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共 17471 条记录，以下是51-60 订阅

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Voice Analysis for Detecting Artificial Speech and Predicting Gender

Voice Analysis for Detecting Artificial Speech and Predictin...

引用

2024 OPJU International technology Conference on Smart Computing for Innovation and Advancement in Industry 4.0, OTCON 2024

作者： Bharadwaj, Rakhi Dugad, Raj Gile, Akshata Patil, Gyaneshwari Hatyalikar, Shrinivas Vishwakarma Institute of Technology Dept. of Computer Engineering Pune India

ISBN: (纸本)9798350373783

This research paper presents a comprehensive voice analysis system capable of detecting artificial speech and accurately predicting the gender and age of the speaker. Leveraging machine learning, acoustic features, and spectral analysis, the system distinguishes between natural human speech and artificial synthesis with high accuracy. It also excels in predicting the gender and age of the speaker, offering versatile applications in marketing, human-computer interaction, and demographic analysis. The study not only introduces an innovative solution to these challenges but also emphasizes its practical applicability across various domains, underscoring the relevance of voice analysis in today's technology landscape. © 2024 IEEE.

关键词： Prediction models

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Trust Based Cooperative Secure Routing Protocols for Internet of Things (IoT) 2

Trust Based Cooperative Secure Routing Protocols for Interne...

引用

2nd International Conference on Recent Trends in Microelectronics, Automation, Computing, and Communications Systems, ICMACC 2024

作者： Mekala, Sagar Ramji, Bhukya CVR College of Engineering Dept. of Computer Science and Engineering Hyderabad India Kakatiya Institute of Technology and Science Dept. of Computer Science and Engineering Hanmakonda India

ISBN: (纸本)9798350366570

The Internet of Things has rapidly emerged and continues to create services, software, sensors-embedded devices, and protocols. IoT allows physical objects to communicate, exchange information, and make decisions while performing critical jobs. The Internet of Things is enhanced by wireless sensor networks, which serve as a continuous layer. To gain adoption and spread, Internet of things-based sensor networks must overcome serious general and specialized risks and technological hurdles. The main drawbacks of wireless sensor networks are insufficient resources. Internet of Things (IOT)-based Wireless Sensor Networks have issues in energy consumption, longevity, throughput, routing, and security. The goal of this effort was to enhance network longevity, throughput, packet latency/loss, and better encounters with hostile nodes. Consider wireless energy harvesting in the proposed three-layer cluster-based wireless sensor network routing protocol to enhance network lifespan. The proposed approach is a Trust based Cooperative Secure Routing Protocol (TCSRP) technique with security system to obtain malicious activities of objects and to slant them into blacklist. Finally, experiments were done to test the methodology. It outperforms most traditional routing protocols like AODV, DSR, and DSDV. © 2024 IEEE.

关键词： Network layers

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Optimizing Kidney Stone Detection with Vision Transformers and CNNs: A Transfer Learning Strategy

Optimizing Kidney Stone Detection with Vision Transformers a...

引用

2025 International Conference on Pervasive Computational Technologies, ICPCT 2025

作者： Kulkarni, Supritha Suhaas Rao, S. Chopra, Tushar Kumar Yeshwanth, S.P. Bhanushree, K.J. Suneetha, K.R. Bangalore Institute of Technology Dept. of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798331508685

Kidney stones are a common and impactful urological condition, with timely and accurate diagnosis being critical to prevent complications such as renal damage and avoid invasive treatments. This study explores the use of advanced deep learning models, including Vision Transformers (ViT), Swin Transformer and Convolutional Neural Networks (CNNs) - specifically XResNet-50, VGG-16, MobileNetV2 and AlexNet - to enhance kidney stone detection from CT scan images. Leveraging a robust dataset of annotated CT scans in JPG format, the approach employs transfer learning which leverages features learnt from the ImageNet dataset to optimize model performance, focusing on classifying cases as either "Kidney Stone Present"or "Kidney Stone Absent". To further improve diagnostic reliability, the Grad-CAM (Gradient-weighted Class Activation Mapping) identifies and localizes kidney stones within CT images, enhancing understanding of the model's decision-making and supporting interpretability. Addressing challenges related to dataset imbalance, model interpretability, and generalizability across healthcare settings. By refining these models for kidney stone detection, the main objective of this work is to build a reliable diagnostic tool that aids in clinical judgement and treatment planning, ultimately enhancing patient outcomes and encouraging broader clinical adoption. © 2025 IEEE.

关键词： Convolutional neural networks

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Automail AI: Intelligent Voice-Controlled Email Generator 3

Automail AI: Intelligent Voice-Controlled Email Generator

引用

3rd International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics, IITCEE 2025

作者： Jayaram, Kavitha Mandagere, Samarth Gopisetti, Sampriti Sahit, S. Bnm Institute of Technology Dept. of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798331515911

The complexity of contemporary communication further emphasizes the need to automate monotonous work to increase efficiency and effectiveness. This paper introduces a new advance, voice-controlled Automail AI, in the form of an email generation tool that automatically sends an email according to end-user-specified keywords. Automail AI utilizes NLP, ML, and Speech Recognition to differentiate formal emails from informal ones and draft appropriate responses as the situation demands. It has been tuned with Naive Bayes Classifier that yields a better level of accuracy as compared to models such as Decision Tree, SVM, and Logistic Regression. Setting the benchmark for Automated Communication tools, Automail AI combines diverse technologies like SMTP to guarantee secure Email delivery, Google Text-to-Speech or GTTS for auditory feedback, and a module providing an interface for speech recognition that offers the possibility to use the tool with no hands. © 2025 IEEE.

关键词： Automail AI email generation GTTS machine learning Naive Bayes natural language processing SMTP speech recognition

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Enhancing Doodling Experience Using Generative Adversarial Networks 2

Enhancing Doodling Experience Using Generative Adversarial N...

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2nd IEEE Global Conference on Communications and Information Technologies, GCCIT 2024

作者： Ashtagi, Rashmi Rathi, Devanshu Handoo, Ripul Purohit, Rishi Madhavaswala, Abbas Nogamawala, Mohammad Vishwakarma Institute of Technology Dept. Of Computer Engineering Pune India

ISBN: (纸本)9798350388916

Interacting with AI systems solely through textual prompts often encounters limitations due to the challenges of expressing complex visual ideas in text. This paper introduces an advanced AI system that interprets and visualizes users' sketches by employing state-of-the-art Generative Adversarial Networks (GANs), such as pix2pix, SketchGAN, DCGAN, and ESRGAN. This system not only significantly enhances real-time interactions but also shows exceptional proficiency in image editing tasks, thus facilitating more intuitive communication between humans and AI. By enabling rapid and accurate visualizations, this technology substantially streamlines and improves design workflows in the architecture and fashion industries. The advancements fostered by this system contribute significantly towards achieving greater capabilities akin to Artificial General Intelligence, enhancing creative processes and production efficiencies. © 2024 IEEE.

关键词： Generative adversarial networks

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A Decentralized Document Storage Platform using IPFS with Enhanced Security 8

A Decentralized Document Storage Platform using IPFS with En...

引用

8th IEEE International Conference on Computing, Communication, Control and Automation, ICCUBEA 2024

作者： Jadhav, Swati Choudhari, Gauri Bhavik, Manasi Bura, Rishita Bhosale, Vaibhavi Vishwakarma Institute of Technology Dept. Of Computer Engineering Pune India

ISBN: (纸本)9798350391770

In response to the evolving challenges of centralized file sharing and transport-layer issues in decentralized file systems, this research paper, "A Decentralized File Sharing using IPFS with Enhanced Security,"delves into the potential of the InterPlanetary File System (IPFS) made secure with Hybrid Encryption. This decentralized approach not only addresses issues of reliability and scalability but also prioritizes enhanced security measures. By integrating cutting-edge security protocols, our study aims to fortify the IPFS framework, creating a resilient platform for secure file sharing in the digital age using algorithms such as AES and ECC-based methods. Through this exploration, we contribute to the ongoing discourse on decentralized systems, offering insights into the future of efficient and secure digital information exchange. © 2024 IEEE.

关键词： AES Blockchain Data Security ECC Encryption IPFS Privacy

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Towards Vision Based Bi-Cycles Detection and An Autonomous Decision Making System for Driving Situation Awareness 13

Towards Vision Based Bi-Cycles Detection and An Autonomous D...

引用

13th International Symposium on computer Science and Educational technology, ISCSET 2024

作者： Nine, Julkar Mehta, Ayushkumar Rajkumar, Sai Rohit Hardt, Wolfram Chemnitz University of Technology Dept. of Computer Engineering Chemnitz Germany

ISBN: (纸本)9798350390803

In response to the growing global emphasis on healthy living and environmental consciousness, the popularity of eco-friendly transportation options like bicycles has surged. However, cyclist safety remains a critical concern, particularly in interactions with automobiles, where accidents often result in severe consequences. This project aims to enhance cyclist safety through machine learning-based bicycle detection and situational awareness techniques, aiming to mitigate vehicle-bicycle collisions. By integrating OpenCV lane detection and YOLOv8-based vehicle/bicycle detection with distance estimation, the system can analyze real-Time road conditions and make informed decisions, including speed reduction, overtaking safety assessment, and maintaining safe distances from cyclists. Testing validates the system's accurate detection, precise analysis, and effective decision-making capabilities, ensuring vehicles respond appropriately to encountered road scenarios. Ultimately, this project addresses the pressing need for cyclist safety in vehicle-rich environments, leveraging machine learning, real-Time analysis, and advanced detection technologies to foster safer roads. © 2024 IEEE.

关键词： Bicycles

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Advancing Pediatric Appendicitis Diagnosis: Harnessing CNN and Hybrid Models with Ultrasound Imaging

Advancing Pediatric Appendicitis Diagnosis: Harnessing CNN a...

引用

2025 International Conference on Pervasive Computational Technologies, ICPCT 2025

作者： Kulkarni, Supritha Sharma, Sanchit Manavi, J. Vachana, U. Bhargavi, M.S. Bangalore Institute of Technology Dept. of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798331508685

Pediatric appendicitis, an acute inflammatory disease, arises from the obstruction of the appendix, often due to inflammation or a fecalith. This common abdominal emergency in children presents diagnostic challenges due to its varied clinical manifestations, which can lead to misdiagnosis or higher perforation rates stemming from atypical symptoms. This research investigates the use of deep learning, more especially Convolutional Neural Networks (CNNs), by utilizing ultrasonic imaging data, which is less expensive, non-invasive, and quicker than the other approaches now in use. Several variants are evaluated including a basic CNN and more advanced hybrid models such as CNN-Support Vector Regression, CNN-Transformer, and Hierarchical Deep CNN, to identify the most optimal model to significantly enhance diagnostic accuracy, for young patients facing this condition. The study's main goal is to develop a highly accurate and dependable diagnostic tool for evaluating the severity of pediatric appendicitis by differentiating between simple and complex cases and identifying whether surgery is required to inform treatment plans. Various challenges that need to be tackled are managing significant dataset imbalances, enhancing interpretability and transparency for real-world clinical settings, and ensuring the robustness and adaptability of all these models across various healthcare environments. © 2025 IEEE.

关键词： Pediatrics

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DDoS Attack Detection in Blockchain Networks 5

DDoS Attack Detection in Blockchain Networks

引用

5th International Conference on Data Intelligence and Cognitive Informatics, ICDICI 2024

作者： Jadhav, Swati Bhosale, Vaibhavi Choudhari, Gauri Bura, Rishita Bhavik, Manasi Vishwakarma Institute of Technology Dept. Of Computer Engineering Pune India

ISBN: (纸本)9798350389609

DDoS attacks pose a significant threat to the security and stability of blockchain networks. Low generalization, high misreporting rates, and ineffective detection capabilities are just a few of the flaws in the detection methods currently in use. DDoS attacks threaten blockchain network security and stability. Current detection methods suffer from low generalization, high misreporting rates, and inefficacy. This project proposes a solution to detect and mitigate the DDOS attack happening on Blockchain. Scapy and Wireshark's real-time data analysis helps identify attack patterns and adapt defenses to evolving threats. This proactive approach ensures the functionality and integrity of blockchain networks. Through thorough experimentation, the solution provides a robust defense against DDoS attacks, enhancing the security of the blockchain ecosystem. © 2024 IEEE.

关键词： Blockchain

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A Hybrid approach for Deepfake Detection using CNN-RNN

A Hybrid approach for Deepfake Detection using CNN-RNN

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2024 OPJU International technology Conference on Smart Computing for Innovation and Advancement in Industry 4.0, OTCON 2024

作者： Antad, Sonali Arthamwar, Vaishnavi Vijay Deshmukh, Rohan Kishor Chame, Akshay Uttam Chhangani, Harshita Pawan Vishwakarma Institute of Technology Dept. of Computer Engineering Pune India

ISBN: (纸本)9798350373783

Reliable deepfake detection of falsified videos generated by deep learning is still a pressing challenge with its growing popularity. Deep adversarial neural networks, which educate on film and target faces to ahead facial resources and facial expressions to targets, underneath DF can without difficulty idiot facial recognition structures the usage of revealed, 3-D photos mask, or video recordings from the valid consumer's face to sensors. We make significant contributions, including building adaptive datasets, comparing primitive and deep models for training, and tunable CNN-RNN tools. The overall evaluation model shows that the results are better than the findings of the most advanced methods. It was acknowledged that Deep faking today greatly impacts our environment;It is done by placing faces on original images/videos using deep neural networks. Together with the sharing of other misinformation via digital social networks, deepfake has formed digital fakery, which has become a real problem of negative social impact and as such there is a great need for successful measures to be taken to examine Deep Fakes [1]. The approach in this research generalizes by capturing physical cues in body shape and size. Our method combines CNN for spatial analysis, capturing facial features and skin texture, and LSTM and RNN for temporal analysis, monitoring expression progress. This method provides stable performance on complex deepfake videos. The modular design allows for future expansion, such as the integration of audio analysis. © 2024 IEEE.

关键词： Convolutional neural networks

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