Results 11 to 20 of about 173,502 (284)
GIScience & Remote Sensing, 2020 Rice mapping with remote sensing imagery provides an alternative means for estimating crop-yield and performing land management due to the large geographical coverage and low cost of remotely sensed data.
Shuang Zhao +5 more
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A Novel Weight-Shared Multi-Stage CNN for Scale Robustness [PDF]
, 2019 Convolutional neural networks (CNNs) have demonstrated remarkable results in image classification for benchmark tasks and practical applications. The CNNs with deeper architectures have achieved even higher performance recently thanks to their robustness
Matsubara, Takashi +2 more
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Going Deeper with Dense Connectedly Convolutional Neural Networks for Multispectral Pansharpening
Remote Sensing, 2019 In recent years, convolutional neural networks (CNNs) have shown promising performance in the field of multispectral (MS) and panchromatic (PAN) image fusion (MS pansharpening).
Dong Wang +4 more
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Dynamic-DSO: Direct Sparse Odometry Using Objects Semantic Information for Dynamic Environments
Applied Sciences, 2020 Traditional Simultaneous Localization and Mapping (SLAM) (with loop closure detection), or Visual Odometry (VO) (without loop closure detection), are based on the static environment assumption.
Chao Sheng +4 more
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Open Chemistry, 2023 Ciprofloxacin (CIP) belongs to the fluoroquinolone antibiotic family. It is mostly used for the treatment of bacterial infections and highly recalcitrant to naturally decompose.
Tamyiz Muchammad, Doong Ruey-an
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CNNs Avoid the Curse of Dimensionality by Learning on Patches
IEEE Open Journal of Signal Processing, 2023 Despite the success of convolutional neural networks (CNNs) in numerous computer vision tasks and their extraordinary generalization performances, several attempts to predict the generalization errors of CNNs have only been limited to a posteriori ...
Vamshi C. Madala +2 more
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Botulinum Toxin Suppression of CNS Network Activity In Vitro
Journal of Toxicology, 2014 The botulinum toxins are potent agents which disrupt synaptic transmission. While the standard method for BoNT detection and quantification is based on the mouse lethality assay, we have examined whether alterations in cultured neuronal network activity ...
Joseph J. Pancrazio +3 more
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Recognizing New Classes with Synthetic Data in the Loop: Application to Traffic Sign Recognition
Sensors, 2020 On-board vision systems may need to increase the number of classes that can be recognized in a relatively short period. For instance, a traffic sign recognition system may suddenly be required to recognize new signs.
Gabriel Villalonga +2 more
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A Comprehensive Review on the Application of 3D Convolutional Neural Networks in Medical Imaging
Engineering Proceedings, 2023 Convolutional Neural Networks (CNNs) are kinds of deep learning models that were created primarily for processing and evaluating visual input, which makes them extremely applicable in the field of medical imaging.
Satyam Tiwari +5 more
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Convolutional Neural Networks: A Survey
Computers, 2023 Artificial intelligence (AI) has become a cornerstone of modern technology, revolutionizing industries from healthcare to finance. Convolutional neural networks (CNNs) are a subset of AI that have emerged as a powerful tool for various tasks including ...
Moez Krichen
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