AIMC Topic: Volatile Organic Compounds

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VOC data-driven evaluation of vehicle cabin odor: from ANN to CNN-BiLSTM.

Environmental science and pollution research international Apr 26, 2024
Emissions of volatile organic compounds (VOCs) in vehicles represent a significant problem, causing unpleasant odors. To mitigate VOCs and odors in vehicles, it is critical to choose interior parts with low odor and VOC emissions. However, prevailing...
Neural Networks, Computer Odorants Volatile Organic Compounds Vehicle Emissions Support Vector Machine Gas Chromatography-Mass Spectrometry
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Rapid and non-destructive microbial quality prediction of fresh pork stored under modified atmospheres by using selected-ion flow-tube mass spectrometry and machine learning.

Meat science Mar 31, 2024
Volatile organic compounds (VOCs) indicative of pork microbial spoilage can be quantified rapidly at trace levels using selected-ion flow-tube mass spectrometry (SIFT-MS). Packaging atmosphere is one of the factors influencing VOC production patterns...
Neural Networks, Computer Machine Learning Animals Mass Spectrometry Oxygen Pork Meat Swine Food Microbiology Volatile Organic Compounds Food Packaging Food Storage
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Multichannel Hierarchical Analysis of Time-Resolved Hyperspectral Data for Advanced Colorimetric E-Nose.

ACS sensors Mar 28, 2024
The colorimetric sensor-based electronic nose has been demonstrated to discriminate specific gaseous molecules for various applications, including health or environmental monitoring. However, conventional colorimetric sensor systems rely on RGB senso...
Electronic Nose Colorimetry Volatile Organic Compounds Neural Networks, Computer
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Rapid classification of coffee origin by combining mass spectrometry analysis of coffee aroma with deep learning.

Food chemistry Feb 22, 2024
Mislabeling the geographical origin of coffee is a prevalent form of fraud. In this study, a rapid, nondestructive, and high-throughput method combining mass spectrometry (MS) analysis and intelligence algorithms to classify coffee origin was develop...
Mass Spectrometry Odorants Algorithms Deep Learning Volatile Organic Compounds Coffee
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Artificial Intelligence Sensing: Effective Flavor Blueprinting of Tea Infusions for a Quality Control Perspective.

Molecules (Basel, Switzerland) Jan 23, 2024
Tea infusions are the most consumed beverages in the world after water; their pleasant yet peculiar flavor profile drives consumer choice and acceptance and becomes a fundamental benchmark for the industry. Any qualification method capable of objecti...
Odorants Quality Control Volatile Organic Compounds Smell China Tea Humans Artificial Intelligence
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Characterization of lamb shashliks with different roasting methods by intelligent sensory technologies and GC-MS to simulate human muti-sensation: Based on multimodal deep learning.

Food chemistry Dec 24, 2023
To simulate the functions of olfaction, gustation, vision, and oral touch, intelligent sensory technologies have been developed. Headspace solid-phase microextraction gas chromatography-mass spectrometry (HS-SPME-GC/MS) with electronic noses (E-noses...
Sheep Volatile Organic Compounds Solid Phase Microextraction Electronic Nose Smell Deep Learning Gas Chromatography-Mass Spectrometry Humans Animals
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Affinity Attention Graph Neural Network for Weakly Supervised Semantic Segmentation.

IEEE transactions on pattern analysis and machine intelligence Oct 4, 2022
Weakly supervised semantic segmentation is receiving great attention due to its low human annotation cost. In this paper, we aim to tackle bounding box supervised semantic segmentation, i.e., training accurate semantic segmentation models using bound...
Supervised Machine Learning Attention Volatile Organic Compounds Semantics Algorithms Image Processing, Computer-Assisted Humans Neural Networks, Computer
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Single-Shot Object Detection via Feature Enhancement and Channel Attention.

Sensors (Basel, Switzerland) Sep 10, 2022
Features play a critical role in computer vision tasks. Deep learning methods have resulted in significant breakthroughs in the field of object detection, but it is still an extremely challenging obstacle when an object is very small. In this work, w...
Volatile Organic Compounds Neural Networks, Computer Attention Semantics Records
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The Cognitive Transformation of Japanese Language Education by Artificial Intelligence Technology in the Wireless Network Environment.

Computational intelligence and neuroscience Jul 7, 2022
This study aims to solve the multiscale problems faced by the current classroom student behavior target detection based on the convolutional neural network (CNN) in the wireless network environment. Firstly, the recent reform of Japanese language edu...
Language Algorithms Japan Humans Cognition Volatile Organic Compounds Technology Artificial Intelligence
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Multiple-Attention Mechanism Network for Semantic Segmentation.

Sensors (Basel, Switzerland) Jun 13, 2022
Contextual information and the dependencies between dimensions is vital in image semantic segmentation. In this paper, we propose a multiple-attention mechanism network (MANet) for semantic segmentation in a very effective and efficient way. Concrete...
Volatile Organic Compounds Semantics Neural Networks, Computer Image Processing, Computer-Assisted
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