Research on variety identification of common bean seeds based on hyperspectral and deep learning.

Accurate, fast and non-destructive identification of varieties of common bean seeds is important for the cultivation and efficient utilization of common beans. This study is based on hyperspectral and deep learning to identify the varieties of common bean seeds non-destructively. In this study, the average spectrum of 3078 hyperspectral images from 500 varieties was obtained after image segmentation and sensitive region extraction, and the Synthetic Minority Over-sampling Technique (SMOTE) was used to achieve the equilibrium of the samples of various varieties.

Semiconductor Multimaterial Optical Fibers for Biomedical Applications.

Integrated sensors and transmitters of a wide variety of human physiological indicators have recently emerged in the form of multimaterial optical fibers. The methods utilized in the manufacture of optical fibers facilitate the use of a wide range of functional elements in microscale optical fibers with an extensive variety of structures. This article presents an overview and review of semiconductor multimaterial optical fibers, their fabrication and postprocessing techniques, different geometries, and integration in devices that can be further utilized in biomedical applications.

Convolutional neural network for apple bruise detection based on hyperspectral.

The timely detection of apple bruises caused by collision and squeeze is of great significance to reduce the economic losses of the apple industry. This study proposed a spectral analysis model (SpectralCNN) based on a one-dimensional convolutional neural network to detect apple bruises. The influences of six spectral preprocessing methods on the SpectralCNN model were firstly analyzed in this paper.

Intelligent detection of hard seeds of snap bean based on hyperspectral imaging.

As a common problem in snap beans, hard seed has seriously affected the large-scale industrial planting and yield of snap bean. To realize accurate, quick and non-destructive identifying the hard seeds of snap bean is of great significance to avoiding the effects of hard seeds on germination and growth. This research was based on hyperspectral imaging (HSI) to achieve accurate detection of hard seeds of snap bean.

Biocompatible and Biodegradable Polymer Optical Fiber for Biomedical Application: A Review.

This article discusses recent advances in biocompatible and biodegradable polymer optical fiber (POF) for medical applications. First, the POF material and its optical properties are summarized. Then, several common optical fiber fabrication methods are thoroughly discussed.

Hyperspectral prediction of sugarbeet seed germination based on gauss kernel SVM.

How to quickly and accurately select sugarbeet seeds with reliable germination is very important to sugarbeet planting. In this study, the hyperspectral images of 3072 sugarbeet seeds of the same variety were collected, and were successively processed by binarization, morphology, contour extraction and so on. The average spectrum of the single seed image was obtained by image segmentation.

Parallel-quadrature on-axis phase-shifting common-path interferometer using a polarizing beam splitter.

A common-path parallel-quadrature on-axis phase-shifting interferometry using a modified Michelson configuration with a polarizing cube beam splitter is proposed for quantitative phase measurement. The frequency spectrum of the circularly polarized object beam is split into two beams using a beam splitter. One beam is converted to a 45° linearly polarized beam to act as the object beam, and the other beam is low-filtered by a pinhole mirror to act as the reference beam.