Analysis of Mechanical Adhesion Climbing Robot Design for Wind Tower Inspection

Mondal, Shyamal; Marquez, Patricio l. C.; Tokhi, M. O.

doi:10.37965/jait.2021.0013

Cited by 13 publications

(13 citation statements)

References 13 publications

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“…WBC segmentation is carried out using the MASK-RCNN network for blood images through the semantic segmentation process; meanwhile, these WBCs relate to positive classes and their pixel relates to negative, which is shown in Figure 4 ; for the input images, the initial process to train the model, ResNet [ 1 , 24 ] was scaled to 224 ∗ 224 to maintain stability and to scale the output of the network. Later, for the ground truth, sample labels were applied to each pixel by making them to the chosen label/class.…”

Section: Resources and Methodsmentioning

confidence: 99%

“…From the above literature, it is found that the existing models suffer from hyperparameters tuning [ 1 , 24 – 26 ], gradient vanishing [ 27 , 28 ], and overfitting [ 29 – 31 ] problems. Therefore, an efficient model is required that can overcome these issues.…”

Section: Literature Reviewmentioning

confidence: 99%

“…From the above literature, it is found that the existing models suffer from hyperparameters tuning [1,[24][25][26], gradient vanishing [27,28], and overfitting [29][30][31] problems.…”

Section: Literature Reviewmentioning

confidence: 99%

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Segmentation and Classification of White Blood Cells Using the UNet

Alharbi

Aravinda²,

Meng

et al. 2022

Contrast Media & Molecular Imaging

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In the bone marrow, plasma cells are made up of B lymphocytes and are a type of WBC. These plasma cells produce antibodies that help to keep bacteria and viruses at bay, thus preventing inflammation. This presents a major challenge for segmenting blood cells, since numerous image processing methods are used before segmentation to enhance image quality. White blood cells can be analyzed by a pathologist with the aid of computer software to identify blood diseases accurately and early. This study proposes a novel model that uses the ResNet and UNet networks to extract features and then segments leukocytes from blood samples. Based on the experimental results, this model appears to perform well, which suggests it is an appropriate tool for the analysis of hematology data. By evaluating the model using three datasets consisting of three different types of WBC, a cross-validation technique was applied to assess it based on the publicly available dataset. The overall segmentation accuracy of the proposed model was around 96%, which proved that the model was better than previous approaches, such as DeepLabV3+ and ResNet-50.

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Section: Resources and Methodsmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

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Segmentation and Classification of White Blood Cells Using the UNet

Alharbi

Aravinda²,

Meng

et al. 2022

Contrast Media & Molecular Imaging

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“…e experimental results demonstrated that the combined approach of SVM and IPSO had higher accuracy. However, the majority of the existing models suffer from overfitting [23][24][25], poor convergence speed [26][27][28], and vanishing gradient problems [29][30][31].…”

Section: Literature Surveymentioning

confidence: 99%

Efficient Long Short-Term Memory-Based Sentiment Analysis of E-Commerce Reviews

Gondhi

Chaahat

Sharma

et al. 2022

Computational Intelligence and Neuroscience

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In today’s modern era, e-commerce is making headway through the process of bringing goods within everyone’s grasp. Consumers are not even required to step out of the comfort of their homes for buying things, which makes it very convenient for them. Moreover, there is a wide variety of brands to choose from. Since more customers depend on online shopping platforms these days, the value of ratings is also growing. To buy these products, people rely solely on the reviews that are being provided about the products. To analyze these reviews, sentiment analysis needs to be performed, which can prove useful for both the buyers and the manufacturer. This paper describes the process of sentiment analysis and its requirements. In this paper, Amazon Review dataset 2018 has been used for carrying out our research and Long Short-Term Memory (LSTM) has been combined with word2vec representation, resulting in improving the overall performance. A gating mechanism was used by LSTM during the training process. The proposed LSTM model was evaluated on four performance measures: accuracy, precision, recall, and F1 score, and achieved overall higher results when compared with other baseline models.

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“…The implications of substantial quantities of improperly classified data in medical image classification are catastrophic, and the objective of proposing a medical diagnosis tool is wrecked. In addition to efficiency, additional parameters such as F1 score [ 25 , 26 ], area under the curve (AUC) [ 27 , 28 ], sensitivity [ 29 , 30 ], and specificity [ 31 – 33 ] are vital in analyzing various approaches. A random sample of cell images infected/not infected with malaria is shown in Figure 1 .…”

Section: Related Workmentioning

confidence: 99%

Computational Models‐Based Detection of Peripheral Malarial Parasites in Blood Smears

Alharbi

Aravinda

Shetty

et al. 2022

Contrast Media & Molecular Imaging

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The most common human parasite as per the medical experts is the malarial disease, which is caused by a protozoan parasite, and Plasmodium falciparum, a common parasite in humans. A microscopist with expertise in malaria diagnosis must conduct this complex procedure to identify the stages of infection. This epidemic is an ongoing disease in some parts of the world, which is commonly found. A Kaggle repository was used to upload the data collected from the NIH portal. The dataset contains 27558 samples, of which 13779 samples carry parasites and 13779 samples do not. This paper focuses on two of the most common deep transfer learning methods. Unlike other feature extractors, VGG-19’s fine-tuning and pretraining made it an ideal feature extractor. Several image classification models, including VGG-19, have been pretrained on larger datasets. Additionally, deep learning strategies based on pretrained models are proposed for detecting malarial parasite cases in the early stages, in addition to an accuracy rating of 98.34 ∗ 0.51%.

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Analysis of Mechanical Adhesion Climbing Robot Design for Wind Tower Inspection

Cited by 13 publications

References 13 publications

Segmentation and Classification of White Blood Cells Using the UNet

Segmentation and Classification of White Blood Cells Using the UNet

Efficient Long Short-Term Memory-Based Sentiment Analysis of E-Commerce Reviews

Computational Models‐Based Detection of Peripheral Malarial Parasites in Blood Smears

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