AIMC Topic: Spectrum Analysis

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A machine learning workflow for raw food spectroscopic classification in a future industry.

Scientific reports Jul 8, 2020
Over the years, technology has changed the way we produce and have access to our food through the development of applications, robotics, data analysis, and processing techniques. The implementation of these approaches by the food industry ensure qual...
Machine Learning Spectrum Analysis Food Industry Raw Foods Workflow Digital Technology
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Role of artificial intelligence and vibrational spectroscopy in cancer diagnostics.

Expert review of molecular diagnostics Jun 27, 2020
INTRODUCTION: Raman and Infrared spectroscopic techniques are being used for the analysis of different types of cancers and other biological molecules. It is possible to identify cancers from normal tissues both in fresh and fixed tissues. These tech...
Spectrum Analysis Neoplasms Spectrum Analysis, Raman Neural Networks, Computer Humans Machine Learning Female Artificial Intelligence Breast Neoplasms
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Automatic diagnosis of melanoma using hyperspectral data and GoogLeNet.

Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI) Jun 25, 2020
BACKGROUND: Melanoma is a type of superficial tumor. As advanced melanoma has a poor prognosis, early detection and therapy are essential to reduce melanoma-related deaths. To that end, there is a need to develop a quantitative method for diagnosing ...
Humans Neural Networks, Computer Spectrum Analysis Machine Learning Melanoma
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Robust Classification of High-Dimensional Spectroscopy Data Using Deep Learning and Data Synthesis.

Journal of chemical information and modeling Mar 16, 2020
This paper presents a new approach to classification of high-dimensional spectroscopy data and demonstrates that it outperforms other current state-of-the art approaches. The specific task we consider is identifying whether samples contain chlorinate...
Algorithms Deep Learning Spectrum Analysis Neural Networks, Computer
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Classification of foodborne bacteria using hyperspectral microscope imaging technology coupled with convolutional neural networks.

Applied microbiology and biotechnology Feb 12, 2020
Foodborne pathogens have become ongoing threats in the food industry, whereas their rapid detection and classification at an early stage are still challenging. To address early and rapid detection, hyperspectral microscope imaging (HMI) technology co...
Food Microbiology Foodborne Diseases Algorithms Image Processing, Computer-Assisted Bacterial Typing Techniques Microscopy Spectrum Analysis Neural Networks, Computer Machine Learning
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New approach in the characterization of bioactive compounds isolated from Calycotome spinosa (L.) Link leaves by the use of negative electrospray ionization LITMS, LC-ESI-MS/MS, as well as NMR analysis.

Bioorganic chemistry Dec 23, 2019
Two novel compounds were isolated for the first time from Calycotome spinosa (L.) Link, an alkaloid 5-Hydroxy-1H-indole (4) and a cyclitol D-pinitol (5), together with the three well-known flavonoids; Chrysin-7-O-(β-D-glucopyranoside) (1), Chrysin-7-...
Genista Plant Extracts Staphylococcus aureus Microbial Sensitivity Tests Antioxidants Plant Leaves Polyphenols Anti-Bacterial Agents Inhibitory Concentration 50 Chromatography, Liquid Spectrum Analysis
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Single spectral imagery and faster R-CNN to identify hazardous and noxious substances spills.

Environmental pollution (Barking, Essex : 1987) Dec 2, 2019
The automatic identification (location, segmentation, and classification) by UAV- based optical imaging of spills of transparent floating Hazardous and Noxious Substances (HNS) benefits the on-site response to spill incidents, but it is also challeng...
Petroleum Pollution Hazardous Substances Water Pollution, Chemical Neural Networks, Computer Spectrum Analysis Hydrocarbons
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Investigating potato late blight physiological differences across potato cultivars with spectroscopy and machine learning.

Plant science : an international journal of experimental plant biology Nov 13, 2019
Understanding plant disease resistance is important in the integrated management of Phytophthora infestans, causal agent of potato late blight. Advanced field-based methods of disease detection that can identify infection before the onset of visual s...
Phytophthora infestans Plant Diseases Machine Learning Remote Sensing Technology Solanum tuberosum Spectrum Analysis Hyperspectral Imaging Plant Leaves
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Extended-wavelength diffuse reflectance spectroscopy with a machine-learning method for in vivo tissue classification.

PloS one Oct 10, 2019
OBJECTIVES: An extended-wavelength diffuse reflectance spectroscopy (EWDRS) technique was evaluated for its ability to differentiate between and classify different skin and tissue types in an in vivo pig model.
Principal Component Analysis Spectrum Analysis Organ Specificity Animals Swine Machine Learning
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Changes of Cerebral Blood Volume During Robot-Assisted Laparoscopic Radical Prostatectomy: Observational Prospective Study Using Near-Infrared Time-Resolved Spectroscopy by Tanaka et al. (From: Tanaka N, Yamamoto M, Abe T, et al. J Endourol 2019;33:995-1001; DOI: 10.1089/end.2019.0217).

Journal of endourology Oct 9, 2019
Humans Prospective Studies Prostatectomy Cerebral Blood Volume Male Laparoscopy Robotics Spectrum Analysis
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