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DeepCerviNet: Enhanced Cervical Cancer Classification Using Supervised Learning Model 3

DeepCerviNet: Enhanced Cervical Cancer Classification Using ...

引用

3rd IEEE international conference on Robotics, automation, Artificial-Intelligence and Internet-of-Things, RAAICON 2024

作者： Rahaman, Md Anikur Binte Rabbani Nuha, Maksura Tahsin, Md Hossain, Al Islam, Raihan Ul Rifat Ahmmad Rashid, Mohammad Reza, Ahmed Wasif Ripon, Shamim H. East West University Department of Computer Science and Engineering Dhaka Bangladesh International Islamic University Chittagong Department of Computer Science and Engineering Chittagong Bangladesh

ISBN: (纸本)9798331534400

Cervical cancer is a female-specific malignancy that poses a substantial threat worldwide, especially in less privileged and underdeveloped regions. Despite continuous progress and advances in medical science research, the rate of death from cervical cancer remains strikingly high among women. Therefore, accurate early-stage cervical cancer identification is imperative for effective diagnosis. It facilitates cost-effective and timely treatment to increase the survival rate of patients, leading to an optimal diagnosis improvement in disease classification. Deep learning approaches demonstrate superior accuracy in medical data classification, motivating us to consider these techniques in this research. In our study, we propose DeepCerviNet, a custom CNN model that achieves 99% precision, which exceeds the accuracy of other deep learning models, MobileNetV2 (97%), ResNET34 (95%), and GoogleNet (94%). Furthermore, to assess our model's generalizability, we use another Multicancer dataset where the proposed model classifies various cancers with 99% accuracy. The DeepCerviNet model's strong performance and adaptability can assist in identifying more aggressive or recurrent cervical cancer types, aiding the development of targeted therapeutic strategies. © 2024 IEEE.

关键词： Self-supervised learning

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Integrating GPS and GSM Technologies for Enhanced Women's Safety: A Fingerprint-Activated Device Approach

Integrating GPS and GSM Technologies for Enhanced Women's Sa...

引用

2024 IEEE international conference on automation and Computation, AUTOCOM 2024

作者： Singh, Kamred Udham Chaudhary, Varun Sharma, Pradeep Kumar Kumar, Pushpendra Varshney, Neeraj Singh, Teekam Graphic Era Hill University School of Computing Dehradun India Ims Engineering College Ghaziabad India Hcl Technologies UP Noida India Scanno System Greater Noida India Gla University Department of Computer Engineering & Applications UP Mathura India Graphic Era Deemed to Be University Department of Computer Science and Engineering Dehradun India

ISBN: (纸本)9798350382723

The creation of a safety system that is based on GPS and is developed exclusively for the health and safety of women via the incorporation of novel elements in order to meet the rising concerns about crimes committed against women. The gadget is capable of contacting authorities, conveying the user's position via SMS, and generating a loud noise to attract attention. It may be triggered in anticipation of potential danger and can be activated in the event that danger is imminent. In order to guarantee that only authorized users are able to activate the device, the system makes use of fingerprint recognition in a very unique way. Using technologies such as global positioning system (GPS), global system for mobile communications (GSM), and microcontrollers, this study makes a contribution to the continuing efforts to improve the safety of women via technological innovation. It provides a proactive approach to prevent violence against women and save lives. The research emphasizes the significance of combining hardware and software in order to provide a complete safety tool. It also illustrates the vital role that quick support plays and the potential of such gadgets to promote confidence among women in public places. © 2024 IEEE.

关键词： Microcontrollers

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A Review on Sugarcane Leaf Defect Detection Approaches 3

A Review on Sugarcane Leaf Defect Detection Approaches

引用

3rd international conference on automation, Computing and Renewable Systems, ICACRS 2024

作者： Patel, Avi Sutaria, Kamal Adhvaryu, Rachit Computer Science & Engineering Department PIET Parul University Gujarat Vadodara India

ISBN: (纸本)9798331532420

Sugarcane is a critical crop, and its productivity is significantly influenced by leaf defects caused by various diseases. Accurate and timely detection of these defects is essential for effective crop management. This review paper explores the state-of-the-art approaches for detecting sugarcane leaf defects, focusing on machine learning (ML), deep learning (DL), and transfer learning techniques. The motivation behind this review is to address the limitations of existing methods and propose future improvements. The objective is to provide a comprehensive overview of the current methodologies, evaluate their performance, and highlight areas for future research. This review aims to contribute to the development of more accurate and robust detection systems that can be effectively implemented in real-world agricultural settings. © 2024 IEEE.

关键词： Adversarial machine learning

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Research on Data Processing and Communication Model of Intelligent Building Environment Monitoring System 2

Research on Data Processing and Communication Model of Intel...

引用

2nd IEEE international conference on Electrical, automation and computer engineering, ICEACE 2024

作者： Fang, Fang Ding, Wang Xiao, Xiao Chongqing Vocational College of Architecture and Technology China Construction Engineering Co. Ltd. China Co. Ltd. China

ISBN: (纸本)9798350368208

This paper proposes a data processing and communication model of intelligent building environment monitoring system based on dynamic network routing algorithm, aiming to improve the real-time and reliability of data transmission. The system collects key data such as temperature, humidity, and air quality in the building environment in real time through the sensor network, and uses the dynamic network routing algorithm to efficiently transmit and process the data, to achieve accurate feedback and optimized management of monitoring information. The dynamicity and complexity in the multi-node environment are fully considered, and the optimal selection of different transmission paths is made to reduce the system delay and improve the stability of data transmission. At the same time, a data communication model simulation platform is established, and the various performance indicators of the algorithm are comprehensively evaluated. The simulation results show that the dynamic network routing algorithm designed in this paper has high accuracy and response speed in complex building environments, significantly reduces data delay compared with traditional methods, and has better performance in data packet loss rate and energy consumption. This study provides a reliable data transmission solution for the intelligent building environment monitoring system and provides effective support for the realization of intelligent management. © 2024 IEEE.

关键词： Green buildings

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A Comprehensive Analysis of Object Tracking in UAVs using computer Vision 3

A Comprehensive Analysis of Object Tracking in UAVs using Co...

引用

3rd international conference on automation, Computing and Renewable Systems, ICACRS 2024

作者： Ilavendhan, A. Paul, Bhenedix Pokala, Joshnavi School of Computer Science and Engineering Vellore Institute of Technology Chennai India

ISBN: (纸本)9798331532420

Object tracking has proven to be an essential in a wide range of applications and unmanned aerial vehicles (UAVs) provide advantages to this field in accurately observing and tracking moving targets in challenging environments. This paper presents an overview of various object tracking methodologies which can be utilized on UAVs. It discusses different approaches to attain an improved method of UAVs to help track moving objects accurately, even under challenging conditions such as occlusions or changes in object size and speed. This research study highlights the combinations of traditional tracking techniques infused with modern machine learning techniques to help explore advancements and opportunities of performance improvement. Key topics discussed are the use of algorithms that enable prediction of location of objects, techniques for tracking even small objects in dynamic environments and possibilities of UAVs cooperating with ground vehicles to improve tracking accuracy by sharing data. Overall, the paper discusses the importance of developing more efficient and reliable tracking systems which have applications in various fields such as surveillance, search and rescue operations. © 2024 IEEE.

关键词： Object tracking

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System for Talent Acquisition: Integrating AI, automation, and Data Analysis in HR 6

System for Talent Acquisition: Integrating AI, Automation, a...

引用

6th international conference on Artificial Intelligence in Information and Communication, ICAIIC 2024

作者： Abitova, Gulnara Serikov, Ayanbek Nikulin, Vladimir Rakhimzhanova, Mira Shuteyeva, Gulnur Kulniyazova, Korlan Astana IT University Dep. Computer Engineeering Astana Kazakhstan Binghamton University Dept. Electical Engineering and Computer Science Binghamton United States Eurasian National University Dept. System Anslysis and Managemnt Astana Kazakhstan

ISBN: (纸本)9798350344349

This article presents a novel system designed for human resources (HR) companies, aiming to predict an individual's personality based on resume analysis through the integration of advanced information technology tools. At the core of this system is Airable, serving as the central database, which is seamlessly I integrated with various other tools such as *** for document handling, GitHub for code repository management, and OpenAI for advanced AI algorithms. The integration and automation of these diverse tools are skillfully orchestrated using Make, a no-code solution that streamlines the workflow and enhances efficiency. This innovative approach allows HR companies to leverage technology for more accurate personality predictions, thereby improving their recruitment processes and decision-making strategies. © 2024 IEEE.

关键词： Machine learning

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Neural Command: Real-Time EEG-Based Brain-computer Interface for Assistive Robotic Control 3

Neural Command: Real-Time EEG-Based Brain-Computer Interface...

引用

3rd IEEE international conference on Robotics, automation, Artificial-Intelligence and Internet-of-Things, RAAICON 2024

作者： Vasker, Nishat Shakib Sakibur Rahman, M.D. Arafat, Yasin Ul Islam, Raihan East West University Department of Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9798331534400

This paper presents a method to help people with disabilities interact with their surroundings using brainwave signals. Since individuals with disabilities often depend on different types of transportation, this research focuses on enabling the real-time control of a robotic vehicle through non-invasive brain-computer interfaces (BCI).Can brain-computer interfaces (BCIs) based on EEG signals control a robotic car in real time? The MUSE headband is used to capture brain waves, and the signals are processed through PETAL metrics and a server within a Brain Wave Processing Unit. Subsequently, they are transmitted via WiFi/IPv4 to a Vehicle Control Unit with esp8266 microcontroller. The system underwent rigorous evaluation, achieving an 85% control accuracy and an average response time of 300 milliseconds. These results highlight the system's effectiveness in real-time applications, offering precise and rapid response capabilities suitable for assistive technology. This research represents a contribution to the development of advanced BCI-based assistive devices, demonstrating the potential for improved human-machine interaction. The high accuracy and low latency of the system emphasize its suitability for environments where swift and reliable control is crucial, particularly for individuals with mobility impairments. © 2024 IEEE.

关键词： Human robot interaction

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Unmanned Vehicle Navigation Based on ROS 2

Unmanned Vehicle Navigation Based on ROS

引用

2nd international conference on automation, Robotics and computer engineering, ICARCE 2023

作者： He, Zhengyang Fu, Xudong School of Mechanical Engineering Sichuan University Jinjiang College Meishan China School of Automation Chongqing University of Posts and Telecommunications Chongqing China

ISBN: (纸本)9798350308341

Under modern conditions, the development momentum of international unmanned driving technology is booming, but the industrialization of unmanned driving cars is still limited by the current level of software and hardware. Reducing the complex and high standard requirements of unmanned driving and then studying unmanned vehicle navigation technology in some simple scenarios are also a hot topic in current research. This paper studies an unmanned autonomous navigation vehicle based on robot operating system (ROS) software framework on the Ubuntu operating system. It combines algorithms such as simultaneous localization and mapping (SLAM) technology, adaptive Monte Carlo localization (AMCL) technology and path planning, aiming to solve the problems of simultaneous localization, mapping and path planning in a closed environment. This case algorithm avoids the problem of large error accumulation caused by traditional odometer navigation and global positioning system (GPS) navigation technologies. The simulation results show that the algorithm has good practical application value. © 2023 IEEE.

关键词： Robot Operating System

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GestureX: Text Generation based on the Gesture Identified using LSTM 8

GestureX: Text Generation based on the Gesture Identified us...

引用

8th IEEE international conference on Computing, Communication, Control and automation, ICCUBEA 2024

作者： Parkar, Zaid Nair, Amitesh Nautiyal, Akhil Patil, Ruturaj Pulgam, Namita D Y Patil Deemed to be University Department of Computer Engineering Ramrao Adik Institute of Technology Navi Mumbai India

ISBN: (纸本)9798350391770

Technology has made remarkable strides, and it is crucial to use new technologies for the benefit of those who are hard of hearing. These people faces many issues in communication. To address this issue system is proposed leverages cutting-edge tools like MediaPipe and TensorFlow to enhance communication. The proposed system is able to understand sign language in real-time, offering a simple and effective solution. The key challenge it tackles is the variability of sign language, which can be influenced by factors like lighting and signing style. To address this a smart computer model using LSTM, has been developed to ensure accurate gesture recognition and through that sign language interpretation. This technique designed has the potential to significantly improve the lives of those with hearing difficulties, making socializing, learning, and conversing much easier for them. © 2024 IEEE.

关键词： Gesture recognition

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AI-Powered Classification of Artistic Attributes 2

AI-Powered Classification of Artistic Attributes

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2nd IEEE international conference on Electrical, automation and computer engineering, ICEACE 2024

作者： Wenhui, Li Guiping, Lu Qichen, Zhang Yuhuan, Wen Kejun, Wang Weidong, Hu Beijing Institute of Technology Zhuhai Faculty of Information Zhuhai China Beijing Institute of Technology Zhuhai Terahertz Science and Applications Center Zhuhai China Beijing Institute of Technology Zhuhai Aviation Academy Zhuhai China Beijing Institute of Technology Zhuhai Faculty of Mathematics Physics and Civil Engineering Zhuhai China

ISBN: (纸本)9798350368208

In view of the current situation in image classification research where algorithms for classification based on the art-style attributes of images are still relatively rare, an automatic image classification system based on art attributes has been implemented. This system mainly involves several typical art-style images such as photographic works, traditional Chinese paintings, watercolor paintings, sketches, and oil paintings. The system uses the Support Vector Machine (SVM) as a classifier and adopts a hierarchical classification method. A specific SVM binary-tree multi-class classification algorithm for the classification of art-attribute images is proposed. Then, through the analysis of the art-style characteristics of various types of images, representative, well-discriminative, and easy-to-calculate features are respectively extracted. Finally, experimental analyses are carried out for the characteristics of each level of classification and the overall characteristics of the classifier. The experimental results show that the system has good classification performance. © 2024 IEEE.

关键词： Trees (mathematics)

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