deeper with convolutions

  2014cited by this paper
• Microsoft COCO: Common Objects in Context

  2014cited by this paper
• Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation

  2013influential reference
• Jellyfish as products and problems of aquaculture

  2013cited by this paper
• A comparison of visual‐ and stereo‐video based fish community assessment methods in tropical and temperate marine waters of Western Australia

  2013cited by this paper
• Practical Recommendations for Gradient-Based Training of Deep Architectures

  2012cited by this paper
• On the difficulty of training recurrent neural networks

  2012cited by this paper
• Fatal and nonfatal severe jellyfish stings in Thai waters.

  2010cited by this paper
• The Pascal Visual Object Classes (VOC) Challenge

  2010influential reference
• Object Detection with Discriminatively Trained Part Based Models

  2010cited by this paper
• Cost-efficient sampling of fish assemblages: comparison of baited video stations and diver video transects

  2010cited by this paper
• ImageNet: A large-scale hierarchical image database

  2009cited by this paper
• Prediction, location, collection and transport of jellyfish (Cnidaria) and their polyps.

  2009cited by this paper
• A Global Map of Human Impact on Marine Ecosystems

  2008cited by this paper
• Anthropogenic causes of jellyfish blooms and their direct consequences for humans: a review

  2007cited by this paper
• Loss or gain? Invasive aliens and biodiversity in the Mediterranean Sea.

  2007cited by this paper
• Efficient Non-Maximum Suppression

  2006cited by this paper
• Developing a simple, rapid method for identifying and monitoring jellyfish aggregations from the air

  2006cited by this paper
• Performance Analysis of Intake Screens in Power Plants on Mass Impingement of Marine Organisms

  2006cited by this paper
• Climate Change and Distribution Shifts in Marine Fishes

  2005cited by this paper
• Genetic polymorphism of the adult medusae invading an electric power station and wild polyps of Aurelia aurita in Wakasa Bay, Japan

  2005cited by this paper
• Global trends in world fisheries: impacts on marine ecosystems and food security

  2005cited by this paper
• Histograms of oriented gradients for human detection

  2005cited by this paper
• Impacts of pollution on coastal and marine ecosystems including coastal and marine fisheries and approach for management: a review and synthesis.

  2004cited by this paper
• Distinctive Image Features from Scale-Invariant Keypoints

  2004cited by this paper
• Climate Change, Human Impacts, and the Resilience of Coral Reefs

  2003cited by this paper
• Segmentation methods for visual tracking of deep-ocean jellyfish using a conventional camera

  2003cited by this paper
• In situ quantification and analysis of large jellyfish using a novel video profiler

  2003cited by this paper
• Modification of marine habitats by trawling activities: prognosis and solutions

  2002cited by this paper
• An extended set of Haar-like features for rapid object detection

  2002cited by this paper
• Cost considerations for long-term ecological monitoring

  2001cited by this paper
• A decision-theoretic generalization of on-line learning and an application to boosting

  1997cited by this paper
• Des poissons médusés

  1995cited by this paper
• Support-Vector Networks

  1995cited by this paper
• The Predictive Sample Reuse Method with Applications

  1975cited by this paper

• Domain adaptation and computer vision approaches for robust detection of jellyfish in aquaculture

  2026cites this paper
• Harnessing AI for smarter water management under a changing climate: A review of machine learning and deep learning applications within EU water framework directive and marine strategy framework directive

  2026cites this paper
• Research on a Lightweight Algorithm for Seabed Organism Detection Based on Deep Learning

  2026cites this paper
• Benthos-DETR: a high-precision efficient network for benthic organisms detection

  2025cites this paper
• Advancing animal farming with deep learning: A systematic review

  2025cites this paper
• Jellyfish detection algorithm of underwater image based on TBFRNet and reinforcement learning

  2025cites this paper
• Real-time tracking of recreational boats in coastal areas using deep learning

  2025cites this paper
• Jellyfish mitigation for net-based fisheries: A qualitative systematic review

  2025cites this paper
• A Novel UAV- and AI-Based Remote Sensing Approach for Quantitative Monitoring of Jellyfish Populations: A Case Study of Acromitus flagellatus in Qinglan Port

  2025cites this paper
• Deep Learning-Driven Image Classification of Jellyfish: A CNN Model Approach

  2025influential citation
• Citizen science-based jellyfish observation initiatives in the Mediterranean Sea

  2025cites this paper
• LSJD-YOLO: Lightweight Small Jellyfish Detection Using Enhanced YOLOv11 for Underwater Edge Computing

  2025cites this paper
• Monitoring jellyfish outbreaks along Israel's Mediterranean coast using digital footprints.

  2024cites this paper
• Key environmental parameters and numerical prediction model of jellyfish bloom in Qingchuan Bay Nuclear Power Plant, China.

  2024cites this paper
• An Improved Jellyfish Image Classification Using the EfficientNetB3-Architectured DCNN

  2024cites this paper
• Enhanced deep learning models for automatic fish species identification in underwater imagery

  2024cites this paper
• Using artificial neural networks and citizen science data to assess jellyfish presence along coastal areas

  2024cites this paper
• Comparative Analysis of Jellyfish Classification: A Study Using YOLOv8 and Pre-trained Models

  2024cites this paper
• Real-time precision detection algorithm for jellyfish stings in neural computing, featuring adaptive deep learning enhanced by an advanced YOLOv4 framework

  2024cites this paper
• An intelligent deep residual learning framework for tomato plant leaf disease classification

  2024cites this paper
• Jellyfish detection algorithm based on multi-gradient flow feature fusion

  2024cites this paper
• Animal Behavior Analysis Methods Using Deep Learning: A Survey

  2024cites this paper
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  2024cites this paper
• Real-time jellyfish classification and detection algorithm based on improved YOLOv4-tiny and improved underwater image enhancement algorithm

  2023cites this paper
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  2023cites this paper
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  2023cites this paper
• Deep learning-based visual detection of marine organisms: A survey

  2023cites this paper
• Deep learning based deep-sea automatic image enhancement and animal species classification

  2023cites this paper
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  2023cites this paper
• JF-YOLO: the jellyfish bloom detector based on deep learning

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  2023cites this paper
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  2023cites this paper
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  2023cites this paper
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  2023cites this paper
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  2022cites this paper
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  2022cites this paper
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  2022cites this paper
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  2022cites this paper
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  2022cites this paper
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  2022cites this paper
• Automatic detection of seafloor marine litter using towed camera images and deep learning.

  2021cites this paper
• Impacts of jellyfish on marine cage aquaculture: an overview of existing knowledge and the challenges to finfish health

  2021cites this paper
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  2021cites this paper
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  2021cites this paper
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  2021cites this paper
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  2021cites this paper
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  2020cites this paper
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