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检索条件"任意字段=Conference on Real-Time Image and Video Processing 2011"

共 8701 条记录，以下是251-260 订阅

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2024 13th Mediterranean conference on Embedded Computing, MECO 2024

2024 13th Mediterranean Conference on Embedded Computing, ME...

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13th Mediterranean conference on Embedded Computing, MECO 2024

ISBN: (纸本)9798350387568

The proceedings contain 114 papers. The topics discussed include: application of artificial neural networks for processing some biomedical data;distinguishing between AI images and real images with hybrid image classification methods;securing Durres Port's digital transformation: cybersecurity strategy for maritime industry;linguistic encryption for underwater communication;a toolset for blood pressure visualization and measurement in time, frequency and time-frequency domains;using a shape from polarization to determine the 3D surface of objects with thermal radiation;on the influence of cell libraries and other parameters to SCA resistance of crypto IP cores;integration of PXROS-HR with micro-ROS in robotic systems;and traffic-aware video streaming topology reconfiguration for smart city applications.

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UnDIVE: Generalized Underwater video Enhancement Using Generative Priors

UnDIVE: Generalized Underwater Video Enhancement Using Gener...

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2025 IEEE/CVF Winter conference on Applications of Computer Vision, WACV 2025

作者： Srinath, Suhas Chandrasekar, Aditya Jamadagni, Hemang Soundararajan, Rajiv Prathosh, A.P. Indian Institute of Science India Qualcomm United States National Institute of Technology Karnataka India

ISBN: (纸本)9798331510831

With the rise of marine exploration, underwater imaging has gained significant attention as a research topic. Under-water video enhancement has become crucial for real-time computer vision tasks in marine exploration. However, most existing methods focus on enhancing individual frames and neglect video temporal dynamics, leading to visually poor enhancements. Furthermore, the lack of ground-truth references limits the use of abundant available underwater video data in many applications. To address these issues, we propose a two-stage framework for enhancing underwater videos. The first stage uses a denoising diffusion probabilistic model to learn a generative prior from unlabeled data, capturing robust and descriptive feature representations. In the second stage, this prior is incorporated into a physics-based image formulation for spatial enhancement, while also enforcing temporal consistency between video frames. Our method enables real-time and computationally-efficient processing of high-resolution underwater videos at lower resolutions, and offers efficient enhancement in the presence of diverse water-types. Extensive experiments on four datasets show that our approach generalizes well and outperforms existing enhancement methods. Our code is available at github. com/suhas-srinath/undive. © 2025 IEEE.

关键词： Photointerpretation

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11th Pacific-Rim Symposium on image and video Technology, PSIVT 2023

11th Pacific-Rim Symposium on Image and Video Technology, PS...

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11th Pacific-Rim Symposium on image and video Technology, PSIVT 2023

ISBN: (纸本)9789819703753

The proceedings contain 34 papers. The special focus in this conference is on image and video Technology. The topics include: Spatial Variation Sequences for Remote Sensing Applications with Small Sample Sizes;exploring the Potential of High-Resolution Drone imagery for Improved 3D Human Avatar Reconstruction: A Comparative Study with Mobile images;point Cloud Novelty Detection Based on Latent Representations of a General Feature Extractor;Efficient 3Dconv Fusion of RGB and Optical Flow for Dynamic Hand Gesture Recognition and Localization;an Investigation of video Vision Transformers for Depression Severity Estimation from Facial video Data;real-time Automated Body Condition Scoring of Dairy Cows;Logo-SSL: Self-supervised Learning with Self-attention for Efficient Logo Detection;HAHANet: Towards Accurate image Classifiers with Less Parameters;evaluating Mammogram image Classification: Impact of Model Architectures, Pretraining, and Finetuning;melanoma Classification Using Deep Learning;3D Formation Control of Multiple Cooperating Autonomous Agents via Leader-Follower Strategy;LAPRNet: Lightweight Airborne Particle Removal Network for LiDAR Point Clouds;real-NET: A Monochromatic Depth Estimation Using REgional Attention and Local Feature Mapping;Spike-EFI: Spiking Neural Network for Event-Based video Frame Interpolation;scrambleMix: A Privacy-Preserving image processing for Edge-Cloud Machine Learning;Comparison of Simplified SE-ResNet and SE-DenseNet for Micro-Expression Classification;facial Deepfake Detection Using Gaussian Processes;A Novel Steganography Scheme Using Logistic Map, BRISK Descriptor, and K-Means Clustering;a Holistic Approach to Elderly Safety: Sensor Fusion, Fall Detection, and Privacy-Preserving Techniques;cluster-Based video Summarization with Temporal Context Awareness;On Deploying Mobile Deep Learning to Segment COVID-19 PCR Test Tube images;enhancing Safety During Surgical Procedures with Computer Vision, Artificial Intelligence, and Natural

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MorphVAD: Efficient video Anomaly Detection Using Morphological Transformation

MorphVAD: Efficient Video Anomaly Detection Using Morphologi...

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2023 IEEE International conference on Visual Communications and image processing, VCIP 2023

作者： Do, Jeonghyeok Kim, Munchurl Korea Advanced Institute of Science and Technology School of Electrical Engineering Daejeon Korea Republic of

ISBN: (纸本)9798350359855

video anomaly detection aims to identify unusual events within video sequences. Approaches that rely on reconstruction and prediction have shown impressive success in this area and continue to be actively explored. However, recent techniques often rely on pre-Trained external components such as optical flow or segmentation maps to handle the challenge of removing background that constitutes a substantial portion of video content. These additional modules, due to their computational complexity, introduce a noteworthy trade-off, particularly in real-time video anomaly detection, where timely monitoring is paramount. So, this paper introduces an efficient video anomaly detection method (MorphVAD) that is based on a novel morphology-based masking module (Morph-Mask). The Morph-Mask harnesses the straightforward concept of morphological transformations to create masks that highlight foreground elements. So, our MorphVAD strategically incorporates these masks during the training phase, focusing on retaining only foreground-related information in memory. Through illustrative experiments and various evaluations, we demonstrate the efficiency and effectiveness of these masks detection, showing the significant enhancements in video anomaly detection performance. © 2023 IEEE.

关键词： Anomaly detection

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Design and Application of image Recognition Framework Based on Cloud Edge Collaboration in Distribution Stations 5

Design and Application of Image Recognition Framework Based ...

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5th IEEE International conference on Power, Intelligent Computing and Systems, ICPICS 2023

作者： Wu, Wenwei Zhang, Lishou Kang, Kai Liu, Juntao State Grid Shanghai Municipal Electric Power Company Construction and Operation Center Shanghai China Shanghai Yitong Information Technology Co. Ltd R and D Department Shanghai China

ISBN: (纸本)9798350333442

Targeted on the intelligent identification and cloud load reduction requirements of power system in video monitoring, a vision analysis system platform and implementation scheme for distribution station based on cloud edge system are proposed. Through multi-source data fusion analysis, optimization of defect fault location, image recognition algorithm, cloud edge threshold classification collaboration, image processing and feature extraction technologies such as YOLOv3, Mask-CRNN, etc., the high-definition real-time image is analyzed, and the main equipment status recognition and security abnormal behavior recognition functions of the distribution station are realized. The real-time and accuracy of each analysis function is verified by the on-site distribution station, and the relevant experimental results of some functions in the power grid are compared to show the effectiveness of the system scheme. © 2023 IEEE.

关键词： Internet of things

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real-time Bangla License Plate Recognition System for Low Resource video-based Applications

Real-time Bangla License Plate Recognition System for Low Re...

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22nd IEEE/CVF Winter conference on Applications of Computer Vision (WACV)

作者： Ashrafee, Alif Khan, Akib Mohammed Irbaz, Mohammad Sabik Al Nasim, Md Abdullah Islamic Univ Technol Dept Comp Sci & Engn Gazipur Bangladesh Pioneer Alpha Ltd Machine Learning Team Dhaka Bangladesh

ISBN: (纸本)9781665458245

Automatic License Plate Recognition systems aim to provide a solution for detecting, localizing, and recognizing license plate characters from vehicles appearing in video frames. However, deploying such systems in the real world requires real-time performance in low-resource environments. In our paper, we propose a two-stage detection pipeline paired with Vision API that provides real-time inference speed along with consistently accurate detection and recognition performance. We used a haar-cascade classifier as a filter on top of our backbone MobileNet SSDv2 detection model. This reduces inference time by only focusing on high confidence detections and using them for recognition. We also impose a temporal frame separation strategy to distinguish between multiple vehicle license plates in the same clip. Furthermore, there are no publicly available Bangla license plate datasets, for which we created an image dataset and a video dataset containing license plates in the wild. We trained our models on the image dataset and achieved an AP(0.5) score of 86% and tested our pipeline on the video dataset and observed reasonable detection and recognition performance (82.7% detection rate, and 60.8% OCR F1 score) with real-time processing speed (27.2 frames per second).

关键词： Computer vision image recognition conferences Pipelines Focusing Licenses Streaming media

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real-time FPGA Implementation of Digital video Watermarking Techniques using Co-Design Approach: Comparative Study 7

Real-Time FPGA Implementation of Digital Video Watermarking ...

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7th International conference on image and Signal processing and their Applications, ISPA 2022

作者： Aissaoui, Noureddine Kaibou, Redouane Azzaz, Mohamed Salah Électroniques et Numériques École Militaire Polytechnique Laboratoire Systèmes Alger16111 Algeria

ISBN: (纸本)9781665480420

This paper presents a Genesys-2 FPGA implementation of three video watermarking techniques in both spatial and frequency domains followed by a comparative analysis. The video acquisition is realized using OV7670 camera used for real-time watermarking with each technique both in visible and invisible schemes with video Graphics Adapter (VGA) display validations. The techniques implemented are based on Least Significant bit (LSB), additive spatial and additive frequency watermarking. All implementations have been realized in Software/Hardware (SW/HW) co-design using Vivado-HLS tool achieving low area, high speed of up to 130 MHz and low power consumption that did not exceed 827 mw all along with good watermarking performances of imperceptibility with fairly good robustness for most of the geometric and image processing attacks. © 2022 IEEE.

关键词： Field programmable gate arrays (FPGA)

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5th International Symposium on Signal and image processing, ISSIP 2024

5th International Symposium on Signal and Image Processing, ...

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5th International Symposium on Signal and image processing, ISSIP 2024

ISBN: (纸本)9789819795147

The proceedings contain 31 papers. The special focus in this conference is on Signal and image processing. The topics include: A Blockchain-Based Secure Framework for Storage and Access of Surveillance video Data;encountering the Challenges and Awareness of Internet Security;Data-Driven Strategies for Twitter Engagement: Hashtag Recommendations and API Insights;Analyzing and Visualizing AI Decision-Making for Human-Centered Interaction and Trust;AI-ML-Based Handover Techniques in Next-Generation Wireless Networks;castle Defender: Design and Implementation of Game Based on Pygame;optimizing Healthcare: Enhancing Disease Management with Recommendation Systems;optimizing Diabetes Prediction Models for Enhanced Health Data processing;comparative Analysis of Classification Models Using Various Feature Sets;An Early Detection of Tomato Plant Disease with Deep Reinforcement Learning and CNN;ioT-Powered Health Monitoring System for Protecting Vital Organs Through Cloud-Based Diagnosis;LASKV: Lightweight Authenticated Session Key Agreement for video Surveillance System;Data Analyses of Factors Influencing Sustainable Adoption of Online Public Services: An Extended UTAUT Analysis in North Macedonia;a Comprehensive Review on real-time Campus Compass;deep Learning Approaches for Early Detection of Bovine Respiratory Diseases in Cattle;identifying Suitable Cloud Storage Services from Cross Cloud Platforms Based on the Requirements;storage-Savvy Frame Recorder: Enhancing Storage Efficiency and Inspection Speed*;lossless Medical image Compression Using Block-Wise Burrows–Wheeler Transform and Modified Run Length Encoding;advancing Software Defect Detection and Prevention: Bridging Gaps in Early-Stage and Evolving Software Systems;a New Way to Communicate: Deep Learning for Deaf and Dumb People;dependent Binomial: A Family of Distributions Derivable by Modifying a Base.

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Construction of real-time Analysis System of Sports video images Based on Fuzzy Clustering Algorithm 22

Construction of Real-time Analysis System of Sports Video Im...

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3rd Asia-Pacific conference on image processing, Electronics and Computers, IPEC 2022

作者： Wu, Fang Wuhan Business University Wuhan430056 China

ISBN: (纸本)9781450395786

The core of sports video analysis technology is the analysis of semantic events and their relationships, which is a complex and challenging problem. Its essence lies in the huge gap between the low-level features suitable for computer processing and the high-level semantics suitable for human understanding. The acquisition and analysis of moving images are the main means to acquire the kinematic parameters of objects in the research of sports biomechanics, which is to take pictures of human bodies or objects with cameras, digitize the videos and then analyze them. Due to the complexity and diversity of sports video content, the current sports video analysis results are not very satisfactory. The purpose of this paper is to establish the structure and index of sports video content by computer processing, analysis and understanding, which is of great theoretical significance and application prospect. Combining with fuzzy clustering algorithm, this paper studies the key technologies of sports video analysis, and puts forward the construction idea of sports video image real-time analysis system. © 2022 ACM.

关键词： Fuzzy clustering

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video Smoke Detection Algorithm Based on a Spatial-Temporal Neural Network Model 9

Video Smoke Detection Algorithm Based on a Spatial-Temporal ...

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9th International conference on Intelligent Computing and Signal processing, ICSP 2024

作者： Cao, Zhen Zhang, Xi Shenyang Fire Science and Technology Research Institute Ministry of Emergency Management Shengyang China

ISBN: (纸本)9798350376548

a kind of spatial-temporal neural network video smoke detection algorithm is proposed in order to solve the problems associated with the incorrect classification of the static approximate smoke background in the face of the detection of smoke in video detection networks, and the problem of false alarms and of the original test model algorithms being different in different detection environments. Based on the original YOLO v4 neural network algorithm, this paper introduces a k-means + + algorithm and genetic algorithm, while using the algorithm's clustering function to classify the sample points of the real boxes of the image data set, which make it a more suitable anchor. At the same time, the genetic algorithm is used to adjust its anchor in order to allow the generated anchor to adapt to the needs related to smoke detection. In the original neural network model, the dual-stream network model algorithm is used to extract information from the first step of the YOLO algorithm in order to further filter the smoke's characteristics as well as filter out error information, all to improve the detection capabilities of the overall neural network for video smoke fog images. Compared with traditional YOLOv4 networks, the algorithm obtained by the model algorithm has been improved by 8.51°/0. In actual tests, the alarm time requirements of the smoke alarm test program for early fire monitoring and the alarm systems for visual images were improved, and the detection accuracy of the network was also improved based on the assurance of the detection speed, while the performance of the model algorithm was also improved for different scenes. © 2024 IEEE.

关键词： dual-stream Network K-means safety science smoke detection YOLOv4

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