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   Articles with "scale convolutional" as a keyword



Microblog Negative Comments Data Analysis Model Based on Multi-scale Convolutional Neural Network and Weighted Naive Bayes Algorithm

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recommendations! Published in 2024 at "Neural Processing Letters"

DOI: 10.1007/s11063-024-11688-9

Abstract: As a form of public supervision, Microblog’s negative reviews allow people to share their opinions and experiences and express dissatisfaction with unfair and unreasonable phenomena. This form of supervision has the potential to promote social… read more here.

Keywords: convolutional neural; naive bayes; multi scale; microblog negative ... See more keywords
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Automated Pulmonary Fibrosis Segmentation Using a 3D Multi-Scale Convolutional Encoder-Decoder Approach in Thoracic CT for the Rhesus Macaque with Radiation-Induced Lung Damage

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recommendations! Published in 2020 at "Journal of Signal Processing Systems"

DOI: 10.1007/s11265-020-01605-3

Abstract: To develop an automated pulmonary fibrosis (PF) segmentation methodology using a 3D multi-scale convolutional encoder-decoder approach following the robust atlas-based active volume model in thoracic CT for Rhesus Macaques with radiation-induced lung damage. 152 thoracic… read more here.

Keywords: convolutional encoder; scale convolutional; encoder decoder; segmentation ... See more keywords

Pathologic liver tumor detection using feature aligned multi-scale convolutional network

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recommendations! Published in 2022 at "Artificial intelligence in medicine"

DOI: 10.1016/j.artmed.2022.102244

Abstract: The detection of the most common type of liver tumor, that is, hepatocellular carcinoma (HCC), is one essential step to liver pathology image analysis. In liver tissue, common cell change phenomena such as apoptosis, necrosis,… read more here.

Keywords: scale convolutional; tumor; liver; detection ... See more keywords

Multi-scale convolutional transformer network for motor imagery brain-computer interface

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recommendations! Published in 2025 at "Scientific Reports"

DOI: 10.1038/s41598-025-96611-5

Abstract: Brain-computer interface (BCI) systems allow users to communicate with external devices by translating neural signals into real-time commands. Convolutional neural networks (CNNs) have been effectively utilized for decoding motor imagery electroencephalography (MI-EEG) signals in BCIs.… read more here.

Keywords: motor imagery; multi scale; brain computer; transformer ... See more keywords

MSCPNet: A Multi-Scale Convolutional Pooling Network for Maize Disease Classification

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recommendations! Published in 2025 at "IEEE Access"

DOI: 10.1109/access.2024.3524729

Abstract: Maize (Zea mays) is a critical crop for global food security and economic stability. However, it is highly vulnerable to various diseases such as northern leaf blight, common rust, and maize lethal necrosis, which can… read more here.

Keywords: multi scale; disease; disease classification; scale convolutional ... See more keywords

RNA-Protein Binding Sites Prediction via Multi Scale Convolutional Gated Recurrent Unit Networks

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recommendations! Published in 2020 at "IEEE/ACM Transactions on Computational Biology and Bioinformatics"

DOI: 10.1109/tcbb.2019.2910513

Abstract: RNA-Protein binding plays important roles in the field of gene expression. With the development of high throughput sequencing, several conventional methods and deep learning-based methods have been proposed to predict the binding preference of RNA-protein… read more here.

Keywords: protein binding; scale convolutional; recurrent unit; rna protein ... See more keywords

Antimicrobial peptide identification using multi-scale convolutional network

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recommendations! Published in 2019 at "BMC Bioinformatics"

DOI: 10.1186/s12859-019-3327-y

Abstract: BackgroundAntibiotic resistance has become an increasingly serious problem in the past decades. As an alternative choice, antimicrobial peptides (AMPs) have attracted lots of attention. To identify new AMPs, machine learning methods have been commonly used.… read more here.

Keywords: scale convolutional; network; convolutional network; model ... See more keywords

Vibration-based gearbox fault diagnosis using a multi-scale convolutional neural network with depth-wise feature concatenation

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recommendations! Published in 2025 at "PLOS One"

DOI: 10.1371/journal.pone.0324905

Abstract: This article proposes a novel approach for vibration-based gearbox fault diagnosis using a multi-scale convolutional neural network with depth-wise feature concatenation named MixNet. In industrial environments where equipment reliability directly impacts productivity, safety, and operational… read more here.

Keywords: diagnosis; multi scale; fault diagnosis; scale convolutional ... See more keywords

Multi-Scale Convolutional Neural Network for Accurate Corneal Segmentation in Early Detection of Fungal Keratitis

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recommendations! Published in 2021 at "Journal of Fungi"

DOI: 10.3390/jof7100850

Abstract: Microbial keratitis is an infection of the cornea of the eye that is commonly caused by prolonged contact lens wear, corneal trauma, pre-existing systemic disorders and other ocular surface disorders. It can result in severe… read more here.

Keywords: scale convolutional; corneal; segmentation; multi scale ... See more keywords

MSCL-Attention: A Multi-Scale Convolutional Long Short-Term Memory (LSTM) Attention Network for Predicting CO2 Emissions from Vehicles

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recommendations! Published in 2024 at "Sustainability"

DOI: 10.3390/su16198547

Abstract: The transportation industry is one of the major sources of energy consumption and CO2 emissions, and these emissions have been increasing year by year. Vehicle exhaust emissions have had serious impacts on air quality and… read more here.

Keywords: mscl attention; attention; multi scale; network ... See more keywords

Adaptive classification of artistic images using multi-scale convolutional neural networks

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recommendations! Published in 2024 at "PeerJ Computer Science"

DOI: 10.7717/peerj-cs.2336

Abstract: The current art image classification methods have low recall and accuracy rate issues . To improve the classification performance of art images, a new adaptive classification method is designed employing multi-scale convolutional neural networks (CNNs).… read more here.

Keywords: classification; convolutional neural; image; adaptive classification ... See more keywords