Development and application of marine exploration and ecological survey technologies under climate change

Introduction

The technology can already use object detectors to correctly recognize lobsters, then count and track them.

The accuracy of the model can reach 99.5%.

Movie 1 is the actual field verification result.

Location: Kenting South Bay

Filming time: 2022.03.25

(2)Coral ecosystem analysis: Automated live coral cover analysis

Based on YOLACT, a sample segmentation algorithm released in 2019, this technology can automatically classify eight substrates from the internationally recognized Reef Check method.

The classification accuracy can reach 93.1%.

Movie 2 is the actual field verification result.

Location: Kenting South Bay

Filming time: 2022.01.26 ~ 2022.01.27

(3)Coral ecosystem analysis: Indicator biological classification 

This technique assesses the ecological development of a coral area by observing its biological species.

The technology can use to classify a variety of indicator fishes and invertebrates.

The classification accuracy can reach 90%.

Movie 3 is the actual field verification result.

Location: Keelung Chaojing Park

Filming time: 2022.05

團隊已於Github提出“AI-series-on-Aquatic-Creatures-Part1_Counting”之水下生物之AI計數應用技術,此技術為可針對龍蝦之物件偵測器。 相關下載檔連結:https://github.com/softcomputinglab520/AI-series-on-Aquatic-Creatures-Part1_Counting


Keywords : Artificial Intelligence Underwater Creatures Coral Underwater Ecological Survey Marine Conservation
Research Project : Development and Application of Marine Exploration and Ecological Survey Technologies under Climate Change
Principal Investigator : Kuo-Ping Chiang
Co-Principal Investigator : Kuo-Ping Chiang