dockship-boat-type-classification-challenge
dockship-boat-type-classification-challenge
Datasets
dockship-boat-type-classification-challenge
File
dockship-boat-type-classification-challenge
Use Case
Computer Vision
Description
Join the Dockship Boat Type Classification Challenge! Use a dataset featuring images of 9 boat types to train models and classify test images accurately.
Overview:
Embark on the Dockship Boat Type Classification Challenge! This challenge tasks participants with accurately classify images into specific boat types using our provided dataset.
Dataset Details: The dataset compose images of nine distinct types of boats, organized within two main List: “TRAIN” and “TEST.” The “TRAIN” List contains 1162 images disjoined by boat type, each locate in its class-labeled folder. The “TEST” list consists of 300 images that participants will classify.
Boat Classes:
- Ferry Boat
- Gondola
- Sailboat
- Cruise Ship
- Kayak
- Inflatable Boat
- Paper Boat
- Buoy
- Freight Boat
Objective: Participants are to classify each image in the “TEST” directory into one of the nine available classes accurately.
Submission Requirements:
Submissions must be consolidated into a single CSV file named ‘output.csv’. This file should contain two columns: “Filename” and “Class.” The first row of the file must be the column headers.
Future Prospects and Industry Impact
Advancements in Autonomous Navigation
The evolution of boat type classification paves the way for autonomous navigation systems capable of making informed decisions based on real-time environmental data and predictive analytics. Autonomous vessels equipped with AI-driven capabilities promise to revolutionize maritime logistics, transportation efficiency, and fleet management.
Collaborative Innovation and Knowledge Sharing
The Dockship – Boat Type Classification Challenge fosters collaborative innovation through knowledge sharing, interdisciplinary research, and industry partnerships. Engaging stakeholders from academia, industry, and government accelerates technological advancements and promotes best practices in AI applications for maritime sustainability and efficiency.
Conclusion
By advancing boat type classification capabilities, this challenge drives innovation, enhances safety measures, and paves the way for sustainable maritime practices in a digitally empowered era.
Contact Us
Quality Data Creation
Guaranteed TAT
ISO 9001:2015, ISO/IEC 27001:2013 Certified
HIPAA Compliance
GDPR Compliance
Compliance and Security
Let's Discuss your Data collection Requirement With Us
To get a detailed estimation of requirements please reach us.