Agroindustrial Plant for the Classification of Hass Avocados in Real-Time with ResNet-18 Architecture

Ramirez, Oscar Jhon Vera; Cruz, J. E.; Machaca, Wilson Antony Mamani

doi:10.1109/icras52289.2021.9476659

Cited by 10 publications

(4 citation statements)

References 14 publications

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“…Additionally, the MNASNet [44] in the variant with Squeeze-and-Excitation (SEMNASNet), in three variants, was taken into account. ResNet18 and ResNet34 [12] were considered for their generalization capabilities, proven in a wide range of computer vision applications [56,25,32].…”

Section: Methodsmentioning

confidence: 99%

Unraveling Induction Motor State through Thermal Imaging and Edge Processing: A Step towards Explainable Fault Diagnosis

Piechocki¹,

Pajchrowski²,

Kraft³

et al. 2023

Eksploatacja i Niezawodność – Maintenance and Reliability

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Equipment condition monitoring is essential to maintain the reliability of the electromechanical systems. Recently topics related to fault diagnosis have attracted significant interest, rapidly evolving this research area. This study presents a non-invasive method for online state classification of a squirrel-cage induction motor. The solution utilizes thermal imaging for non-contact analysis of thermal changes in machinery. Moreover, used convolutional neural networks (CNNs) streamline extracting relevant features from data and malfunction distinction without defining strict rules. A wide range of neural networks was evaluated to explore the possibilities of the proposed approach and their outputs were verified using model interpretability methods. Besides, the top-performing architectures were optimized and deployed on resource-constrained hardware to examine the system's performance in operating conditions. Overall, the completed tests have confirmed that the proposed approach is feasible, provides accurate results, and successfully operates even when deployed on edge devices.

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Section: Methodsmentioning

confidence: 99%

Unraveling Induction Motor State through Thermal Imaging and Edge Processing: A Step towards Explainable Fault Diagnosis

Piechocki¹,

Pajchrowski²,

Kraft³

et al. 2023

Eksploatacja i Niezawodność – Maintenance and Reliability

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“…The input size taken by it is (224, 224, 3), where 224 is the width and height, and 3 represents the RBG channel. The output is a fully connected layer that gives input to the sequential layer [16,17].…”

Section: Resnet18 Architecturementioning

confidence: 99%

Particulate Matter Levels Classification Using Modified and Combined ResNet Models with Low Features Extraction

Matloob¹,

Shakir²

2023

3C TIC

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Smog is a serious environmental problem. It is an atmospheric pollutant that, if inhaled frequently, can lead to lung diseases such as asthma and bronchitis. One of the most dangerous air pollutants is particulate matter with a diameter of fewer than 2.5 micrometers (PM2.5), which may be breathed into the body and cause major health issues by introducing dangerous compounds deep into the lungs and bloodstream. In this research, a new convolutional neural network is proposed, by upgrading and parallelly stacking the two pre-trained models ResNet18 and ResNet50 to form a new modified-combined convolutional model (C-DCNN). Besides, we stacked another two columns of layers to extract the low features of ResNet18 and ResNet50 separately, to create finally four stacked columns of layers. The new model classifies images into different classes based on their PM2.5 concentration levels. To assess the suggested approach, an image augmentation is applied, then divided the images randomly (80% for the training progress,20% of the used training data for validation, and 20% for testing). The experimental results demonstrate that the proposed method increased the accuracy of level estimation with an accuracy increment equal to (6.25% at LR=0.

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“…Peru is a fruit exporter, mainly: grapes, nuts, mango, mandarin, banana and, of course, avocado [3]. Peru ranks third in the export of avocado [4], having two main growing seasons, the first is from January to March for the local market and the second is between April and June for export [5]. In the month of June 2022 alone, Peruvian avocado production totaled 168,404 tons with a growth of 10.1% compared to June 2021; with partial increases from 42.5% to 4.5% in 13 departments of Peru [6].…”

Section: Introductionmentioning

confidence: 99%

Design of a radio frequency robot for the analysis of farmlands of avocado crops in Peru

Manzanares Grados,

Rosales Gurmendi,

Yabar Gamarra

et al. 2023

Proceedings of the 21th LACCEI International Multi-Conference for Engineering, Education and Technology (LACCEI 2023): “Leaders

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Avocado is a fruit of high export demand. It is the third most exported product in Peru. To improve its quality, as well as the characteristics of the soil in which is gown strict supervision and control has to be taken; however, for the small and medium producers, this process is slow and costly, which generates possibilities of loss and consequently a decrease of export possibilities and economic growth. To overcome this situation, a robot has been developed to analyze the soil of the land, such as humidity, pH, macronutrients, Nitrogen, Phosphorus and Potassium. Additionally, a simple interface has been developed so that, after collecting the data, the farmer can read the results in multi-layer colored maps and perform the necessary actions to take care of the plants in a shorter time than in which is currently done.

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Agroindustrial Plant for the Classification of Hass Avocados in Real-Time with ResNet-18 Architecture

Cited by 10 publications

References 14 publications

Unraveling Induction Motor State through Thermal Imaging and Edge Processing: A Step towards Explainable Fault Diagnosis

Unraveling Induction Motor State through Thermal Imaging and Edge Processing: A Step towards Explainable Fault Diagnosis

Particulate Matter Levels Classification Using Modified and Combined ResNet Models with Low Features Extraction

Design of a radio frequency robot for the analysis of farmlands of avocado crops in Peru

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