Results 31 to 40 of about 53,858 (186)
High Throughput Multispectral Image Processing with Applications in Food Science. [PDF]
PLoS ONE, 2015 Recently, machine vision is gaining attention in food science as well as in food industry concerning food quality assessment and monitoring. Into the framework of implementation of Process Analytical Technology (PAT) in the food industry, image ...
Panagiotis Tsakanikas +2 more
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Time and time-frequency analysis of near-infrared signals for the assessment of ozone autohemotherapy long-term effects in multiple sclerosis [PDF]
, 2013 Ozone autohemotherapy is an emerging therapeutic technique that is gaining increasing importance in treating neurological disorders. A validated and standard methodology to assess the effect of such therapy on brain metabolism and circulation is however ...
Franzini, M. +4 more
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Remote Sensing, 2022 The high spectral resolution of hyperspectral images (HSIs) provides rich information but causes data redundancy, which imposes a computational burden on practical applications.
Zhou Zhang +5 more
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Semi-supervised Segmentation Fusion of Multi-spectral and Aerial Images
, 2014 A Semi-supervised Segmentation Fusion algorithm is proposed using consensus and distributed learning. The aim of Unsupervised Segmentation Fusion (USF) is to achieve a consensus among different segmentation outputs obtained from different segmentation ...
Ozay, Mete
core +1 more source
Spatial residual clustering and entropy based ranking for hyperspectral band selection
European Journal of Remote Sensing, 2020 Though the Hyper-spectral images (HSI) are associated with rich spectral information for discriminating the class-specific objects, the high dimensional data generates Hughes effect for additional processing. So, during pre-processing, band Selection (BS)
Kishore Raju K. +2 more
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Remote Sensing, 2020 A comparative study of water indices and image classification algorithms for mapping inland water bodies using Landsat imagery was carried out through obtaining 24 high-resolution (≤5 m) and cloud-free images archived in Google Earth with the same (or ±1
Feifei Pan, Xiaohuan Xi, Cheng Wang
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Discovering the Representative Subset with Low Redundancy for Hyperspectral Feature Selection
Remote Sensing, 2019 In this paper, a novel unsupervised band selection (BS) criterion based on maximizing representativeness and minimizing redundancy (MRMR) is proposed for selecting a set of informative bands to represent the whole hyperspectral image cube.
Wenqiang Zhang +2 more
doaj +1 more source
Sensors, 2022 Hyperspectral imaging can simultaneously acquire spectral and spatial information of the samples and is, therefore, widely applied in the non-destructive detection of grain quality.
Zhen Kang +5 more
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Ambient Sound Provides Supervision for Visual Learning
, 2016 The sound of crashing waves, the roar of fast-moving cars -- sound conveys important information about the objects in our surroundings. In this work, we show that ambient sounds can be used as a supervisory signal for learning visual models.
Freeman, William T. +4 more
core +1 more source
European Journal of Remote Sensing, 2019 Selecting the decisive spectral bands is a key issue in unsupervised hyperspectral band selection techniques. These methods are the most popular ways for dimensionality reduction of original data.
Sarra Ikram Benabadji +5 more
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