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检索条件"主题词=detection algorithms"

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Context Encoded Multi-Modal Attention Network for Detecting Audio Spoofing

Context Encoded Multi-Modal Attention Network for Detecting ...

引用

IEEE International Joint Conference on Biometrics (IJCB)

作者： Rishabh Ranjan Mayank Vatsa Richa Singh Indian Institute of Technology Jodhpur Jodhpur India

ISBN: (数字)9798350364132

ISBN: (纸本)9798350364149

Humans interpret speech through both acoustic and textual signals. Recognizing the importance of incorporating contextual information into speech processing, especially for spoofing detection, we introduce a multimodal representation framework that integrates text with audio signals to enhance spoof detection effectiveness. This research advances in two significant ways: firstly, through the creation of a new multimodal spoof detection model called Raw-BERT, and secondly, by developing an innovative multi-headed multimodal attention network that synergistically merges text and audio data for enhanced detection capabilities. We have extensively evaluated the proposed framework across diverse datasets in various languages, demonstrating that the addition of textual context significantly boosts model performance. Overall, the proposed model demonstrates superior results, consistently outperforming existing spoof detection algorithms in multiple evaluations on benchmark audio spoofing datasets.

关键词： Deepfakes Text recognition Biological system modeling Speech recognition Feature extraction Robustness Speech processing detection algorithms Streams Context modeling

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A Hybrid Vision/Force Control Strategy for Handheld Robotic Devices Enhancing Probe-Based Confocal Laser Endomicroscopy

A Hybrid Vision/Force Control Strategy for Handheld Robotic ...

引用

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Ingu Choi Eunchan Kim Sungwook SW Campus HL Mando Seongnam South Korea LG Electronics Seoul Korea Center for Intelligent and Interactive Robotics Korea Institute of Science and Technology Seoul South Korea

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

We introduce a novel hybrid vision/force control strategy for robotic devices designed to obtain clear and consistent images using probe-based confocal laser endomicroscopy (pCLE). Due to the variable nature of tissue characteristics encountered during pCLE imaging, the conventional approach of pre-setting forces or focus metrics for either force or vision control is often impractical and inadequate. To address this, our strategy employs a blur metric called the CR score to assess the level of blur in pCLE images, enabling the attainment of clear and focused images. At the onset of a pCLE scan, the system autonomously determines the target CR score for vision control, in tandem with a real-time peak detection algorithm. Concurrently, force control is applied judiciously to prevent excessive force on the tissue, adjusting to ensure minimal force is applied, thus preserving image focus. This innovative approach facilitates seamless transitions between vision and force control, depending on the imaging conditions, thereby ensuring the acquisition of consistent pCLE images with minimal force. Our method marks a notable improvement over conventional PID force control techniques. By dynamically adjusting target forces and minimizing force application during operation, we not only enhance the precision and quality of pCLE imaging but also eliminate the dependency on manual pre-settings.

关键词： Measurement Force Lasers Imaging Endomicroscopy Real-time systems Force control detection algorithms Intelligent robots

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Unmasking Deep Fakes: Detecting Low-Quality Forgeries through Unseen Artifacts

Unmasking Deep Fakes: Detecting Low-Quality Forgeries throug...

引用

Electronics and Sustainable Communication Systems (ICESC), 2020 International Conference on

作者： M. Venkateshwarlu M. Yashaswi Dhanya Shah R. Akash Reddy Department of Computer Science and Engineering(AI & ML) Vignan Institute of Technology and Science Nalgonda Telangana

ISBN: (数字)9798350379945

ISBN: (纸本)9798350379952

The spread of deepfakee-technology is a danger to the veracity of multimedia material, since it may be used to manipulate people's identities or spread false information. Low-quality forgeries continue to be difficult to detect because of their subtle artifacts, which elude traditional detection approaches. This is true even while deep fake detection algorithms have made significant progress in identifying high-quality forgeries. This research work presents a unique method for identifying hidden elements in low-quality forgeries, which may be used to uncover deep fakes. The proposed approach, which makes use of sophisticated machine learning algorithms and computer vision techniques, is centred on locating and taking advantage of distinctive artifacts that are introduced throughout the deep fake production process. This study provides a thorough analysis of these artefacts and show how well they can distinguish between real multimedia material and poor-quality deep fakes. The proposed technique is effective in properly detecting low-quality forgeries of photos, videos, and audio recordings. These findings are based on experiments conducted on a variety of datasets. Additionally, the proposed method's resilience is assessed against the cutting-edge deep fake creation techniques and emphasize its practical benefits in preventing the distribution of false information.

关键词： Deepfakes Computer vision Machine learning algorithms Communication systems Neural networks Production Streaming media Forgery detection algorithms Resilience

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Global Path Planning for A Vessel Based on Improved Ant Colony Algorithm

Global Path Planning for A Vessel Based on Improved Ant Colo...

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Computer, Big Data and Artificial Intelligence (ICCBD+AI), International Conference on

作者： Pengfei Xu Xiaori Gao Lidong Wang Chongzhang Wang Navigation College Dalian Maritime University Dalian China School of Science Dalian Maritime University Dalian China

ISBN: (数字)9798331533991

ISBN: (纸本)9798331534004

This study presents a global path planning algorithm utilizing an enhanced ant colony algorithm to overcome challenges like vulnerability to local optima, inadequate pheromone update, and suboptimal paths in traditional ant colony algorithms for global path planning of vessels. First, an improved heuristic function is introduced to overcome the problem of local optima. Subsequently, an adaptive pheromone evaporation coefficient is employed to balance the convergence of the algorithm in different stages. Finally, an adjacent node detection algorithm for obstacles is designed to ensure that the optimized path aligns with maritime practice. The simulation results confirm the proposed algorithm's effectiveness. This research provides valuable insights and practical recommendations for global path planning in maritime navigation.

关键词： Navigation Simulation Big Data Approximation algorithms Path planning Evaporation Marine vehicles detection algorithms Standards Convergence

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Interference Impact on BeiDou Signal Reception Performance

Interference Impact on BeiDou Signal Reception Performance

引用

IEEE International Conference on Civil Aviation Safety and Information Technology (ICCASIT)

作者： Zhao Qingtian Wang Jing China CAST Zhongyu (Beijing) New Technology Development Co. Ltd Beijing China China Railway Fifth Survey and Design Institute Group Beijing China

ISBN: (数字)9798350389418

ISBN: (纸本)9798350389425

The BeiDou satellite receiving signal is interfered, and its receiving performance will be greatly affected, and even the signal will not be captured directly. Based on equivalent carrier-to-noise ratio, a method to evaluate the reception performance of BeiDou signal is presented, the influence of interference on reception performance of BeiDou signal is studied, and the relationship between the relevant evaluation parameters and the equivalent carrier-to-noise ratio and its calculation method is analyzed. Finally, through MATLAB simulation, the relationship between the reception performance of the signal and the equivalent carrier-to-noise ratio and the pre-detection integration time are obtained. Comparison results show that the greater the interference power is, the closer the center frequency of the interference is to the center of the band of the signal, and the smaller the equivalent carrier-to-noise ratio is, the poorer the reception performance of the signal is; under the same interference conditions, increasing the pre-detection integration time of the carrier tracking loop can reduce the influence of interference on the reception performance of the BeiDou signal.

关键词： Time-frequency analysis Tracking loops Satellites Interference Bandwidth Vectors Safety detection algorithms MATLAB Testing

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Joint Multi-Agent Trajectory Prediction for Cooperative Vehicle Infrastructure System

Joint Multi-Agent Trajectory Prediction for Cooperative Vehi...

引用

Conference on Vehicle Control and Intelligence (CVCI)

作者： Qian Chen Tan Liu Zhen Gao Rongjie Yu Jian Sun Peng Hang Department of Traffic Engineering Key Laboratory of Road and Traffic Engineering Ministry of Education Tongji University Shanghai China School of Software Engineering Tongji Univeristy Shanghai China

ISBN: (数字)9798331504892

ISBN: (纸本)9798331504908

In the context of Cooperative Vehicle Infrastructure System(CVIS) communication, predicting multi-agent trajectories from a global perspective is crucial. Accurate prediction of behaviors and trajectories can provide decision-making guid-ance for Connected and Automated Vehicles(CAVs). This paper proposes a scene-consistent multi-agent trajectory prediction model. In this work, the scene is firstly divided into several weakly correlated subgraphs. Within each sub graph, A revised LaneGCN is employed to encode agents and HD-Map, and the joint prediction task is decomposed into a series of marginal and conditional predictions by proposed directed interaction graph predictor, increasing the interpretability of future predictions. Experiments conducted on the INTERACTION and Soochow roadside dataset validate the effectiveness of the model.

关键词： Accuracy Decision making Predictive models Prediction algorithms Trajectory Partitioning algorithms detection algorithms

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Challenges of Processing Data Clumps within Plugin Architectures of Integrated Development Environment

Challenges of Processing Data Clumps within Plugin Architect...

引用

IDE Workshop (IDE), IEEE/ACM

作者： Nils Baumgartner Elke Pulvermüller Software Engineering Research Group School of Mathematics/Computer Science/Physics Osnabrück University Germany

ISBN: (数字)9798400705809

ISBN: (纸本)9798350364880

In this study, we explore advanced strategies for enhancing software quality by detecting and refactoring data clumps, special types of code smells. Our approach transcends the capabilities of integrated development environments, utilizing a novel method that separates the detection of data clumps from the source access. This method facilitates data clump processing. We introduce a command-line interface plug in to support this novel method of processing data clumps. This research highlights the efficacy of modularized algorithms and advocates their integration into continuous workflows, promising enhanced code quality and efficient project management across various programming and integrated development environments.

关键词： Computer languages Codes Conferences Project management Data visualization Software quality Computer architecture Programming detection algorithms Plugs

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Comparative Evaluation of Model Based Deep Learning Receivers in Coded MIMO Systems

Comparative Evaluation of Model Based Deep Learning Receiver...

引用

IEEE Conference on Vehicular Technology (VTC)

作者： Aritra Mazumdar Carles N. Manchon Oana E. Barbu Ramoni O. Adeogun Department of Electronic Systems Aalborg University Aalborg Denmark Nokia Bell Labs Aalborg Denmark

ISBN: (数字)9798331517786

ISBN: (纸本)9798331517793

Deep learning (DL) methods have shown potential in tackling the performance-complexity trade-off in multiple-input multiple-output (MIMO) detection. Unlike most studies that evaluate state-of-the-art (SoA) DL receivers in uncoded scenarios, our paper focuses on realistic coded MIMO systems. After a comprehensive literature review, three representative SoA model-based DL receivers viz: DetNet, OAMPNet2, and DUIDD (MMSE-PIC and LoCo-PIC) were selected and comprehensively evaluated. Our findings indicate that DL receivers such as DetNet and OAMPNet2, which base their classical designs on the principle of symbol denoising, fail to sustain their superior performances from uncoded systems to coded systems due to inaccurate residual noise statistics. In contrast, DUIDD, specifically designed for coded systems, achieves effective interference cancellation, resulting in improved coded bit error rates across i.i.d. Gaussian channels, suggesting promising avenues for future research. However, LoCo-PIC, which simplifies MMSE-PIC with a linear solution, suffers performance degradation in correlated urban microcell channels, highlighting the importance of considering the non-linear correlation impacts during detection. Additionally, this simplification leads to further degradation in out-of-distribution channel scenarios, emphasizing the need to address these impacts in realistic wireless systems with varying channel conditions.

关键词： Wireless communication Interference cancellation Noise reduction Noise Receivers Iterative methods detection algorithms MIMO communication Iterative decoding Optimization

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Development of Novel 3D Face Masks for Assessment of Face Recognition Systems

Development of Novel 3D Face Masks for Assessment of Face Re...

引用

International Conference of the Biometrics Special Interest Group (BIOSIG)

作者： Lambert Igene Afzal Hossain Richard Plesh Sandip Purnapatra Surendra Singh Masudul Imtiaz Stephanie Schuckers Department of Electrical and Computer Engineering Clarkson University Potsdam NY USA

ISBN: (数字)9798350373714

ISBN: (纸本)9798350373721

Face recognition is integral to identity management and access control systems, but the rise of biometric face recognition has raised concerns about the vulnerability of Presentation Attack detection (PAD) to various attacks. This paper focuses on developing and evaluating novel, low-cost 3D presentation attack instruments (PAIs) to test the performance of advanced biometric systems. Our PAIs include specialized bobbleheads, white resin 3D-printed masks, white filament 3D masks, masks with image projections, and projections on generic mannequin heads. This project aims to create a diverse, cost-effective PAI dataset to enhance PAD training. We evaluated the effectiveness of these 3D PAIs using three algorithms (Fraunhofer IGD, CLFM, and FaceMe) from the Liveness detection Face Competition 2021 (LivDet Face, 2021). Additionally, we conducted a comparison between PAIs and bona fide samples using the ArcFace face comparator, achieving an Imposter Attack Presentation Match Rate (IAPAR) of 70% for bobbleheads and 43% for white resin with projection. Our preliminary assessment indicates an Average Classification Error Rate (ACER) of 10.6%, demonstrating the potential of these new PAIs to improve PAD training.

关键词： Training Three-dimensional displays Head Error analysis Face recognition Instruments Production Classification algorithms Resins detection algorithms

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A lightweight network for detecting and monitoring wildfire cores using UAV thermal imagery

A lightweight network for detecting and monitoring wildfire ...

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International Conference on Control, Automation and Systems ( ICCAS)

作者： Wang Linfeng Doukhi Oualid Dae Uk Kang Deok Jin Lee Department of Mechanical Design Engineering Jeonbuk National University School of Mechanical Design Engineering Center for Autonomous Intelligence & e-Mobility

ISBN: (数字)9788993215380

ISBN: (纸本)9798331517939

The occurrence of wildfires poses major challenges to disaster management and environmental protection, so early fire monitoring and management is crucial. With advances in deep learning, early wildfire detection algorithms from a drone perspective offer a promising solution. However, the complex fire environment results in low detection accuracy and poor real-time performance. Therefore, a lightweight real-time flame core detection algorithm based on UAV infrared images to solve the above problems is introduced. This paper proposes many innovative techniques that are different from existing algorithms. Firstly, this paper introduces a novel drone infrared imagery fire core dataset, utilizing infrared images for detection to circumvent obstruction issues. Secondly, an efficient processing (EP) module and a lightweight feature-sharing decoupled detection head (Fast head) are introduced to reduce network complexity. Finally, this work proposes Adaptive Sample Attention Loss (ASA loss) and simultaneously adopts Normalized Wasserstein Distance loss (NWD loss), which improves the network's detection accuracy for small and long-distance fires. Experimental verification shows that the model size of our algorithm is only 4.0M, which is 36.5% smaller than the original YOLOv8n network, and the number of parameters is reduced by 38%. The computational requirement was only 5 GFLOPs (-38.3%) and an average precision (mAP) of 77.5% (@50-95 IOU) was achieved, a 1% improvement.

关键词： Wildfires Head Accuracy Autonomous aerial vehicles Feature extraction Real-time systems detection algorithms Protection Monitoring Drones

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