领学术科研之先,创食品科技之新
—— 中国食品杂志社
期刊集群
Advances in data mining for food flavor analysis: a comprehensive review of techniques, applications and future directions
来源:导入 阅读量: 2 发表时间: 2026-02-10
作者: Qihan Wu, Jiawen Yuan, Jie Zhou, Shuai Yu, Xing Xin, Jin Liu, Xiaohui Cui
关键词: Multimodal deep learning;flavor perception;Convolutional neural network;recurrent neural network
摘要:

Deep learning, a core branch of artificial intelligence, has shown great potential in food flavor analysis, prediction and optimization with its powerful data processing and pattern recognition capabilities. this article reviews deep learning applications in food flavor, discussing various deep learning algorithms and models including artificial neural network, convolutional neural network, recurrent neural network, autoEncoder, graph neural network, and generative adversarial network. besides, the latest progress and development trends of deep learning are discussed in this field. Compared with traditional flavor analysis methods, deep learning methods have obvious advantages and important application prospects in the field of food flavor. With the continuous advancement of technology in the future, it is expected that more deep learning applications will appear in the food industry.

电话: 010-87293157 地址: 北京市丰台区洋桥70号

版权所有 @ 2023 中国食品杂志社 京公网安备11010602060050号 京ICP备14033398号-2