Articles with "mobilenet" as a keyword



Beans Leaf Diseases Classification Using MobileNet Models

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Published in 2022 at "IEEE Access"

DOI: 10.1109/access.2022.3142817

Abstract: In recent years, plant leaf diseases has become a widespread problem for which an accurate research and rapid application of deep learning in plant disease classification is required. Beans is also one of the most… read more here.

Keywords: mobilenet; leaf diseases; classification; disease ... See more keywords

Approach Based Lightweight Custom Convolutional Neural Network and Fine-Tuned MobileNet-V2 for ECG Arrhythmia Signals Classification

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Published in 2024 at "IEEE Access"

DOI: 10.1109/access.2024.3378730

Abstract: Arrhythmia detection in electrocardiogram (ECG) signals is a vital aspect of cardiovascular health monitoring. Current automated methods for arrhythmia classification often struggle to attain satisfactory performance in the detection of various heart conditions, particularly when… read more here.

Keywords: classification; mobilenet; ecg; arrhythmia ... See more keywords

Optimizing Detection: Compact MobileNet Models for Precise Hall Sensor Fault Identification in BLDC Motor Drives

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Published in 2024 at "IEEE Access"

DOI: 10.1109/access.2024.3407766

Abstract: This paper presents a comprehensive study on fault identification in Hall sensors within Brushless Direct Current (BLDC) motor drives using neural networks. Detecting these faults is critical for optimizing motor performance, enhancing energy efficiency, and… read more here.

Keywords: hall; mobilenet; motor; hall sensor ... See more keywords

Mobile-X: Dedicated FPGA Implementation of the MobileNet Accelerator Optimizing Depthwise Separable Convolution

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Published in 2024 at "IEEE Transactions on Circuits and Systems II: Express Briefs"

DOI: 10.1109/tcsii.2024.3440884

Abstract: MobileNet proposed depthwise separable convolution (DSC) as a replacement for standard convolution (SC), achieving significant reductions in parameters and computational complexity compared with traditional convolutional neural network (CNN) models. Recently, there has been a growing… read more here.

Keywords: accelerator; mobilenet; convolution; depthwise separable ... See more keywords

Smart Gravimetric System for Enhanced Security of Accesses to Public Places Embedding a MobileNet Neural Network Classifier

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Published in 2022 at "IEEE Transactions on Instrumentation and Measurement"

DOI: 10.1109/tim.2022.3162270

Abstract: In this article, we present a smart gravimetric system for the automatic security monitoring of the accesses to public places with some entrance ticket or pass required (e.g., railway stations, subway stations, museums, exhibitions). The… read more here.

Keywords: system; gravimetric system; mobilenet; network ... See more keywords

Facial Mask Detection Using Depthwise Separable Convolutional Neural Network Model During COVID-19 Pandemic

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Published in 2022 at "Frontiers in Public Health"

DOI: 10.3389/fpubh.2022.855254

Abstract: Deep neural networks have made tremendous strides in the categorization of facial photos in the last several years. Due to the complexity of features, the enormous size of the picture/frame, and the severe inhomogeneity of… read more here.

Keywords: mobilenet; network; depthwise separable; convolutional neural ... See more keywords

Image Classification of Parcel Boxes under the Underground Logistics System Using CNN MobileNet

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Published in 2022 at "Applied Sciences"

DOI: 10.3390/app12073337

Abstract: Despite various economic crisis situations around the world, the courier and delivery service market continues to be revitalized. The parcel shipping volume in Korea is currently 3.37 billion parcels, achieving a growth rate of about… read more here.

Keywords: parcel boxes; image classification; image; underground logistics ... See more keywords

Visual Measurement of Grinding Surface Roughness Based on GE-MobileNet

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Published in 2025 at "Applied Sciences"

DOI: 10.3390/app152111489

Abstract: Grinding surface texture is random and feature information is weak, so it is difficult to extract effective features by deep learning network. In addition, the existing deep learning methods mostly adopt a large parameter model… read more here.

Keywords: mobilenet; surface roughness; surface; network ... See more keywords