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Exploiting Wavelet Scattering Transform & Squeeze-Excitation Blocks with Cross-Modal Attention for Multi-modal Emotion Recognition

Exploiting Wavelet Scattering Transform & Squeeze-Excitation...

引用

international conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Junchen Liu Jesin James Karan Nathwani Department of Electrical Computer and Software Engineering The University of Auckland New Zealand Department of Electrical Engineering India Institute of Technology Jammu India

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Multi-modal emotion recognition (MER) is crucial for improving human-computer interaction. Convolutional neural networks (CNNs) are the mainstream for MER tasks, but they require large databases, extensive memory, and significant energy, limiting their practical use. This paper proposes a novel MER system that leverages wavelet scattering transform (WST) to address these challenges, achieving improved performance with lower computational consumption. Moreover, the system benefits from the noise robustness provided by WST. By integrating WST as a non-trainable initial layer in a CNN model and employing an encoder module, our system effectively captures time-frequency, local and high-level features from both speech and video. We enhance feature integration and representation with cross-modal attention (CMA) and a squeeze-and-excitation (SE) block. The results demonstrate that our system performs consistently across varying noise levels and duration thresholds. Ablation studies reveal that the combination of MFCC, Mel spectrogram, and raw waveform features yields the highest accuracy, with Mel spectrogram being the most influential. Experimental results on the IEMOCAP and RAVDESS databases achieve emotion recognition accuracy of 83.2% and 97.8%, respectively, showcasing improved performance and robustness compared to state-of-the-art models, while using fewer trainable parameters.

关键词： Wavelet transforms Emotion recognition Time-frequency analysis Accuracy Databases Computational modeling Scattering Feature extraction Convolutional neural networks Spectrogram

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Enhanced Small Lesion Detection on Grape Leaves Using Optimized YOLOv7

Enhanced Small Lesion Detection on Grape Leaves Using Optimi...

引用

Integrated Circuits and Communication systems (ICICACS), ieee international conference on

作者： Mahalakshmi S Jay Gandhi V. Prabakaran Shailesh Rastogi Department of Computer Science and Engineering Chennai Institute of Technology Kundrathur Chennai India Department of Computer science and Engineering Faculty of Engineering and Technology Parul University Vadodara India Balaji Institute of Technology & Management (BITM) Pune India Department of Finance Symbiosis Institute of Business Management Nagpur Symbiosis International (Deemed University) Pune India

ISBN: (数字)9798331508456

ISBN: (纸本)9798331508463

The detection of small lesions on grape leaves plays a pivotal role in the early identification and management of plant diseases, potentially reducing significant agricultural losses. Traditional detection systems, including advanced versions such as YOLOv7, often overlook small target diseases due to resolution constraints and inadequate feature extraction capabilities. Addressing this, our research enhances the YOLOv7 architecture by incorporating a specialized prediction branch and leveraging an improved channel attention mechanism in conjunction with an Extended-Efficient Long-range Attention Network (E-ELAN). Firstly, a new detection head specifically designed for small targets enhances the resolution capabilities of the system. Secondly, the integration of asymmetric convolution into the E-ELAN facilitates refined multi-scale feature extraction, critical for distinguishing minute pathological changes. Further, we enhance the model's sensitivity to small-scale features through a revamped channel attention mechanism. Moreover, we replace the conventional Complete Intersection over Union (CIoU) with a Structured Intersection over Union (SIoU) in the loss function, significantly improving the model's localization accuracy. Experimental results from testing the optimized YOLOv7 on a dataset of grape leaves affected by three prevalent diseases show an average accuracy improvement of 2.7%, achieving a remarkable 93.5%. This substantiates our model's efficacy in enhancing small lesion detection, thereby contributing effectively to early disease intervention strategies in viticulture.

关键词： Training Plant diseases Attention mechanisms Accuracy Sensitivity Convolution Pipelines Feature extraction Lesions Integrated circuit modeling

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Hand Motion Sign Language Detection Using Convolutional Neural Network (CNN) and YOLOv5 Object Detection Framework

Hand Motion Sign Language Detection Using Convolutional Neur...

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Disruptive Technologies (ICDT), international conference on

作者： Pankaj Kumar S. K. Singh Department of Computer Science & Engineering G. L. Bajaj Institute of Technology and Management Greater Noida Uttar Pradesh INDIA Department of Computer Science & Engineering Galgotias College of Engineering & Technology Greater Noida Uttar Pradesh INDIA

ISBN: (数字)9798331519582

ISBN: (纸本)9798331519599

The majority of people who don't hear or speak depend upon sign language as their main method of communication. Sign language mastery presents particular difficulties to learners. Our system will convert sign language gestures from interpreters into spoken and textual words. Our technology functions as a personal language translator which operates through computers or smartphones. The combination of OpenCV alongside his YOLOv5 framework enables users to watch hand gestures while detecting gesture signals accurately. Through this system individuals who struggle with hearing and speaking abilities can conveniently approach anyone. The system integrates with cellphone calls and applications along with video conversation features. We aim to provide affordable communication solutions that work for every person.

关键词： Hands YOLO Computers Sign language Translation Oral communication Auditory system Convolutional neural networks Disruptive technologies Smart phones

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Shoe-Based PDR system for Two-Dimensional Tracking

Shoe-Based PDR System for Two-Dimensional Tracking

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ieee international conference on Consumer Electronics (ICCE)

作者： Dai Kajimoto Yusuke Tanaka Siya Bao Nozomu Togawa Department of Computer Science and Communications Engineering Waseda University Ashirase Corporation

ISBN: (数字)9798331521165

ISBN: (纸本)9798331521172

The most famous absolute self-positioning is GPS (Global Positioning system). However, GPS cannot be used in indoor and underground environments. Thus, relative positioning methods such as sensor-based pedestrian dead reckoning (PDR) are required. The visually impaired has difficulty using navigation devices using visual information, such as smartphones, and it is necessary to develop navigation devices using non-visual information. In this paper, we propose a highly accurate two-dimensional PDR using Ashirase device, a shoe-based wearable sensor. This sensor provides non-visual navigation aids through the underfoot vibrations and has an accurate position estimation as the sensor is strongly attached to the shoe. The proposed method obtained a low estimation error <0.2% walking in straight lines and <1.2% walking in circles.

关键词： Legged locomotion Vibrations Visualization Accuracy Pedestrians Dead reckoning Wearable devices Wearable sensors Smart phones Global Positioning system

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Integrated Real-Time Monitoring for Soldier Health and Operational Efficiency: A Multi-Metric Approach

Integrated Real-Time Monitoring for Soldier Health and Opera...

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Advancements in Electrical, Electronics, Communication, Computing and Automation (ICAECA), international conference on

作者： S. Umamaheswari Lingeswaran G B. Shuriya Dept of Electronics and Communication Engineering Kumaraguru College of Technology Coimbatore India Department of Electronics and Communication Engineering Velalar College of Engineering and Technology Thindal India Department of Computer Science Engineering PPG Institute of Technology Coimbatore India

ISBN: (数字)9798331525439

ISBN: (纸本)9798331525446

Protection of soldiers' lives and war readiness in risk-prone areas demands continuous monitoring of health, location, and surroundings. In this paper, a hybrid soldier location tracking, health monitoring, and live video streaming system using smart sensors, RF technology, and ESP32-CAM module is presented. Real-time body temperature, gun detection, oxygen saturation, and heart rate monitoring are based on an ATmega2560 microcontroller and MAX30100 pulse oximeter. Command stations are fed in real-time with secure RF transmit. Real-time video and GPS location are offered to provide situational awareness in order to support timely decisions. The system supports low-latency, high-reliability deployment in hostile ground. Testing is structured to validate robust operation, precise diagnostics, and power conservancy. AI-driven analytics and sophisticated sensor fusion will be the focus of future development for higher battlefield resilience.

关键词： Heart rate Temperature sensors Radio frequency Streaming media Real-time systems Telecommunication computing systems support Monitoring Global Positioning system Testing

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Daily updates on Construction sites progress using Artificial Intelligence

Daily updates on Construction sites progress using Artificia...

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Intelligent and Innovative Technologies in Computing, Electrical and Electronics (IITCEE), international conference

作者： Inbamalar T.M S.R.Theekshaya D.Yoga Priya C.Subhalakshmi R. Varsha R. V.Vishnu Priya Electronics Engineering RMK College of Engineering and Technology Tamilnadu India Electronics and Communication Engineering RMK College of Engineering and Technology Tamilnadu India

ISBN: (数字)9798331515911

ISBN: (纸本)9798331515928

Construction planning stands as a cornerstone in the successful management and execution of construction projects, presenting both fundamental principles and significant challenges. The planning process encompasses the strategic selection of technology, accurate estimation of required resources and task durations, and the meticulous identification of interactions among diverse work tasks. A well-crafted construction plan serves as the bedrock for developing comprehensive budgets and schedules, laying the groundwork for efficient project execution. Furthermore, the system recognizes the importance of adaptability and customization in the construction industry. It stores and updates customized requirements for materials, ensuring that the construction plan remains agile and responsive to changing project dynamics. the proposed construction planning system represents a paradigm shift from traditional methods, offering a holistic and technologically advanced approach to project management.

关键词： Heart Schedules Project management Estimation Machine learning Real-time systems Maintenance Internet of Things Standards Optimization

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Empowering Smart Living: FPGA-Enabled Home Automation for Enhanced Safety, Security, and Efficiency

Empowering Smart Living: FPGA-Enabled Home Automation for En...

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Interdisciplinary Approaches in technology and Management for Social Innovation (IATMSI), ieee conference on

作者： Narendra Singh Beniwal Shruti Kalra Ruby Beniwal Department of Electronics and Communication BIET Jhansi UP India Department of Electronics and Communication Jaypee Institute Of Information Technology Noida India

ISBN: (数字)9798331521691

ISBN: (纸本)9798331521707

This paper presents an FPGA-based home automation system implemented on a Xilinx Zynq-7000 SoC. Using Verilog HDL, FSM logic handles sensor signals (fire sensor: 5V, digital; buzzer: 5-12V). Cadence tools generated verified RTL schematics and waveforms. Key features include automated lighting, temperature regulation, and fire/intruder alerts, with a detection threshold of 3 seconds. The modular system ensures scalability, supporting seamless integration of additional devices for enhanced functionality and security.

关键词： Automation Accuracy Scalability Feature extraction Motion detection Security Time factors Hardware design languages Usability Field programmable gate arrays

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Improvement of Trajectory Estimation Considering Imaging Delay for Autonomous Image Tracking system in Flyby Observation

Improvement of Trajectory Estimation Considering Imaging Del...

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international conference on Mechatronics (ICM)

作者： Yohei Hashino Haruhi Nakatani Kenta Seki Yoshihide Aoyanagi Kikuko Miyata Makoto Iwasaki Dept. of Electrical and Mechanical Engineering Nagoya Institute of Technology Nagoya Japan Dept.of Headquarters for Innovative Society Academia Cooperation University of Fukui Fukui Japan Dept. of Vehicle and Mechanical Engineering Meijo University Nagoya Japan

ISBN: (数字)9798331533892

ISBN: (纸本)9798331533908

In recent years, close approach exploration, called flyby, of asteroids by small spacecraft has attracted attention. In flybys, guidance based on a spacecraft trajectory pre-calculated on the ground is problematic because the accuracy of tracking and imaging is degraded due to uncertainty in geometric parameters during spacecraft navigation. In particular, recent missions tend to fly at higher speeds and shorter proximity distances to the target asteroid. Therefore, the effects of camera measurement error and delay time cannot be ignored, making it difficult to achieve the required performance with simple feedback control. To improve the flyby accuracy, highly accurate trajectory estimation based on measured relative trajectory and the design of a precise control system for the actuator is effective. This paper focuses on accurate trajectory estimation, where a trajectory estimation method based on an online autonomous imaging algorithm is proposed. The least-squares method estimates the relative velocity between the spacecraft and the asteroid. Based on the estimated relative velocity, an accurate target trajectory is generated. In addition, a target trajectory with improved accuracy is generated by correcting the camera's delay time, and the imaging system's actuators are controlled based on the trajectory. The accuracy of the tracking system is evaluated through experiments using an experimental setup that simulates a flyby exploration.

关键词： Space vehicles Actuators Accuracy Target tracking Estimation Asteroids Cameras Control systems Trajectory Delays

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Advances in Computational Epilepsy Diagnostics: Machine Learning at the Forefront

Advances in Computational Epilepsy Diagnostics: Machine Lear...

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Industrial Electronics: Developments & Applications (ICIDeA), ieee international conference on-

作者： Anmol Rattan Singh Gurjinder Singh Nagendar Yamsani Saif Obbayed Chitkara University Institute of Engineering and Technology Chitkara University Punjab India School of Computer Science and Artificial Intelligence SR University Warangal Telangana India Department of Computers Techniques Engineering College of Technical Engineering The Islamic University Najaf Iraq Department of Computers Techniques Engineering College of Technical Engineering The Islamic University of Al Diwaniyah Al Diwaniyah Iraq

ISBN: (数字)9798331533205

ISBN: (纸本)9798331533212

Epilepsy is a prevalent neurological condition marked by spontaneous, recurrent seizures, significantly affecting quality of life and increasing mortality risk. This research paper delves into advanced computational methodologies for the detection and classification of epileptic seizures. Leveraging the power of machine learning and deep learning, this study aims to overcome the limitations of traditional diagnostic methods, which typically involve invasive monitoring and subjective analysis of EEG data. By introducing sophisticated machine learning models and employing non-linear classification techniques through kernel methods and support vector clustering, this research enhances the precision and speed of epilepsy diagnosis. The study not only explores the integration of these models into non-invasive, real-time monitoring systems but also discusses their impact on clinical practice and healthcare systems.

关键词： Deep learning Accuracy Computational modeling Epilepsy Medical services Brain modeling Electroencephalography Real-time systems Kernel Monitoring

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A Monitoring Method Based on EEG Data and Deep Learning

A Monitoring Method Based on EEG Data and Deep Learning

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Consumer Electronics and Computer engineering (ICCECE), 2021 ieee international conference on

作者： Zihao Gong Guoliang Liu School Of Information and Communication Guilin University of Electronic Technology Guilin Guangxi China School of Computer Science and Information Security Guilin University of Electronic Technology Guilin Guangxi China

ISBN: (数字)9798331533113

ISBN: (纸本)9798331533120

In the context of modern education, the pursuit of effective teaching and learning has been constantly evolving. With the increasing emphasis on personalized education and the need to understand students' cognitive processes in real-time, the limitations of traditional teaching assessment methods have become more prominent. This paper presents a monitoring method for real-time assessment of students' classroom understanding based on EEG data and deep learning. By addressing the limitations of traditional teaching assessment methods, this approach aims to provide educators with more accurate and timely feedback. The proposed method utilizes specific EEG data, advanced data processing techniques, and deep learning algorithms to achieve high-accuracy monitoring.

关键词： Deep learning Accuracy Cognitive processes Educational technology Data processing Electroencephalography Real-time systems Monitoring Random forests Consumer electronics

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