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检索条件"任意字段=Conference on Image Processing - Algorithms and Systems XI"

共 16349 条记录，以下是4901-4910 订阅

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Registration and Fusion Techniques for Medical images: Demonstration and Evaluation

引用

3rd International Joint conference on Biomedical Engineering systems and Technologies

作者： Faliagka, Evanthia Matsopoulos, George Tsakalidis, Athanasios Tsaknakis, John Tzimas, Giannis Univ Patras Comp Engn & Informat Dept Patras Greece Natl Tech Univ Athens Sch Elect & Comp Engn Athens Greece Natl Tech Univ Messolongh Dept Appl Informat Adm & Econ Mesolongion Greece

In this work, we present an integrated system for the registration and fusion of medical images, named >. It is often necessary to align medical images to illustrate the changes between the data retrieved at differ... 详细信息

ISBN: (纸本)9783642184710

In this work, we present an integrated system for the registration and fusion of medical images, named << dIaGnosis >>. It is often necessary to align medical images to illustrate the changes between the data retrieved at different times so as to assess the progress of a disease, or to assess the effectiveness of a treatment. The proposed system supports the storage, retrieval, distribution and presentation of medical images from different modalities, such as CT and MRI, in DICOM format. It also supports multiple examinations per patient and uses parallel processing threads to perform the processing of the acquired three-dimensional (3D) images in almost real time. In this paper, the architecture and the working environment of the implemented system are presented in detail, along with a pilot scenario that demonstrates the system in use. Additionally, the registration and fusion algorithms implemented are presented and evaluated, along with the image processing techniques used for the enhancement of medical images. The contribution of the proposed work is multilayered. It provides automatic matching methods based on both segmented surfaces and on different levels of gray, and it improves the alignment process when there is a relative movement and / or distortion of images in the data collected from different imaging systems.

关键词： Medical systems image processing Registration Fusion

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RailSet: A Unique Dataset for Railway Anomaly Detection 5

RailSet: A Unique Dataset for Railway Anomaly Detection

引用

5th IEEE International conference on image processing Applications and systems (IPAS)

作者： Zouaoui, Arij Mahtani, Ankur Hadded, Mohamed Amine Ambellouis, Sebastien Boonaert, Jacques Wannous, Hazem FCS Railenium Famars France Gustave Eiffel Univ Lille France Univ Lille Ctr Digital Syst IMT Nord Europe Inst Mines Tel ecom Lille France

ISBN: (纸本)9781665462198

Understanding the driving environment is one of the key factors in achieving an autonomous vehicle. In particular, the detection of anomalies in the traffic lane is a high priority scenario, as it directly involves vehicle's safety. Recent state of the art image processing techniques for anomaly detection are all based on deep learning of neural networks. These algorithms require a considerable amount of annotated data for training and test purposes. While many datasets exist in the field of autonomous road vehicles, such datasets are extremely rare in the railway domain. In this work, we present a new innovative dataset relevant for railway anomaly detection called RailSet. It consists of 6600 high-quality manually annotated images containing normal situations and 1100 images of railway defects such as hole anomaly and rails discontinuity. Due to the lack of anomaly samples in public images and difficulties to create anomalies in the railway environment, we generate artificially images of abnormal scenes, using a deep learning algorithm named StyleMapGAN. This dataset is created as a contribution to the development of autonomous trains able to perceive tracks damage in front of the train. The dataset is available at this link.

关键词： image generation Anomaly dataset Railway tracks anomaly Autonomous train Generative and Adversarial Neural Networks

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An Application of Backprojection for Video SAR image Formation Exploiting a Subaperture Circular Shift Register

An Application of Backprojection for Video SAR Image Formati...

引用

conference on algorithms for Synthetic Aperture Radar imagery XX

作者： Miller, J. Bishop, E. Doerry, A. Gen Atom Aeronau Syst Inc San Diego CA 92127 USA

ISBN: (纸本)9780819495372

This paper details a Video SAR (Synthetic Aperture Radar) mode that provides a persistent view of a scene centered at the Motion Compensation Point (MCP). The radar platform follows a circular flight path. An objective is to form a sequence of SAR images while observing dynamic scene changes at a selectable video frame rate. A formulation of backprojection meets this objective. Modified backprojection equations take into account changes in the grazing angle or squint angle that result from non-ideal flight paths. The algorithm forms a new video frame relying upon much of the signal processing performed in prior frames. The method described applies an appropriate azimuth window to each video frame for window sidelobe rejection. A Cardinal Direction Up (CDU) coordinate frame forms images with the top of the image oriented along a given cardinal direction for all video frames. Using this coordinate frame helps characterize a moving target's target response. Generation of synthetic targets with linear motion including both constant velocity and constant acceleration is described. The synthetic target video imagery demonstrates dynamic SAR imagery with expected moving target responses. The paper presents 2011 flight data collected by General Atomics Aeronautical systems, Inc. (GA-ASI) implementing the video SAR mode. The flight data demonstrates good video quality showing moving vehicles. The flight imagery demonstrates the real-time capability of the video SAR mode. The video SAR mode uses a circular shift register of subapertures. The radar employs a Graphics processing Unit (GPU) in order to implement this algorithm.

关键词： Video Synthetic aperture radar Video acceleration Video surveillance Radar Microchannel plates Neptunium Detection and tracking algorithms image resolution image acquisition

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Siamese-Driven Optimization for Low-Resolution image Latent Embedding in image Captioning 27

Siamese-Driven Optimization for Low-Resolution Image Latent ...

引用

27th IEEE Signal processing: algorithms, Architectures, Arrangements, and Applications, SPA 2024

作者： Tan, Jing Jie Mokraoui, Anissa Kwan, Ban-Hoe Ng, Danny Wee-Kiat Hum, Yan-Chai Universiti Tunku Abdul Rahman Lee Kong Chian Faculty of Engineering and Science Department of Mechatronics and Biomedical Engineering Malaysia Université Sorbonne Paris Nord Laboratoire de traitement et transport de l'information France

ISBN: (纸本)9788362065486

image captioning is essential in many fields including assisting visually impaired individuals, improving content management systems, and enhancing human-computer interaction. However, a recent challenge in this domain is dealing with low-resolution image (LRI). While performance can be improved by using larger models like transformers for encoding, these models are typically heavyweight, demanding significant computational resources and memory, leading to challenges in retraining. To address this, the proposed SOLI (Siamese-Driven Optimization for Low-Resolution image Latent Embedding in image Captioning) approach presents a solution specifically designed for lightweight, low-resolution images captioning. It employs a Siamese network architecture to optimize latent embeddings, enhancing the efficiency and accuracy of the image-to-text translation process. By focusing on a dual-pathway neural network structure, SOLI minimizes computational overhead without sacrificing performance, making it an ideal choice for training on resource-constrained scenarios. © 2024 Division of Signal processing and Electronic systems, Poznan University of Technology (DSPES PUT).

关键词： Signal encoding

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IMPROVING CROSS-DOMAIN FEW-SHOT CLASSIFICATION WITH MULTILAYER PERCEPTRON 49

IMPROVING CROSS-DOMAIN FEW-SHOT CLASSIFICATION WITH MULTILAY...

引用

49th IEEE International conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： Bai, Shuanghao Zhou, Wanqi Luan, Zhirong Wang, Donglin Chen, Badong Xi An Jiao Tong Univ Inst Artificial Intelligence & Robot Xian Peoples R China Xian Univ Technol Sch Elect Engn Xian Peoples R China Westlake Univ Inst Adv Technol Westlake Inst Adv Study Hangzhou Peoples R China

ISBN: (纸本)9798350344868;9798350344851

Cross-domain few-shot classification (CDFSC) is a challenging and tough task due to the significant distribution discrepancies across different domains. To address this challenge, many approaches aim to learn transferable representations. Multilayer perceptron (MLP) has shown its capability to learn transferable representations in various downstream tasks, such as unsupervised image classification and supervised concept generalization. However, its potential in the fewshot settings has yet to be comprehensively explored. In this study, we investigate the potential of MLP to assist in addressing the challenges of CDFSC. Specifically, we introduce three distinct frameworks incorporating MLP in accordance with three types of few-shot classification methods to verify the effectiveness of MLP. We reveal that MLP can significantly enhance discriminative capabilities and alleviate distribution shifts, which can be supported by our expensive experiments involving 10 baseline models and 12 benchmark datasets. Furthermore, our method even compares favorably against other state-of-the-art CDFSC algorithms.

关键词： Multilayer Perceptron cross-domain few-shot classification distribution shift

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Tools for Dynamic Network Structures: GRAPE Grammars

Tools for Dynamic Network Structures: GRAPE Grammars

引用

1992 International Joint conference on Neural Networks, IJCNN 1992

作者： Freund, Rudolf Haberstroht, Brigitte Bischof, Horst Technical University of Vienna Karlsplatz 13 Vienna1040 Austria Institute for Computer Languages Technical University of Vienna Austria Institute for Information Systems Technical University of Vienna Austria Institute for Pattern Recognition and Image Processing Technical University of Vienna Austria

ISBN: (纸本)0780305590

Dynamic neural networks are able to alter the topology of the underlying graph in order to provide better performance. A lot of interesting algorithms for topology learning have been published, but no formal description method is available. We propose a unique theoretical framework which is based on "attributed elementary programmed graph grammars"(GRAPE grammars) and which turns out to be equally well suited for describing network dynamics, weight learning algorithms, and topology learning algorithms. We show how GRAPE grammars can be used to model neural networks. Special emphasis is devoted to topology learning. © 1992 IEEE.

关键词： Learning algorithms

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A CAD System for Brain Haemorrhage Detection in Head CT Scans 18

A CAD System for Brain Haemorrhage Detection in Head CT Scan...

引用

18th IEEE International conference on Smart Technologies (IEEE EUROCON)

作者： Napier, John Debono, Carl James Bezzina, Paul Zarb, Francis Univ Malta Dept Commun & Comp Engn MSD-2080 Msida Malta Univ Malta Dept Radiog MSD-2080 Msida Malta

ISBN: (纸本)9781538693018

Medical imaging is an important medical diagnostic tool that provides visual information of the interior of the human body. In recent years computer-aided detection/diagnosis (CAD) systems became a key component of routine clinical practice in several medical areas, such as mammography and colonoscopy. However, research on brain CAD systems is still limited compared to other areas. This paper presents a solution that uses image processing techniques on brain computed tomography (CT) scans to create a CAD system that detects fresh bleeds. The system also features a basic classification method that distinguishes between an intra-axial and an extra-axial haemorrhage with the only limitation being subarachnoid haemorrhage (SAH), which is not always properly classified due to its complex structure. The techniques implemented include noise reduction methods, morphological operations and segmentation algorithms. The developed CAD system was tested on 36 brain CT sets obtained from the general hospital in Malta. Results show that the system achieves a sensitivity of 94.4 %, a specificity of 94.4%, a precision of 91.259% and a classification accuracy of 88.89%.

关键词： Computer-aided diagnosis computed tomography image processing medical imaging

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Design and development of automated 3D visual tracking system

Design and development of automated 3D visual tracking syste...

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8th International conference on Automation Technology

作者： Mir-Nasiri, N Hamzaid, NAB Hameed, ABBS Int Islam Univ Dept Mechatron Engn Jalan Gombak 53100 KL Madagascar

Camera-based systems are frequently used to track moving objects which are in the field of their view. This paper describes design and development of a camera-based visual system that can constantly track a moving object without the necessity of calibrating the camera in real world coordinates. This reduces the complexity of the system and processing time due to unnecessary conversions and calibrations. The system consists of a two-motor pan-tilt carnera driving mechanism, PCI image acquisition board, and PWM-based DC-motor driver board. It uses image processing techniques to identify and locate the object in the 3D scene and motion control algorithms to direct the camera towards the object. Thus the objective of the project is to develop a vision system and control algorithms which can be locked on a moving object within the field of its view. The developed software and related interface hardware monitor and control the motors in such a way that the moving object should always be located right at the center of the camera image plane. The system, in general, simulates the 3D motion of the human eye which always tends to focus on a moving object within the range of its view. It actually imitates the tracking ability of human eye.

关键词： image processing object recognition motion control

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image processing using template model and wavelet domain hidden Markov model

Image processing using template model and wavelet domain hid...

引用

International conference on Machine Learning and Cybernetics

作者： Liao, ZW Lam, CM Tang, YY Hong Kong Baptist Univ Dept Comp Sci Kowloon Hong Kong Peoples R China

ISBN: (纸本)0780384032

Wavelet domain Hidden Markov Models (HMMs) have been proven to be useful tools for statistical signal and image processing. However, most of the improvements of wavelet domain HMMs only focus on how to impose an additional dependency structure on the original wavelet domain HMMs to capture the additional dependencies among wavelet coefficients. Besides this, existing methods do not fully consider the effects of noise in high frequency subbands of wavelet transforms, some simple algorithms of wavelet domain HMMs, such as dividing the subband of wavelet coefficients into blocks, cannot be carried on smoothly in noisy image. In this paper, we give a more general framework to simplify wavelet domain HMM using templates. The new model enables us to concisely share the statistics in real-world noisy image using a more reasonable way and enables us to get a simple, local and reliable model using templates. Templates are constructed in the subband of scaling coefficients in order to reduce the effects of image noises and provide powerful yet tractable probabilistic image, models. Before we process images using wavelet domain HMMS, the estimation of parameters for the HMMs must be obtained by the EM training algorithm that shares statistics according to the templates. Finally, to demonstrate the utility of new models, we give an example for image denoising using templates and wavelet-domain HMMs.

关键词： wavelet wavelet domain HMM contextual HAM block HMM template image denoising EM algorithm mixture Gaussian model (MGM)

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Archiving image sequences considering associated geographical and nongeographical attributes

Archiving image sequences considering associated geographica...

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conference on Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense xi

作者： Bruestle, Stefan Heinze, Norbert Fraunhofer IOSB D-76131 Karlsruhe Germany

ISBN: (纸本)9780819490377

image sequences (e.g. video) gathered by a sensor mounted on an airborne platform (e.g. UAV) are used today to address many different tasks in various fields of application. Sequences are usually taken to gather information of an area for planning and assessing purposes, to witness any changes and to monitor activities within that area. image sequences are usually stored as they are taken. In order to perform the above tasks in a post processing step properly, it is necessary to find relevant sequences or subsequences in the huge amount of stored data efficiently. Therefore it is mandatory to store the sequences in a way to enable retrieving any relevant frame or subsequence with respect to a geographical attribute such as e.g. the position of the footprint or a nongeographical attribute such as the date and time gathered or the spectral band of gathered sequence. We have developed a method to store each frame of an image sequence into a spatial relational database in a way that addresses this issue. We further have developed an interface to that database that allows us to retrieve frames and subsequences both employing task specific clients and existing exploitation software systems such as Fraunhofer IOSB's ABUL exploitation station.

关键词： Video exploitation Change Detection IED Detection UAV Mosaic Georeference Video Archive Geodatabase

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