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为食品科学家构建人工智能的实用指南:数据,算法和应用
1Department of Food Science and Technology, Faculty of Science, National University of Singapore, 2 Science Drive 2, Singapore 117542, Singapore; National University of Singapore (Suzhou) Research Institute, 377 Lin Quan Street, Suzhou Industrial Park, Jiangsu 215123, China.
Food chemistry
|December 1, 2025
概括
在食品科学中采用人工智能 (AI) 需要高质量的数据,定制的算法和有影响力的应用. 这本指南有助于食品科学家构建有效的AI创新模型.
科学领域:
- 食品科学 食品科学 食品科学
- 人工智能的人工智能
- 数据科学数据科学数据科学
背景情况:
- 在食品科学中采用人工智能是分散的.
- 当前的人工智能应用程序的范围通常是有限的.
- 可持续的进步需要一个多支柱的方法.
研究的目的:
- 为食品科学家提供实用指南,帮助他们构建有效的AI模型.
- 概述人工智能在食品科学中的三个基本支柱:数据,算法和应用.
- 提出AI模型开发和部署的检查清单.
主要方法:
- 讨论与食品科学相关的最先进的AI方法.
- 强调高质量的数据集的重要性.
- 强调量身定制的算法和有影响力的应用.
主要成果:
- 人工智能可以推动食品科学领域的新科学见解和工业价值.
- 特定的人工智能方法,如LLMs,高吞吐量平台,PINNs和多式联络融合是适用的.
- 对人工智能开发的结构化方法至关重要.
结论:
- 推进数据,算法和应用程序是人工智能在食品科学领域的关键.
- 拟议的检查清单可以指导AI模型的规划,开发,评估和部署.
- 将未来的工作与这些支柱结合起来,将加速人工智能驱动的食品领域的发现和创新.
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