Articles with "crop classification" as a keyword



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Crop classification for UAV visible imagery using deep semantic segmentation methods

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Published in 2022 at "Geocarto International"

DOI: 10.1080/10106049.2022.2032387

Abstract: Abstract Unmanned aerial vehicle (UAV) has become a mainstream data collection platform in precision agriculture. For more accessible UAV–visible imagery, the high spatial resolution brings the rich geometric texture features triggered large differences in same… read more here.

Keywords: crop; uav visible; crop classification; visible imagery ... See more keywords
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Satin Bowerbird Optimization With Convolutional LSTM for Food Crop Classification on UAV Imagery

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Published in 2023 at "IEEE Access"

DOI: 10.1109/access.2023.3269806

Abstract: Food crop classification and identification are crucial aspects of modern agriculture. With progression of drones or unmanned aerial vehicles (UAVs), crop detection from RGB images goes through a paradigm shift from traditional image processing methods… read more here.

Keywords: technique; crop; food crop; crop classification ... See more keywords
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CC-SSL: A Self-Supervised Learning Framework for Crop Classification With Few Labeled Samples

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Published in 2022 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"

DOI: 10.1109/jstars.2022.3211994

Abstract: Labeled samples with real crop types are important for crop classification, but the acquisition of large batches of labeled samples will consume many resources, so it is necessary to study crop classification based on few… read more here.

Keywords: crop; crop classification; supervised learning; framework ... See more keywords
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Crop Classification of Multitemporal PolSAR Based on 3-D Attention Module With ViT

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Published in 2023 at "IEEE Geoscience and Remote Sensing Letters"

DOI: 10.1109/lgrs.2023.3270488

Abstract: Multitemporal polarimertic SAR is considered to be very effective in crop classification and cultivated land detection, which has received much attention from researchers. Currently, for most multitemporal polarimetric SAR data classification methods, the simultaneous temporal–polarimetric–spatial… read more here.

Keywords: classification; attention module; crop classification; attention ... See more keywords
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Crop Classification Under Varying Cloud Cover With Neural Ordinary Differential Equations

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Published in 2022 at "IEEE Transactions on Geoscience and Remote Sensing"

DOI: 10.1109/tgrs.2021.3101965

Abstract: Optical satellite sensors cannot see the earth’s surface through clouds. Despite the periodic revisit cycle, image sequences acquired by earth observation satellites are, therefore, irregularly sampled in time. State-of-the-art methods for crop classification (and other… read more here.

Keywords: neural ordinary; crop; classification; crop classification ... See more keywords
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Deep Learning Application for Crop Classification via Multi-Temporal Remote Sensing Images

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Published in 2023 at "Agriculture"

DOI: 10.3390/agriculture13040906

Abstract: The combination of multi-temporal images and deep learning is an efficient way to obtain accurate crop distributions and so has drawn increasing attention. However, few studies have compared deep learning models with different architectures, so… read more here.

Keywords: crop; crop classification; classification; multi temporal ... See more keywords
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Deep Learning Models for the Classification of Crops in Aerial Imagery: A Review

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Published in 2023 at "Agriculture"

DOI: 10.3390/agriculture13050965

Abstract: In recent years, the use of remote sensing data obtained from satellite or unmanned aerial vehicle (UAV) imagery has grown in popularity for crop classification tasks such as yield prediction, soil classification or crop mapping.… read more here.

Keywords: classification; crop classification; imagery; deep learning ... See more keywords
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Enhanced Convolutional-Neural-Network Architecture for Crop Classification

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Published in 2021 at "Applied Sciences"

DOI: 10.3390/app11094292

Abstract: Automatic crop identification and monitoring is a key element in enhancing food production processes as well as diminishing the related environmental impact. Although several efficient deep learning techniques have emerged in the field of multispectral… read more here.

Keywords: methodology; accuracy; architecture; crop classification ... See more keywords
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Gray level co-occurrence matrix (GLCM) texture based crop classification using low altitude remote sensing platforms

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Published in 2021 at "PeerJ Computer Science"

DOI: 10.7717/peerj-cs.536

Abstract: Crop classification in early phenological stages has been a difficult task due to spectrum similarity of different crops. For this purpose, low altitude platforms such as drones have great potential to provide high resolution optical… read more here.

Keywords: crop classification; low altitude; gray level; glcm ... See more keywords