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Lightweight HMMF-Net achieves high accuracy in fish feeding assessment

By PulseAugur Editorial · [1 sources] ·

Researchers have developed HMMF-Net, a novel lightweight network designed for accurate fish feeding intensity assessment in aquaculture. This multimodal architecture effectively combines visual and acoustic data, overcoming limitations of unimodal methods and computationally intensive existing multimodal frameworks. HMMF-Net achieves high accuracy and F1-scores on the AV-FFIA dataset and demonstrates efficient deployment on resource-constrained edge devices like the NVIDIA Jetson Orin Nano. AI

IMPACT Enables more efficient and accurate precision aquaculture through edge-deployable AI.

RANK_REASON Academic paper detailing a new model and its performance. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Lightweight HMMF-Net achieves high accuracy in fish feeding assessment

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Academic paper detailing a new model and its performance. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CV TIER_1 English(EN) · Phi-Hung Hoang, Van-Manh Tran, Nam-Thuan Trinh, Thi-Thu-Hong Phan ·

    HMMF-Net: A Lightweight Hierarchical Multi-Frame Multimodal Fusion Network for Accurate Fish Feeding Intensity Assessment

    arXiv:2611.09224v1 Announce Type: new Abstract: Automated fish feeding intensity assessment (FFIA) is important for precision aquaculture and feed cost optimization. However, unimodal methods are vulnerable to acoustic noise and visual disturbances, while existing multimodal fram…

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