Intelligent data post and read data system like to feed for IoT sensors

Hussain, Md. Zair; Ashraf, Mohammad; Singh, Dinesh; Haldorai, Anandakumar; Mishra, Divyendu Kumar; Shanavas, T. N.

doi:10.1007/s13198-022-01683-5

Cited by 13 publications

(2 citation statements)

References 9 publications

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“…This analysis involves a comparison between the judgments made by the gold standard (GS) and the system. According to the data presented in [18], there were a total of 156 occurrences of Hedges in the GS test data, which consisted of reserved test messages. The system accurately identified and classified 116 instances, while it failed to detect 40 instances.…”

Section: Resultsmentioning

confidence: 99%

Literature Review of Qualitative Data with Natural Language Processing

Epoka

2023

JRS

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Qualitative research techniques are frequently employed by scholars in the field of social sciences when investigating communities and their communication media. The proliferation of computer-mediated communications has resulted in a substantial volume of textual content. However, the process of coding this vast amount of information necessitates significant time and effort. This article examines the potential for automating specific elements of content analysis through the utilization of natural language processing (NLP) systems, which analyze text in human languages, with a focus on extracting theoretical evidence. In this study, we present a case analysis utilizing NLP to examine the effectiveness of NLP rules in qualitative analysis. Our findings indicate that the NLP rules demonstrated strong performance across multiple codes. The utilization of a NLP system in its current developmental stage has the potential to significantly minimize the text volume, which has to be evaluated using the human coder. This reduction could potentially result in a substantial increase in coding speed, potentially by a factor of ten or more. The research is considered groundbreaking as it pioneers the application of advanced NLP approach to evaluate qualitative data, making it one of the earliest studies in this domain.

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Section: Resultsmentioning

confidence: 99%

Literature Review of Qualitative Data with Natural Language Processing

Epoka

2023

JRS

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“…To ensure the promotion of road safety for all persons, encompassing both drivers and non-drivers, it is imperative that the technologies incorporated inside autonomous vehicles encompass precise determination of the vehicle's position and orientation. The research undertaken by [18] presented an architectural framework that integrates several point clouds and deep neural networks (DNN) to address the localization challenges in autonomous driving. The achievement of this outcome is facilitated by the use of eigenvalue computations employing Point Net and 3DCNN.…”

Section: Advancements In Robotic Perception Systems: Deep Learning Tr...mentioning

confidence: 99%

Optimizing Object Classification in Robotic Perception Environments Exploring Late Fusion Strategies

Adam,

Haldorai

2024

JRS

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Robotic perception systems often include approaches that can extract valuable features or information from the studied dataset. These methods often involve the application of deep learning approaches, such as convolutional neural networks (CNNs), for processing of images, as well as the incorporation of 3D data. The notion of image categorization is well delineated via the use of networks that include convolutional networks. However, some network topologies exhibit a substantial scope and need significant amounts of time and memory resources. On the other hand, the neural networks FlowNet3D and PointFlowNet have the capability to accurately predict scene flow. Specifically, these networks are capable of estimating the three-dimensional movements of point clouds (PCs) within a dynamic environment. When using PCs in robotic applications, it is crucial to examine the robustness of accurately recognizing the points that belong to the object. This article examines the use of robotic perception systems inside autonomous vehicles and the inherent difficulties linked to the analysis and processing of information obtained from diverse sensors. The researchers put out a late fusion methodology that integrates the results of many classifiers in order to enhance the accuracy of categorization. Additionally, the authors propose a weighted fusion technique that incorporates the proximity to objects as a significant factor. The findings indicate that the fusion methods described in this study exhibit superior performance compared to both single modality classification and classic fusion strategies.

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Marine Vision-Based Situational Automatic Ship Detection Using Remote Sensing Images

Haldorai,

Murugan

et al. 2024

EAI/Springer Innovations in Communication and Computing

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Intelligent data post and read data system like to feed for IoT sensors

Cited by 13 publications

References 9 publications

Literature Review of Qualitative Data with Natural Language Processing

Literature Review of Qualitative Data with Natural Language Processing

Optimizing Object Classification in Robotic Perception Environments Exploring Late Fusion Strategies

Marine Vision-Based Situational Automatic Ship Detection Using Remote Sensing Images

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