An Empirical Analysis of 3D Image Processing by using Machine Learning-Based Input Processing for Man-Machine Interaction

Alanya-Beltrán, Joel; Narang, Pravin; Taufikin,; Bangare, Sunil L.; Valderrama-Zapata, Carlos; Jaiswal, Sushma

doi:10.1109/icacite53722.2022.9823699

Cited by 4 publications

(4 citation statements)

References 18 publications

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“…Using three classifiers and the qualities listed below-username, gadget ID, and IP address-they created a purposeful condition for the Assault ID device that was equipped. The producers have picked the Neath conditions to give the chosen classifiers the best enchanter for spotting unusual and genuine visitors in MQTT associations [33][34][35]. The newest CNN version, called a capsule network-based technique by S. Pande et al, has been proposed as the optimal architecture for maintaining links between learned characteristics across the network and the authors also proposed the KNN-based strategy for retrieving medicinal leaf information [36][37][38].…”

Section: Literature Surveymentioning

confidence: 99%

Internet of Things Based Secured Data Transmission Protocol for Agriculture Application

Bangare¹,

Patil²

2023

ISI

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In this research, we proposed a protocol for information transmission in a communication system. The protocol consists of three parts: Publisher, Broker, and Subscriber. The main problem in the transmission is the reliability of the broker. It is very difficult to get the status of the broker whether it is active or not. Secondly, we also worked on the part of security.Here by employing a Watchdog timer to determine whether the broker is active or not. To make the system more secure AES algorithm is incorporated into it. To validate the suggested protocol hardware setup is built and performance is tested in various conditions. Performance tests show that our proposed system outperforms the current system when compared to the existing system. The suggested system architecture's temporal and spatial complexity are also presented in this research.

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Section: Literature Surveymentioning

confidence: 99%

Internet of Things Based Secured Data Transmission Protocol for Agriculture Application

Bangare¹,

Patil²

2023

ISI

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“…K. Gulati et al [20] reviewed IOT methods. S. Pande et al, have presented the latest variant of CNN termed as capsule network based approach which is the best architecture that maintains the relationships among the learned features throughout the network and KNN based approach for medicinal leaf retrieval [21] [22].…”

Section: Literature Surveymentioning

confidence: 99%

Predictive Models for ABS and TPMS based on Gaussian Naïve Bays

Vanjire

Patil²

2022

IJRITCC

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The car industry is currently preoccupied with the issue of safety. The increasing number of accidents occurring around the world as a result of automobile problems is a major contributing factor to these incidents. The amount of complicated electronics that is used in vehicles is becoming more prevalent every day. A great effort has been made in evaluating vehicle features in relation to vehicle components. Through such systems, a smart architecture and complex function designs are involved. During all of this vehicle transformation and evolution, the automotive industry recognises a high demand for vehicle safety. While designing and manufacturing this system, automotive experts understand a need for a strict monitoring and feedback system for complex vehicle architecture, which can notify the end user if there is any indication of a failure ahead of time. In order to effectively participate in vehicle design activities, it is critical to grasp the significance of safety features. Tire system failures and braking system failures have played a large role in several recent traffic accidents. The failures of the tyre system and the braking system in the vehicle are addressed in this study. While investigating this system, it is discovered that it is supported by complex electrical systems, which include an ECU (electronic controller unit), sensors, and a wire system. Through the use of these technologies, censored data can be processed in a timely manner and made available for diagnostic purposes. Nevertheless, car diagnostics is needed after any vehicle failure but that does not serve the aim of maintaining vehicle safety. As a result, predictive analysis or predictive diagnostics may be a viable option for informing the driver about the health of a particular vehicle component in advance. In this study, the author discusses the concepts of vehicle prognostics for the tyre pressure monitor system and the antilock braking system, which are accomplished using a statistical method of machine learning. In today's world, machine learning is expanding in breadth, and the world is becoming more aware of its enormous potential in the field of data analytics. It is the purpose of this study to introduce methodologies by which machine learning can assist vehicle predictive analytics to attain the intended goal of vehicle safety.The author of this article discusses how Bayesian statistics may be used to produce predictions in the form of probability estimation. The prediction's outcome is thoroughly analysed.

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“…G. Awate et al [22] CNN method-based work is good. A. Seekoli et al [23] and J. Alanya-Beltran et al [24] and S. D. Pande et al [25][26][27] have done empirical research on machine learning. It has been highlighted that most study is done at the contemporary database to improve classification precision.…”

Section: Literature Reviewmentioning

confidence: 99%

Advanced EEG Signal Based Min to Mean Algorithm Approach For Human Emotion Taxonomy And Mental State Analysis

Kimmatkar

Babu

2022

IJRITCC

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With electroencephalography (EEG) brain waves alone, it is full-scale phenomena in the field of computer-brain interface DNN, CNN, and SVM have improved detection and prediction accuracy in a number of researches during the last several years. But when it comes to recognizing global reliance, both deep learning and SVM have obvious limits. Pre-processing, extraction capabilities, and network design are the most common techniques used in deep learning models today, yet they are still unable to produce reliable results in noisy and sparse datasets. Any dataset, no matter how little or large, may suffer from poor SVM performance due to overlapping target instructions and boundaries. There are many different sorts of emotions that may be classified using the particular approach employed in this research. In order to get a whole picture of a person's mental state, it is best to use a "Min of mean” proposed technique. After comparison to the referential mean, a feeling is divided into one of four emotional quadrants. The MIN Max range is used to further split the emotion into 12 subcategories based on the amount of arousal. The proposed set of rules performed better than existing methods. Research on multi-class emotion reputation has shown that, compared to more recent studies, the proposed technique may be rather strong. It is possible to analyze a person's mental health by using the emotional spectrum, which has an accuracy rate of above 90%.

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An Empirical Analysis of 3D Image Processing by using Machine Learning-Based Input Processing for Man-Machine Interaction

Cited by 4 publications

References 18 publications

Internet of Things Based Secured Data Transmission Protocol for Agriculture Application

Internet of Things Based Secured Data Transmission Protocol for Agriculture Application

Predictive Models for ABS and TPMS based on Gaussian Naïve Bays

Advanced EEG Signal Based Min to Mean Algorithm Approach For Human Emotion Taxonomy And Mental State Analysis

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