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| == The Proof of Value Phase == | | == The Proof of Value Phase == |
− | The project currently is at the proof of value phase. The process for reviewing involves reviewers following their usual routine, where clips relevant to the participating boats from different tows are extracted from the loaded footage into FishVue Interpret and then loaded into the Proof of Concept solution. The reviewer is tasked with selecting at least 3 to 5 images from each tow for catch apportionment analysis. Afterward, they will review these catch apportionment results, utilizing them to inform and make more accurate catch estimates. Moreover, a sample of tows will undergo a full manual review. This step is crucial as it allows for the assessment of the impact on the accuracy of the catch estimates. | + | The project currently is in the proof of value phase. The process for reviewing involves reviewers following their usual routine, where clips relevant to the participating boats from different tows are extracted from the loaded footage into FishVue Interpret and then loaded into the Proof of Concept solution. The reviewer is tasked with selecting at least 3 to 5 images from each tow for catch apportionment analysis. Afterward, they will review these catch apportionment results, utilizing them to inform and make more accurate catch estimates. Moreover, a sample of tows will undergo a full manual review. This step is crucial as it allows for the assessment of the impact on the accuracy of the catch estimates. |
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− | * The Key Performance Indicators (KPIs) for the Proof of Value phase include the following:
| + | The POV phase will be conducted in 2 iterations to facilitate an opportunity for incorporation of feedback on either algorithm or user interface performance.The Key Performance Indicators (KPIs) for the Proof of Value phase include the following: |
− | * Number of catch apportionment results rejected by reviewers (single images) | + | |
− | * Number of total catch apportionment results rejected by reviewers (tows) | + | * Number of catch apportionment results rejected by reviewers (single images). |
− | * Accuracy of catch apportionment (deviation compared with manual review) | + | * Number of total catch apportionment results rejected by reviewers (tows). |
− | * Delta in results between first and second iterations | + | * Accuracy of catch apportionment (deviation compared with manual review). |
− | * Change in administrative user feedback between iterations if any UI/UX adjustments are made | + | * Delta in results between first and second iterations. |
| + | * Change in administrative user feedback between iterations if any UI/UX adjustments are made. |
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| == Next Steps == | | == Next Steps == |
− | Following the success of both the proof of concept and the proof of value, DFO plans to promote the AI-assisted solution for Pacific trawl fisheries into production in the fiscal years 2023-2024. Furthermore, the department is planning another pilot project for the use of AI in Snow Crab fisheries in the Quebec region. | + | Following the successful completion of both the proof of concept and the proof of value, the Department of Fisheries and Oceans (DFO) has plans to promote the AI-assisted solution for Pacific trawl fisheries into production in the fiscal years 2023-2024. In addition, the department is also planning another pilot project for the application of AI to monitor Snow Crab fisheries in the Quebec region. |