Assessing the Quality of Dried Squid
该研究利用高光谱成像结合深度学习方法(1D-KAN-CNN)对干鱿鱼进行无损质量检测,通过分析可见近红外光谱数据评估脂肪、蛋白质和挥发性氮含量。 2025-9-12 21:5:12 Author: www.schneier.com(查看原文) 阅读量:1 收藏

Research:

Nondestructive detection of multiple dried squid qualities by hyperspectral imaging combined with 1D-KAN-CNN

Abstract: Given that dried squid is a highly regarded marine product in Oriental countries, the global food industry requires a swift and noninvasive quality assessment of this product. The current study therefore uses visiblenear-infrared (VIS-NIR) hyperspectral imaging and deep learning (DL) methodologies. We acquired and preprocessed VIS-NIR (4001000 nm) hyperspectral reflectance images of 93 dried squid samples. Important wavelengths were selected using competitive adaptive reweighted sampling, principal component analysis, and the successive projections algorithm. Based on a Kolmogorov-Arnold network (KAN), we introduce a one-dimensional, KAN convolutional neural network (1D-KAN-CNN) for nondestructive measurements of fat, protein, and total volatile basic nitrogen….

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Posted on September 12, 2025 at 5:05 PM0 Comments

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