Marine Litter Image Annotation for ML model training
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Marine Litter Image Annotation for ML model training
VE3 partnered with the Centre for Environment, Fisheries and Aquaculture Science (Cefas) to develop a machine learning algorithm capable of identifying at least 89 marine litter items based on international protocols. To achieve this, approximately 7,000 high-resolution images from beaches were annotated.
Marine litter like plastic bottles, plastic bags, etc. pollutes the ocean and environment. By Annotating and labeling a dataset of images using advanced object detection technology (Machine Learning), litter can be easily detected and hence, dealt with properly, saving the environment from pollution.
Used advanced image annotation techniques, including polygon and bounding box annotation (bbox) following the guidelines at COCO Dataset.
Ensured data integrity through quality assurance and inter-rater assessments.
Managed the project with structured project management and phased delivery schedule.
Complied with environmental regulations and implemented stringent data security measures.
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VE3 successfully addressed the challenge of annotating marine litter images through their expertise, commitment to environmental responsibility, and advanced Data Analytics and Machine Learning technology. Contact VE3 Global for innovative digital solutions with a focus on environmental impact.
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