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Online Optimization of Offloading Video Analytics Tasks to Multiple Edges for Accuracy Maximization

Online Optimization of Offloading Video Analytics Tasks to M...

引用

International conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： Yu Liang Sheng Zhang Jie Wu School of Computer and Electronic Information and the School of Artificial Intelligence Nanjing Normal University State Key Laboratory for Novel Software Technology Nanjing University Center for Networked Computing Temple University US

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Real-time video analytics (VA) presents challenges due to its computational intensity and latency sensitivity, especially when processed on mobile devices with limited local resources. We propose to offload VA tasks to edge servers with diverse computational capabilities. We present a "detect + track" approach with on-device object tracking and edge-assisted object detection. We formulate a long-term nonlinear integer programming to maximize the overall accuracy within detection frequency and latency constraints. We then design a queue-based online optimization algorithm to solve it: relax the original problem from the integer domain to the real domain, then employ a queue-based adaptation and randomized rounding strategy. Via rigorous proof, both dynamic regret regarding detection accuracy and the real-time requirement are ensured. Evaluation results also demonstrate the effectiveness of our approach.

关键词： Accuracy image edge detection visual analytics Signal processing algorithms Streaming media Signal processing Real-time systems Servers Speech processing Optimization

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image Recognition and Analysis of Computer Interlock Interface Based on OpenCV Technology

Image Recognition and Analysis of Computer Interlock Interfa...

引用

ieee Advanced Information Management,Communicates,Electronic and Automation Control conference (IMCEC)

作者： Xuanmo Chen Qiang Li College of Computer Science and Technology Lanzhoujiaotong University Lanzhou China Key Laboratory of Optoelectronic Technology and Intelligent Control Ministry of Education Province Lanzhou China

ISBN: (数字)9798350316537

ISBN: (纸本)9798350316544

An integrated computerized locking mechanism is vital for upholding the safety of train movements within railway networks. As computer technology progresses swiftly, conventional locking systems are encountering a multitude of difficulties, with the identification and processing of visual interface data being a key challenge. Furthermore, the pace of technological innovation has led to an array of other obstacles for these systems to surmount. The deployment of cutting-edge technologies, including AI and machine learning, has markedly enhanced the functionality and security of these mechanisms. Anticipatedly, the future will witness the development of even more sophisticated and secure railway traffic management systems. These evolving technologies serve as formidable instruments in tackling the prevailing issues and challenges. Specifically, the computerized interface locking system is indispensable in guaranteeing the safe running of trains within railway *** paper applies the image processing capability of OpenCV to preprocess and extract characteristics from the interlocking interface image. Subsequently, the enhanced clustering algorithm of RV-DBSCAN is utilized to identify the text of signaling equipment diagrams, followed by the implementation of the Paddle OCR (Optical Character Recognition) machine learning algorithm to classify and identify the images. The recognition accuracy rate for information related to railway signaling equipment stands at 92.6%. This process offers a dependable approach for extracting and recognizing station information from computerized interlocking interfaces.

关键词： visualization Technological innovation image recognition Machine learning algorithms Optical character recognition Software algorithms Clustering algorithms

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AI-Powered Optimization and Integrity of Hydro Power Plants

AI-Powered Optimization and Integrity of Hydro Power Plants

引用

International conference on Computer and communications Technologies (ICCCT)

作者： Sheela A Navneeth S Yokeshwaran M Sanjeevei A Computer Science and Engineering Sri Sai Ram Engineering College

ISBN: (数字)9798331537579

ISBN: (纸本)9798331537586

This research addresses the critical task of crack detection, essential for maintaining the safety and integrity of various structures. Detecting cracks is vital for ensuring the longevity and reliability of infrastructures such as buildings, bridges, and roads. Traditional methods like manual visual inspections are often ineffective, subjective, and prone to human error. This paper introduces an automated crack detection approach using grayscale image processing techniques to improve accuracy. The methodology involves converting images to grayscale, enhancing contrast, and applying edge detection algorithms along with morphological operations to effectively identify and isolate cracks. The experimental findings demonstrate that this approach not only accurately detects cracks but also minimizes false positives and reduces computational complexity. This research offers a practical automated solution for crack detection and paves the way for future advancements, including real-time monitoring with machine learning for more comprehensive and scalable infrastructure health assessment.

关键词： visualization Accuracy image edge detection Roads Machine learning Gray-scale Solids Real-time systems Safety Morphological operations

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Volatile MAB-based Configuration Selection for Offloading Video Analytics Tasks to Edges

Volatile MAB-based Configuration Selection for Offloading Vi...

引用

International conference on Acoustics, Speech, and Signal processing (ICASSP)

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

The demand for video analytics is increasing rapidly. Due to the limited computational and network resources on edge servers, adjusting video configurations such as resolution and frame rate has become an effective strategy to reduce computational and transmission costs. However, this can also compromise detection accuracy, necessitating a balance between resource consumption and analytics accuracy. Also, the dynamic availability of edge servers and variability in their energy consumption further complicates making offloading decisions and configuration selection. In this paper, we first model the problem as a mixed planning program. Then we propose a volatile MAB-based configuration selection algorithm, VACS, which aims to maximize video analytics accuracy while reducing the overall energy consumption. Rigorous proof measures the gap between online decisions and the optimum. Extensive experiments validate the effectiveness of VACS.

关键词： Energy consumption Accuracy visual analytics image edge detection Heuristic algorithms Signal processing algorithms Signal processing Planning Servers Speech processing

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Multi-Sensor Fusion SLAM Based on Fast Euclidean Clustering to Filter Dynamic Targets

Multi-Sensor Fusion SLAM Based on Fast Euclidean Clustering ...

引用

ieee International conference on Signal and image processing (ICSIP)

作者： Ming Geng Yongxing Jia Xiaojian Qian Ziang Zhao College of Communications Engineering Army Engineering University of PLA Nanjing China

ISBN: (数字)9798350350920

ISBN: (纸本)9798350350937

R3LIVE is a new multi-sensor fusion SLAM framework, which mainly uses the three sensors of lidar, camera and IMU to realize the effective fusion of heterogeneous data through the error state iterative Kalman filtering method, so as to achieve the function of efficient and accurate simultaneous positioning and mapping. Specifically, this system uses lidar and IMU to construct laser inertial odometer (LIO) to construct the geometry of the external environment, and also it builds a visual inertial odometer (VIO) with a camera and IMU to reconstruct a dense RGB map of the environment. However, in the face of the environment where dynamic objects appear, the positioning accuracy of the system will be affected due to the point cloud of the sensor on the dynamic objects. Moreover, the continuous point cloud of the dynamic objects will cause continuous “ghost” in the dense RGB map constructed. In order to solve the above problems, a fast Euclidean clustering algorithm is proposed to filter out dynamic targets, that is, before the LIO system laser point cloud registration, the input point cloud is initially classified by using a fast Euclidean clustering algorithm, and the original point cloud is divided into ground points, background points and foreground points, among which the ground points and background points are usually considered static points. The foreground points may be either dynamic or static points. Then, the viewpoint visibility method is used for the foreground points to further verify the existence of dynamic points, and the dynamic points in the foreground points are filtered out. Finally, a widely distributed sparse extraction method is designed to solve the problem of excessive extraction of surface features in scenes with rich structure and texture. This enhances the real-time performance and robustness of the system in dynamic scenarios.

关键词： Point cloud compression visualization Accuracy Simultaneous localization and mapping Heuristic algorithms Clustering algorithms Filtering algorithms

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A multi-modal dataset for analyzing the imageability of concepts across modalities 4

A multi-modal dataset for analyzing the imageability of conc...

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ieee 4th International conference on Multimedia Information processing and Retrieval (ieee MIPR)

作者： Kastner, Marc A. Matsuhira, Chihaya Ide, Ichiro Satoh, Shin'ichi Natl Inst Informat 2-1-2 HitotsubashiChiyoda Ku Tokyo 1018430 Japan Nagoya Univ Grad Sch Informat Furo ChoChikusa Ku Nagoya Aichi 4648601 Japan Nagoya Univ Math & Data Sci Ctr Furo ChoChikusa Ku Nagoya Aichi 4648601 Japan

ISBN: (纸本)9781665418652

Recently, multi-modal applications bring a need for a human-like understanding of the perception differences across modalities. For example, while something might have a clear image in a visual context, it might be perceived as too technical in a textual context. Such differences related to a semantic gap make a transfer between modalities or a combination of modalities in multi-modal processing a difficult task. imageability as a concept from Psycholinguistics gives promising insight to the human perception of vision and language. In order to understand cross-modal differences of semantics, we create and analyze a cross-modal dataset for imageability. We estimate three imageability values grounded in 1) a visual space from a large set of images, 2) a textual space from Web-trained word embeddings, and 3) a phonetic space based on word pronunciations. A subset of the corpus is evaluated with an existing imageability dictionary to ensure a basic generalization, but otherwise targets finding cross-modal differences and outliers. We visualize the dataset and analyze it regarding outliers and differences for each modality. As additional sources of knowledge, part-of-speech and etymological origin of all words are estimated and analyzed in context of the modalities. The dataset of multi-modal imageability values and a link to an interactive browser with visualizations are made available on the Web.

关键词： visualization Dictionaries Grounding conferences Semantics Data visualization Information processing

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Automatic SPECT image processing for Parkinson’s Disease Early Detection 4th

Automatic SPECT Image Processing for Parkinson’s Disease Ea...

引用

4th International conference on Smart Applications and Data Analysis, SADASC 2022

作者： Boucherouite, Jihad Jilbab, Abdelilah Jbari, Atman E2SN ENSAM Mohammed V University in Rabat Rabat Morocco

ISBN: (纸本)9783031204890

The absence of an effective cure to Parkinson as a neurodegenerative disease calls for early diagnosis and appropriate therapeutic process to provide patients with better quality of treatment. Therefore, to diagnose Parkinson’s Disease (PD) at its early stage, clinicians rely on visual observation of dopaminergic deficit in both caudate and putamen in the striatum region of the brain. SPECT images (Single Photon Emission Computed Tomography) are among functional neuroimaging scans that can show putamen and caudate, and hence help visualizing Dopamine deficit. In this work, we developed an automatic SPECT image model to classify patients as Healthy Control (HC) or Early PD, starting from Dicom SPECT images from PPMI (Parkinson’s Progression Markers Initiative) database to Machine learning classification. The approach we proposed starts with image processing of SPECT images, then extraction of boundary, radial, Striatal Binding Ratio (SBR) and threshold features, then classification using Support Vector Machine (SVM). To the best of our knowledge, no work in the literature has used this combination of the mentioned features together in the classification model. The use of this combination demonstrates promising results. We used a database of 526 images, with 130 HC and 396 PD. The results of our approach show that the Medium Gaussian SVM has a high performance with an accuracy of 97.3%, sensitivity of 95.3%, and specificity of 98%. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Single photon emission computed tomography

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Dermoscopic images Classification Using Pretrained VGG-16 and ResNet-50 Models

Dermoscopic Images Classification Using Pretrained VGG-16 an...

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International conference on Advanced Technologies for Signal and image processing (ATSIP)

作者： Sirine Mejri Afef Elloumi Oueslati SITI Laboratory National School of Engineers of Tunis (ENIT) BP37 le Belvédère University Tunis El Manar Tunis Tunisia National School of Engineers of Carthage (ENICarthage) 45 Rue des Entrepreneurs 2035 Charguia II University of Carthage Tunisia

ISBN: (数字)9798350351484

ISBN: (纸本)9798350351491

Skin cancer is the uncontrolled proliferation of skin’s cells due to overexposure to ultraviolet (UV) radiation. It can be classified into benign and malignant lesions, the last ones are deadly and have the potential to metastasize. For example, melanoma, a type of malignant lesion, can spread extensively and is fatal. For this reason, early detection is crucial as it helps avoid the need for time-consuming biopsies and reduces the impact of heavy treatments for patients. This research introduces an automated skin cancer classification system using ISIC archive dataset (International Skin Imaging Collaboration) from Kaggle. In this study, we focus on deep learning, particularly transfer learning, when we use VGG-16 (visual Geometry Group) and ResNet-50 model (Residual Network) for the classification of dermoscopic images. The VGG-16 model achieves an accuracy of 91.20%, while ResNet50 model achieves an accuracy of 92.80%. In conclusion, our study presents encouraging results that could assist dermatologists in their diagnosis.

关键词： visualization Accuracy image processing Transfer learning Melanoma Transformers Skin

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DNN-Based Speech Re-Reverb for VR Rooms

DNN-Based Speech Re-Reverb for VR Rooms

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ieee Region 10 International conference TENCON

作者： Ian McLoughlin Jeannie S.A. Lee Indriyati Atmosukarto Ding Zhongqiang InfoComm Technology Cluster Singapore Institute of Technology Singapore Merry Electronics Co. Ltd.

ISBN: (数字)9798350350821

ISBN: (纸本)9798350350838

Reverberation is a physical phenomena caused by room impulse reflection from walls, ceilings and other plane surfaces. When occurring in speech, it contributes an additive echo to the speech which is proportional to the geometry of the environment in which that speech was recorded. Reverberation is not just noise though, as the echo timing in speech affects its intelligibility as well as the listener's interpretation of the playback environment. It gives listeners a sense of the size, shape and materials of the room it is in. For communications scenarios where playback reverberation differs significantly from the visual display (e.g. speech recorded in a small room but played back in a cavernous virtual reality (VR) space), a psychoacoustic dissonance arises between visual and auditory perception. This paper presents an AI-based algorithm to remove source room reverberation impulse effects from speech. We then add reverberation to match the target playback environment. To assess effectiveness, we simulate a set of recording room geometries, and perform psychoacoustic assessment to estimate the effect on a human listener.

关键词： Psychoacoustics Geometry visualization Shape Shape measurement Virtual reality Reflection Timing Reverberation Speech processing

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A Comprehensive Privacy Protection Solution: Enhancing Face Obscuring Techniques with Automated Identification, Mobile Integration, and Scalable Services

A Comprehensive Privacy Protection Solution: Enhancing Face ...

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2025 ieee International conference on Consumer Electronics, ICCE 2025

作者： Kim, Ilhwan Oh, Hyeongseok Yun, Sangwoo Lim, Heunseung Ryu, Jaeseok Paik, Joonki Image Processing and Intelligent System Laboratory Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University Seoul Korea Republic of Image Processing and Intelligent System Laboratory Graduate School of Artificial Intelligence Chung-Ang University Seoul Korea Republic of

ISBN: (纸本)9798331521165

We propose a novel application aimed at protecting personal privacy. With the proliferation of various media platforms, issues related to personal portraits have emerged. To address these problems, previous applications propose methods for either Mosaic or replace it with another object. However, existing methods suffer from issues such as high time costs and unnatural rendering. To address these problems, we propose designing an automatic face identification and replacement system by combining face detection, super-resolution, and face replacement models. This approach aims to reduce processing time and enhance natural rendering. In addition to the technological advancements, we suggest expanding this system into a mobile service, allowing users to easily protect their privacy on the go. This mobile platform would provide a user-friendly interface and seamless integration with various social media and communication apps, making it accessible to a broader audience. Furthermore, we explore potential expansion opportunities, such as cloud-based processing for scalability and the development of APIs that other developers can integrate into their own applications, thereby broadening the service's reach and impact. We demonstrate that our approach is simpler and more natural compared to traditional handcrafted tasks by applying it to diverse scenarios. © 2025 ieee.

关键词： Rendering (computer graphics)

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