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Performance Comparison of Overlapping Sound Event Detection Methods

Performance Comparison of Overlapping Sound Event Detection ...

引用

International Conference on Confluence The Next Generation Information Technology Summit (Confluence)

作者： Akshay Tyagi Kartikeya Singh P V S Jaswanth Kumar Prof. Rakesh Garg Mohammed Edres Yousef Abdullah Dept. of Computer Science and Engineering Amity University Uttar Pradesh India

Sound event detection is pivotal in various applications, including environmental monitoring and surveillance systems, enhancing situational awareness and response strategies. This paper investigates the intricacies of overlapping sound events, where multiple events occur concurrently, creating complexities in accurate detection. Traditional methods falter when confronted with this challenge, necessitating advanced approaches. This research pursues two primary objectives: comprehensive review of existing overlapping sound event detection methodologies and exploration of innovative solutions to enhance accuracy and robustness. Through meticulous analysis of prior research, this paper offers insights into field progress and identifies unexplored areas. Subsequent sections dissect existing methodologies, evaluating their strengths and limitations, and addressing challenges in common evaluation metrics and datasets. This paper contributes to the advancement of sound event detection technology, particularly in complex audio environments, promoting better solutions for real-world applications.

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Voice Controlled Autonomous Vehicle: Execution on a Small Scale

Voice Controlled Autonomous Vehicle: Execution on a Small Sc...

引用

Data, Computation and Communication (ICDCC), International Conference on

作者： Jigisha Mourya Navya John Krishan Kumar Dept. of Computer Science Engineering Sharda University Greater Noida India

ISBN: (数字)9798331532956

ISBN: (纸本)9798331532963

This paper addresses the challenge of improving user interaction with autonomous vehicles by integrating voice command recognition with real-time visual feedback. The study employs Google's speech recognition Application Programming Interface to transcribe spoken commands and the turtle graphics library to simulate the corresponding vehicle actions. The system is designed to accurately recognize and process voice commands, translating them into visual simulations that mirror the intended vehicle movements. The research method involved testing the system with various commands to assess its performance and effectiveness. The findings suggest that this integrated approach has significant potential for enhancing the usability and accessibility of autonomous vehicle systems.

关键词： Visualization Accuracy Speech recognition Real-time systems Libraries Internet Reliability Usability Autonomous vehicles Testing

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Neural Style Transfer: A Comparative Study

Neural Style Transfer: A Comparative Study

引用

International Conference on Computing and Networking Technology (ICCNT)

作者： M Suryamritha Varshini Balaji Srinidhi Kannan Tripty Singh Mansi Sharma Dept. of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bangalore India Dept. of Computer Science and Engineering Graphic Era(Deemed to be) University India

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

Neural Style Transfer (NST) has emerged as a powerful technique for artistic image synthesis by fusing the base image with style source. In this study, we present a comparative analysis of NST using popular convolutional neural network (CNN) architectures, using pre-trained models such as VGG19, DenseNet121, ResNet50, and MobileNetV2. The methodology involves leveraging the deep features extracted by the models to balance content and style in synthesized images. We delve into the specifics of the model’s layer utilization, loss function definition, and TensorFlow implementation details. Experimental results demonstrate the model’s ability to produce visually compelling images that seamlessly merge content and style characteristics. Densenet121 has demonstrated superior performance compared to the other models in the evaluation. This work not only contributes to the field of NST but also offers a user-friendly TensorFlow framework, fostering further exploration and advancements in the realm of computer vision and image processing.

关键词： computer vision Analytical models Image synthesis Computational modeling Neural networks computer architecture Feature extraction Convolutional neural networks Residual neural networks

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Leukaemia: A Comparative Analysis of Deep Learning Models Using ALL Dataset

Leukaemia: A Comparative Analysis of Deep Learning Models Us...

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IEEE Recent Advances in Intelligent Computational Systems (RAICS)

作者： Rhea Sudheer Rapaka Vivek Richa Ramesh Apoorva Sarvade Sada Kakarla Preethi P Dept. of Computer Science and Engineering PES University Bangalore Karnataka India

ISBN: (数字)9798350381689

ISBN: (纸本)9798350381696

White blood cells, also known as leukocytes, or WBCs, spread abnormally in the bone marrow and blood, resulting in leukaemia (blood cancer). Leukaemia can be identified by pathologists by examining a patient's blood sample under a microscope. By counting different blood cells and physical characteristics, they can identify and classify leukaemia. This method takes a lot of time to forecast leukaemia. The pathologist's professional qualifications and experiences may also have an impact on this process. Traditional machine learning and deep learning techniques in computer vision are useful road maps that improve the precision and speed of identifying and categorizing medical images, such as minuscule blood cells. This paper offers a thorough analysis of the different Deep CNN models for identification and classification of WBCs and acute leukaemia in microscopic blood cells.

关键词： Deep learning White blood cells Analytical models Accuracy Microscopy Roads Cells (biology) Blood Testing Biomedical imaging

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Work in Progress: Enhancing Students' Learning Experience in Formal Methods through Practical Assignments

Work in Progress: Enhancing Students' Learning Experience in...

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IEEE World engineering Education Conference (EDUNINE)

作者： Ruth Schorr Dept. of Computer Science and Engineering Frankfurt University of Applied Sciences Frankfurt Germany

ISBN: (数字)9798331542788

ISBN: (纸本)9798331542795

Formal methods are crucial for ensuring higher integrity levels for safety-critical systems. However, teaching these methods can be quite challenging. Students often show low motivation and are primarily focused on passing formal methods courses with minimal effort. Performance in compulsory formal methods courses is usually below average, with students perceiving the subject as overly mathematical and lacking practical relevance. To address these challenges and enrich the learning experience, we have integrated mandatory group homework assignments into our teaching framework. Students are required to work collaboratively on case studies and present their solutions during class. This work-in-progress paper provides an experience report on enhancing the learning possibilities of master’s students in a model checking course at the Frankfurt university of Applied sciences (FRA-UAS).

关键词： Model checking engineering education

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CAS-PUF: Current-Mode Array-Type Strong PUF for Secure Computing in Area Constrained SoCs

CAS-PUF: Current-Mode Array-Type Strong PUF for Secure Compu...

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2025 Design, Automation and Test in Europe Conference, DATE 2025

作者： Georgoulas, Dimosthenis Tsiatouhas, Yiorgos Tenentes, Vasileios University of Ioannina Vcas Lab Dept. of Computer Science and Engineering Ioannina Greece

ISBN: (纸本)9783982674100

Secure computing necessitates the integration in Systems-on-Chips (SoCs) of strong Physical Unclonable Functions (PUFs) that can generate a vast amount of Challenge Response Pairs (CRPs) for cryptographic keys generation, identification and authentication. However, the excessive area cost of strong PUF designs imposes integration difficulties to SoCs of area constrained applications, such as the IoT and mobile computing. In this paper, we present a novel strong PUF design, with silicon area requirements significantly lower than those of previous strong PUFs. The proposed Current-mode Array-type Strong PUF (CAS-PUF) is based on a current source topology of only six minimum size transistors, which is tolerant to power supply variation for enhanced reliability. Compared to previous strong PUFs, the CAS-PUF achieves the same number of CRPs with 20% to 72% less area size;while for the same area size, it provides 19 to 53 orders of magnitude higher number of CRPs. Furthermore, extensive Monte Carlo simulations on CAS-PDF show a reliability of 96.45% under ±10% power supply fluctuation;and 97.69% under temperature variation (0°C to 80°C), with an average uniqueness and uniformity of 50.01% and 49.54%, respectively. Therefore, CAS-PUF can be used as a hardware root of trust mechanism to secure computing in area constrained SoCs. © 2025 EDAA.

关键词： Integrated circuit design

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Balancing Safety and Security in Autonomous Driving Systems: A Machine Learning Approach with Safety-First Prioritization

Balancing Safety and Security in Autonomous Driving Systems:...

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computer Security Applications Conference Workshops (ACSAC Workshops), Annual

作者： Afshin Hasani Mehran Alidoost Nia Reza Ebrahimi Atani Dept. of Computer Engineering University of Guilan Rasht Iran Faculty of Computer Science and Engineering Shahid Beheshti University Tehran Iran

ISBN: (数字)9798331532819

ISBN: (纸本)9798331532826

In the era of autonomous vehicles (AVs), ensuring the safety and security of the system is an ongoing challenge, particularly when faced with increasingly cyber-attacks such as GPS spoofing and man-in-the-middle. This paper presents a novel reinforcement learning (RL)-based framework that prioritizes safety over security concerns in AVs, ensuring that life-critical tasks such as collision avoidance and speed control are always maintained, even in the presence of security threats. Our system leverages the MAPE-K loop to dynamically adapt to changing conditions, using RL in the Analyzing phase to make real-time decisions that maximize cumulative safety rewards while addressing security risks that directly affect operational integrity. We demonstrate how our RL-based self-adaptive system mitigates security threats while maintaining safe driving behaviors through various simulations and experiments. The proposed system shows significant improvements in collision avoidance and threat detection, ultimately ensuring that the AV’s safety is preserved in even the most challenging scenarios.

关键词： Conferences Velocity control Reinforcement learning Real-time systems Threat assessment Safety Security Collision avoidance Autonomous vehicles Global Positioning System

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Detecting Near-Surface Melt-Water and Basal Ice-Water Interfaces by VHF Radar Sounder Data

Detecting Near-Surface Melt-Water and Basal Ice-Water Interf...

引用

IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Sanchari Thakur Lorenzo Bruzzone Dept. of Information Engineering and Computer Science University of Trento Trento Italy

ISBN: (数字)9798350360325

ISBN: (纸本)9798350360332

Very high-frequency (VHF) radar sounding from an orbital platform is a promising mission concept for subsurface observations of the Earth’s polar caps for mapping the ice sheets and ice shelves from the surface to the base. Previous feasibility studies have analyzed the detectability of the basal interface, the internal layers and the subglacial lakes in simulated VHF radargrams. However, there are few studies on the detection of near-surface melt-water and the ice-ocean interface, which are important for predicting the stability of the polar ice. This paper both presents a novel semi-supervised basal ice-water detection algorithm and exploits a state-of-the-art dielectric inversion technique to detect surface melt for the analysis of simulated VHF radargrams. Results show that about 90% of the ice-ocean interfaces are correctly detected with the proposed detection algorithm and that the dielectric inversion revealed a pool of melt-water in the Antarctic peninsula.

关键词： Radar remote sensing Radar detection Radar Lakes Ice Stability analysis Dielectrics

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Privacy-Preserving Techniques in AI-Based Healthcare: A Comprehensive Review

Privacy-Preserving Techniques in AI-Based Healthcare: A Comp...

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IEEE UP Section Conference on electrical computer and Electronics (UPCON)

作者： Nandini Sharma Pritaj Yadav Dept. of Computer Science & Engineering Rabindranath Tagore University Bhopal India

ISBN: (数字)9798350378726

ISBN: (纸本)9798350378733

The incorporation of Artificial Intelligence (AI) in the healthcare has transformed patient care, diagnostics, and personalized Medicare in the today's era. As a result, it also increases significant privacy concerns due to sensitive healthcare data. This paper provides the comprehensive review of privacy-preserving methods, including federated learning, homomorphic encryption, differential privacy, blockchain, and secure multiparty computation that analyzing them in terms of privacy guarantees, computational complexity, scalability, and real-time applicability. Future work focuses on developing hybrid frameworks, lightweight privacy solutions for edge computing, and quantum-resistant cryptography to address evolving security threats. These advancements will play the pivotal role in ensuring secure, scalable, and ethically sound AI-driven healthcare systems.

关键词： Privacy Ethics Differential privacy Quantum computing Reviews Scalability Medical services Real-time systems Artificial intelligence Edge computing

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Rare and Common Types of Retinal Disease Recognition Using Ensemble Deep Learning

Rare and Common Types of Retinal Disease Recognition Using E...

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International Conference on electrical, computer and Communication engineering (ECCE)

作者： Jesika Debnath Al Shahriar Uddin Khondakar Pranta Arafath Bin Mohiuddin Amira Hossain Anamul Sakib Md. Moniruzzaman Shanto Shamim Forhad Abdullah Al-Sakib Rezaul Haque Shafiur Rahman Dept. of Computer Science Westcliff University Irvine CA USA Dept. of Computer Science Wright State University Dayton USA Department of Collage of Engineering and Technology Westcliff University CA USA Department of Business Administration International American University CA USA Dept. of Computer Science and Engineering East West University Dhaka Bangladesh Dept. of Electrical and Electronics Engineering American International University Bangladesh Dept. of Information Technology Westcliff University CA USA Dept. of Software Engineering Daffodil International University Dhaka Bangladesh

ISBN: (数字)9798350357509

ISBN: (纸本)9798350357516

Detecting retinal diseases is crucial for preventing vision loss, but it comes with challenges, such as data imbalance and accurately classifying rare conditions. This study introduces a new ensemble transfer learning model that combines EfficientNetB7, SE-ResNet, DenseNet-169, and NASNet to improve the classification of common and rare retinal diseases. The ensemble uses a probability averaging approach to maximise each architecture’s strengths. Essential preprocessing techniques such as Global Contrast Normalization (GCN) and Total Variation Denoising (TVD) were used to enhance image quality. The model was trained and evaluated on the Retinal Fundus Multi-Disease Image Dataset (RFMiD) 2.0, achieving 98.65% accuracy and an F1-score of 0.96% for common diseases and 99.10% accuracy with an F1-score of 0.97 for rare diseases, outperforming individual models significantly. The ensemble has been integrated into a web-based application that allows clinicians to upload retinal images for instant diagnostic feedback, enabling real-time analysis and visual insights. Despite its strengths, challenges such as high computational demands and reliance on high-resolution photos remain. Future work will improve computational efficiency through model compression techniques and extend the model to other imaging modalities, such as Optical Coherence Tomography (OCT). In conclusion, this study presents a robust and scalable solution for retinal disease classification, potentially improving early detection and providing real-time support in clinical settings, particularly in resource-limited environments.

关键词： Deep learning Visualization Accuracy Computational modeling Optical coherence tomography Transfer learning Imaging Retina Real-time systems Diseases

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