Overview
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.
Challenge
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.
Approach
Used advanced image annotation techniques, including polygon and bounding box annotation (bbox) following the guidelines at COCO Dataset.
Impact and Results:
- Successful Annotation and Delivery 7,000 images of marine litter in three phases
- Provided a robust dataset within the established timeline
- Integrated environmentally responsible practices into our project approach
- Implemented robust data security measures.
- Supported research and conservation efforts in monitoring and mitigating marine litter.
Key Takeaways
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.
Enhance Your Image Annotation Capabilities with VE3
The success of machine learning models hinges on the quality of data they are trained on, particularly when it comes to high-resolution images. At VE3, we specialize in precise and efficient image annotation services designed to optimize the training of machine learning models. Our advanced techniques ensure that your models are trained on the most accurate data, leading to superior performance and results.
Insights
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