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  • Open Access


    Machine Vision Based Fish Cutting Point Prediction for Target Weight

    Yonghun Jang, Yeong-Seok Seo*

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 2247-2263, 2023, DOI:10.32604/cmc.2023.027882

    Abstract Food processing companies pursue the distribution of ingredients that were packaged according to a certain weight. Particularly, foods like fish are highly demanded and supplied. However, despite the high quantity of fish to be supplied, most seafood processing companies have yet to install automation equipment. Such absence of automation equipment for seafood processing incurs a considerable cost regarding labor force, economy, and time. Moreover, workers responsible for fish processing are exposed to risks because fish processing tasks require the use of dangerous tools, such as power saws or knives. To solve these problems observed in the fish processing field, this… More >

  • Open Access


    Weight Prediction Using the Hybrid Stacked-LSTM Food Selection Model

    Ahmed M. Elshewey1, Mahmoud Y. Shams2,*, Zahraa Tarek3, Mohamed Megahed4, El-Sayed M. El-kenawy5, Mohamed A. El-dosuky3,6

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 765-781, 2023, DOI:10.32604/csse.2023.034324

    Abstract Food choice motives (i.e., mood, health, natural content, convenience, sensory appeal, price, familiarities, ethical concerns, and weight control) have an important role in transforming the current food system to ensure the healthiness of people and the sustainability of the world. Researchers from several domains have presented several models addressing issues influencing food choice over the years. However, a multidisciplinary approach is required to better understand how various aspects interact with one another during the decision-making procedure. In this paper, four Deep Learning (DL) models and one Machine Learning (ML) model are utilized to predict the weight in pounds based on… More >

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