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检索条件"任意字段=Conference on Real-Time Image Processing 2007"

共 25827 条记录，以下是101-110 订阅

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MULTI-OBJECT TRACKING AS ATTENTION MECHANISM 30

MULTI-OBJECT TRACKING AS ATTENTION MECHANISM

引用

30th IEEE International conference on image processing (ICIP)

作者： Fukui, Hiroshi Miyagawa, Taiki Morishita, Yusuke NEC Corp Ltd Tokyo Japan

ISBN: (纸本)9781728198354

We propose a conceptually simple and thus fast multi-object tracking (MOT) model that does not require any attached modules, such as the Kalman filter, Hungarian algorithm, transformer blocks, or graph networks. Conventional MOT models are built upon the multi-step modules listed above, and thus the computational cost is high. Our proposed end-to-end MOT model, TicrossNet, is composed of a base detector and a cross-attention module only. As a result, the overhead of tracking does not increase significantly even when the number of instances (N-t) increases. We show that TicrossNet runs in real-time;specifically, it achieves 32.6 FPS on MOT17 and 31.0 FPS on MOT20 (Tesla V100), which includes as many as >100 instances per frame. We also demonstrate that TicrossNet is robust to N-t;thus, it does not have to change the size of the base detector, depending on N-t, as is often done by other models for real-time processing.

关键词： Multi-object tracking Attention mechanism Cross-attention mechanism real-time processing End-to-end MOT model

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Comparison of deep generative models for real-time generation of synthesized defective wafer maps

Comparison of deep generative models for real-time generatio...

引用

conference on real-time image processing and Deep Learning

作者： Alam, Lamia Kehtarnavaz, Nasser Univ Texas Dallas Dept Elect & Comp Engn Richardson TX 75080 USA

ISBN: (纸本)9781510673878;9781510673861

Modern wafer inspection systems in Integrated Circuit (IC) manufacturing utilize deep neural networks. The training of such networks requires the availability of a very large number of defective or faulty die patterns on a wafer called wafer maps. The number of defective wafer maps on a production line is often limited. In order to have a very large number of defective wafer maps for the training of deep neural networks, generative models can be utilized to generate realistic synthesized defective wafer maps. This paper compares the following three generative models that are commonly used for generating synthesized images: Generative Adversarial Network (GAN), Variational Auto-Encoder (VAE), and CycleGAN which is a variant of GAN. The comparison is carried out based on the public domain wafer map dataset WM-811K. The quality aspect of the generated wafer map images is evaluated by computing the five metrics of peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM), inception score (IS), Frechet inception distance (FID), and kernel inception distance (KID). Furthermore, the computational efficiency of these generative networks is examined in terms of their deployment in a real-time inspection system.

关键词： Synthesized Wafer Maps Generative Adversarial Network Variational Autoencoder CycleGAN real-time image Synthesis

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End-to-end Prediction of Streaming Video Quality of Experience: Dataset and Approach

End-to-end Prediction of Streaming Video Quality of Experien...

引用

2024 conference on Visual Communications and image processing

作者： Jia, Ziheng Min, Xiongkuo Zhai, Guangtao Shanghai Jiao Tong Univ Inst Image Commun & Network Engn Shanghai Peoples R China

ISBN: (纸本)9798331529543;9798331529550

With the rapid development of video-on-demand (VOD) and real-time streaming video technologies, the accurate objective assessment of streaming video Quality of Experience (QoE) has become a focal point for optimizing streaming-related technologies. However, due to the inherent transmission distortions caused by poor Quality of Service (QoS) conditions in streaming videos, such as intermittent stalling, rebuffering, and drastic changes in video sharpness due to bitrate fluctuations, evaluating streaming video QoE presents numerous challenges. This paper introduces a large and diverse in-the-wild streaming video QoE evaluation dataset - the SJLIVE-1k dataset. This work addresses the limitations of corresponding datasets, which lack in-the-wild video sequences under real network conditions and whose amount of video content is insufficient. Furthermore, we propose an end-to-end objective QoE evaluation strategy that extracts video content and QoS features from the video itself without using any extra information. By implementing self-supervised contrastive learning as the "reminder" to bridge the gap between the different types of features, our approach achieves state-of-the-art results across three datasets. Our proposed dataset will be released to facilitate further research.

关键词： Quality of Experience streaming videos contrastive learning

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Medical image Scalar for Portable Medical Devices 1

Medical Image Scalar for Portable Medical Devices

引用

1st International conference on AIML-Applications for Engineering and Technology, ICAET 2025

作者： Pangaonakar, Mrinalini Joshi Shingare, P.P. College of engineering Pune Dept of E&TC Engineerig Pune India

ISBN: (纸本)9798350355611

The field of image processing is playing a vital role in making technological changes those results in real time applications. image scaling is one of such fundamental method that helps to resolve storage issue and also helps for fast image data transmission. The technique is beneficial in case of real time portable devices and similar applications as usually the scaling required at end user device. This paper proposes medical image scalar for portable medical devices implemented using FPGA which involves creating a compact, efficient, and reliable system capable of adjusting the size and resolution of medical images for display on different devices This medical image scalar can be used for applications such as portable medical devices for remote disease diagnosis, image assisted surgery and other telemedicine applications where image quality, processing power and energy efficiency are of critical concerns. The proposed medical image scalar involves polynomial based enhanced bilinear interpolation technique for image scaling that preserves the image quality and also make VLSI implementation easier. © 2025 IEEE.

关键词： Diagnosis

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Enhancing Blurred image processing with IoT Integration for Improved Clarity 2

Enhancing Blurred Image Processing with IoT Integration for ...

引用

2nd IEEE International conference on Emerging Research in Computational Science, ICERCS 2024

作者： Tummalapalli, Geetamma Summia Parveen, H. Ramesh, S.M. Monica, P. Santhiya, B. Rajasekaran, Arun Sekar GMR Institute of Technology Department of Electronics and Communication Engineering Rajam India Sri Eshwar College of Engineering Department of Computer Science Engineering Coimbatore India KPR Institute of Engineering and Technology Department of Electronics and Communication Engineering Coimbatore India GITAM Deemed to be University Department of Electronics and Communication Engineering GST Visakhapatnam India Bannari Amman Institute of Technology Department of Information Technology Sathyamangalam India SR University Department of Electronics and Communication Engineering Warangal India

ISBN: (纸本)9798331534950

A blurred image is an image that has undergone a blurring or smoothing effect, resulting in a loss of sharpness and clarity. Blurring is a technique used in image processing to reduce noise, remove unwanted details, or create a visual effect. It involves averaging or blending neighboring pixels to create a smoother appearance. The specific processing techniques and algorithms used will depend on the nature and extent of the blur, the intended outcome, and the available software or programming tools. It's important to experiment with different methods and parameters to achieve the desired result. IoT (Internet of Things) can be used in image processing in several ways to enhance functionality, efficiency, and data processing capabilities enhances image processing by enabling real-time analysis, edge computing capabilities, integration with other IoT devices, and remote monitoring and control. These advancements facilitate applications such as object detection, image recognition, and real-time decision-making, contributing to more efficient and intelligent systems in various domains. Here is a proposed model for blurred image processing with IoT. This proposed model demonstrates the integration of IoT devices, image processing techniques, and cloud-based analytics to address the challenges of blurred image processing. It combines edge processing for real-time analysis and cloud-based processing for more complex algorithms, enabling efficient and intelligent image processing applications in various domains. © 2024 IEEE.

关键词： Edge computing

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Multithreading approach for white blood cell segmentation implementation

Multithreading approach for white blood cell segmentation im...

引用

conference on real-time processing of image, Depth, and Video Information

作者： Garcia-Salgado, Beatriz P. Ponomaryov, Volodymyr, I Diaz-Resendiz, Jose Luis Mora-Martinez, Yeredith G. Almaraz-Damian, Jose A. Reyes-Reyes, Rogelio Sadovnychiy, Sergiy Inst Politecn Nacl ESIME Culhuacan Mexico City DF Mexico Inst Mexicano Petr Mexico City DF Mexico

ISBN: (纸本)9781510673199;9781510673182

Childhood leukaemia demands meticulous blood cell analysis for diagnosis, focusing on morphological irregularities like asymmetry and abnormal cell counts. Traditional manual diagnosis via microscopic blood smear images suffers from limitations: reduced reliability, time intensiveness, and observer variability. Automated methods using Computer-Aided Diagnostic (CAD) systems address these challenges. Integrating real-time image preprocessing and segmentation ensures swift operation, reducing the CAD system's processing time and enhancing its overall effectiveness, enabling timely medical intervention and better patient outcomes. This study aims to simplify the overall algorithmic complexity of other state-of-the-art techniques using preprocessing steps, including bilateral filtering and Contrast-Limited Adaptive Histogram Equalization (CLAHE), alongside the segmentation stage involving morphological operations and the watershed algorithm. Therefore, an edge-based approach is proposed to enhance the segmentation mask as these operations aggregate time complexity. This work also describes a parallel implementation utilizing OpenMP and CUDA of the proposed method, evaluating its performance using Intersection over Union (IoU) and F1-score metrics along with computing time and algorithmic complexity. Furthermore, computing time is compared using two x86-64 and two ARM architectures, each with a different number of available CPU cores, to evaluate the behaviour of the proposed approach in different conditions. The study highlights the benefits of parallel processing in enhancing the efficiency and accuracy of White Blood Cell (WBC) Segmentation. It reports that the proposed approach has an average IoU of 0.9439 and an F1-score of 0.9697 with an image processing rate higher than 60 images per second.

关键词： White Blood Cell Segmentation Computer-Aided Diagnostic Systems Parallel processing Algorithmic Complexity real-time Segmentation

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Road Intersection Analysis: Integrating image processing into Digital Twin Technologies

Road Intersection Analysis: Integrating Image Processing int...

引用

conference on real-time processing of image, Depth, and Video Information

作者： Vdzquez Donaire, Francisco C. Abalo-Garcia, Alejandra Montemayor, Antonio S. Pantrigo, Juan J. Univ Rey Juan Carlos Calle Tulipan S-N Mostoles Spain

ISBN: (纸本)9781510673199;9781510673182

We present a real-time system for vehicle detection and classification in road intersections, incorporating image processing techniques. This system estimates the traffic flow at a specific point, as it is capable of recognizing the trajectories of different vehicles at an intersection, inferring whether they leave or enter the city. It is designed to be integrated into a high-fidelity digital twin, aiding in estimating environmental traffic pollutants. Since Computational Fluid Dynamics (CFD) use estimators like average or aggregate measurements, we use more accurate methods to estimate pollution. The implications of our study are significant for urban planning and traffic management. It allows for immediate decisions and informs long-term infrastructure planning by providing a deep understanding of intersection dynamics. Our research offers a comprehensive perspective on traffic analysis, introducing data-driven traffic management strategies for efficient urban mobility. The code developed for this purpose can be found in https://***/capo- urjc/TrackingSORT

关键词： deep learning digital twins traffic monitoring visual tracking

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Structural-functional model of a parallel-hierarchical optical network as a systematic tool for artificial intelligence methods 20

Structural-functional model of a parallel-hierarchical optic...

引用

conference on Optical Fibers and their Applications

作者： Tymchenko, Leonid Kokriatska, Natalia Tverdomed, Volodymyr Pavlov, Sergii Bondarenko, Zlata Vitiuk, Anna Didenko, Yurii Semenova, Liudmyla Zhuk, Dmytro Sawicki, Daniel Amirgaliyev, Yedilkhan Smailova, Saule State Univ Infrastruct & Technol Kyiv Ukraine Vinnytsia Natl Tech Univ Vinnytsia Ukraine Lublin Univ Technol Lublin Poland Inst Informat & Computat Technol CS MES RK Alma Ata Kazakhstan D Serikbayev East Kazakhstan Tech Univ Ust Kamenogorsk Kazakhstan

ISBN: (纸本)9781510672895;9781510672888

The article discusses the challenges of real-time data processing and analyzes various methods used to solve them, with a focus on image processing. It points out the limitations of existing methods and argues for the need to use more effective and modern technologies, proposing parallel- hierarchical networks as a promising solution. The article provides a detailed description of the structural-functional model of this type of network, which involves cyclically transforming the input data matrix using a "common part" criterion and an array evolution operator until a set of individual elements is formed. The proposed model is expected to improve real-time image recognition and can potentially be applied to other fields by using the "common part" criterion.

关键词： image processing parallel-hierarchical optical networks parallel information encoding criterion of common part real-time data processing

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The real-time 4K image Super- Resolution on CPU with Hybrid of Post-Training Quantization And Quantization-Aware Training 15

The Real-Time 4K Image Super- Resolution on CPU with Hybrid ...

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15th IEEE International conference on Software Engineering and Service Science (ICSESS)

作者： Xie, Yi Liu, Kaixuan Wang, Bin Xu, Kunda Yao, Weifeng Ding, Ke Peng, Bo Intel Corp Shanghai Shanghai Peoples R China

ISBN: (纸本)9798350389166;9798350389173

This real-time 4K image super-resolution (SR) is an intensive task that demands substantial computational resources, typically allocated to GPUs or ASICs. In contrast, most high-quality video transcoding workloads are executed on CPUs. This disparity necessitates the use of different hardware platforms for super-resolution and transcoding, resulting in increased complexity and elevated costs. With the advent of the new AI instructions, AMX, on the 5th generation Xeon platform, a single-socket CPU is now capable of delivering over 200 TOPs of INT8 computational power. Despite this advancement, the current quantization algorithms for SR models, including Quantization-Aware Training (QAT) and Post-Training Quantization (PTQ), fall short of expectations. In this paper, we introduce an innovative hybrid algorithm tailored for the quantization of image super-resolution models, designed to strike an optimal balance between processing speed and image quality.

关键词： FFmpeg OpenVINO super-resolution quantization aware training post training quantization

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A Dual-Approach to Drone image Enhancement: Software-Based processing and FPGA Implementation

A Dual-Approach to Drone Image Enhancement: Software-Based P...

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2024 International conference on Smart Electronics and Communication Systems, ISENSE 2024

作者： Nair, Arun T Varma, Nanditha N Nandakumar, R. National Institute of Electronics and Information Technology Calicut India

ISBN: (纸本)9798331528126

This work offers a thorough method for real-time dehazing of drone-captured images by different filtering techniques with post-processing improvements. Enhancing visibility and picture clarity in hazy situations is the main goal since it is essential for applications like environmental monitoring, navigation, and surveillance. In order to estimate the atmospheric light and transmission map, the suggested methodology makes use of the dark channel. A farrow filter and a guided filter are then applied to improve the transmission. Metrics including the PSNR, SSIM, Execution time, and MSE that are derived from Python-based image processing implementations are used to assess the effectiveness of the dehazing algorithms. The outcomes show notable gains in processing efficiency and image clarity. In order to accelerate the performance, this method was implemented on an FPGA based SoC. Power consumption and throughput of the FPGA - based solution were evaluated, demonstrating its effectiveness and appropriateness for real-time applications. © 2024 IEEE.

关键词： Drones

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