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

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Hybrid code description for developing fast and resource efficient image processing architectures 16

Hybrid code description for developing fast and resource eff...

引用

16th International conference on Embedded Computer systems: Architectures, Modeling and Simulation, SAMOS 2016

作者： Haublein, Konrad Reichenbach, Marc Reiche, Oliver Akif Ozkan, M. Fey, Dietmar Hannig, Frank Teich, Jurgen Computer Architecture Martensstraße 3 Erlangen91058 Germany Hardware-Software-Co-Design Cauerstraße 11 Erlangen91058 Germany

ISBN: (纸本)9781509030767

image processing algorithms applied on programmable embedded systems very often do not meet the given constraints in terms of real time capability. Mapping these algorithms to reconfigurable hardware solves this issue, but demands further specific knowledge in hardware development. The design process can be accelerated by code generation through high-level synthesis, which is very flexible. However, the quality of synthesis depends on many factors like the provided constraints, code description, and algorithmic complexity. Hence, optimizing these parameters may improve the generated results in terms of logic and memory utilization, as well as data throughput and synthesis duration. In this work, we aim to exploit domain-specific knowledge for a hybrid code description in order to benefit from rapid development through high-level synthesis in combination with throughput optimized generic hardware descriptions. By utilizing code generation techniques, the entire design flow gets accelerated. Our synthesis results show a similar resource utilization and achievable throughput to a pure HDL described hardware. © 2016 IEEE.

关键词： Codes (symbols)

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Scale-Aware Alignment of Hierarchical image Segmentation 29

Scale-Aware Alignment of Hierarchical Image Segmentation

引用

2016 IEEE conference on Computer Vision and Pattern Recognition (CVPR)

作者： Chen, Yuhua Dai, Dengxin Pont-Tuset, Jordi Van Gool, Luc Swiss Fed Inst Technol Comp Vis Lab Zurich Switzerland Katholieke Univ Leuven ESAT PSI VISICS Leuven Belgium

ISBN: (纸本)9781467388511

image segmentation is a key component in many computer vision systems, and it is recovering a prominent spot in the literature as methods improve and overcome their limitations. The outputs of most recent algorithms are in the form of a hierarchical segmentation, which provides segmentation at different scales in a single tree-like structure. Commonly, these hierarchical methods start from some low-level features, and are not aware of the scale information of the different regions in them. As such, one might need to work on many different levels of the hierarchy to find the objects in the scene. This work tries to modify the existing hierarchical algorithm by improving their alignment, that is, by trying to modify the depth of the regions in the tree to better couple depth and scale. To do so, we first train a regressor to predict the scale of regions using mid-level features. We then define the anchor slice as the set of regions that better balance between over-segmentation and under-segmentation. The output of our method is an improved hierarchy, re-aligned by the anchor slice. To demonstrate the power of our method, we perform comprehensive experiments, which show that our method, as a post-processing step, can significantly improve the quality of the hierarchical segmentation representations, and ease the usage of hierarchical image segmentation to high-level vision tasks such as object segmentation. We also prove that the improvement generalizes well across different algorithms and datasets, with a low computational cost.

关键词： image segmentation

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Medic: An Artificially Intelligent System to Provide Healthcare Services to Society and Medical Assistance to Doctors

Medic: An Artificially Intelligent System to Provide Healthc...

引用

International conference on Communication and Electronics systems (ICCES)

作者： Jayawant, Shubham Chair of Power Electronics Institute of Power Engineering Dresden Germany

ISBN: (纸本)9781509010660

Since the last decade, number of applications of Artificial Intelligence in daily livelihood has drastically increased. This is primarily because of the inclusion of high-tech gadgets in our day-to-day lives. These gadgets provide high computational capabilities and geographical reach. These two features could be exerted to provide medical services to the society. This paper is based on a project which emphasizes on creating a software infrastructure which would provide healthcare services like diagnosis of diseases, advising medical tests to patients, providing medical prescription to patients by making use of personalized medicine problem solving algorithms etc., and providing medical assistance to doctors. This project, Medic, makes use of natural language processing, fuzzy logic, deep learning and a constantly evolving knowledge base to correctly diagnose diseases. It also provides various services to doctors which would help them while making decisions regarding any patient's medical treatment.

关键词： Artificial Intelligence Natural language processing image recognition Convolution neural networks Deep learning Artificial neural networks

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Predicting learners' multi-question performance based on neural networks 4

Predicting learners' multi-question performance based on neu...

引用

4th International conference on Behavioral, Economic, and Socio-Cultural Computing, BESC 2017

作者： Liao, Pan Sun, Yuan Ye, Shiwei Li, Xin Su, Guiping Sun, Yi School of Computer and Control Engineering University of Chinese Academy of Sciences China Information and Society Research Division National Institute of Informatics Tokyo Japan Big Data Research Institute Hefei China

ISBN: (纸本)9781538623657

As massive open online courses (MOOCs) and online intelligent tutoring systems(ITS) have become increasingly widespread, the number of learners enrolled in online courses has shown explosive growth. However, these learners are likely to have acquired knowledge from diverse educational and vocational backgrounds. Therefore, it is unwise to apply the same criteria and assessment questions to assess all learners' abilities without differentiation. Therefore, the demand for the adaptive arrangement of questions for online learners is ever critical. Deep learning is a new increasingly popular approach for handling extraordinarily complex problems such as image recognition and natural language processing. In this research, we use neural networks to forecast learners' multi-question performance on new test questions and propose a new concept called predictable property for the first time to explain the reasons why neural networks can be applied to predict learners' multi-question performance based on their previous question responses. This approach means that fewer questions need to be answered by learners although more information can be gathered about them through the use of deep-learning-based techniques. Finally, we use both artificial datasets generated by cognitive models and three real-world datasets to validate the algorithm's performance. Experiments show a promising research result when using deep learning to predict learner performance in multi-question tasks and can ultimately provide more accurate adaptive tests for learners. © 2017 IEEE.

关键词： image recognition

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Fast gender recognition in videos using a novel descriptor based on the gradient magnitudes of facial landmarks

Fast gender recognition in videos using a novel descriptor b...

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IEEE conference on Advanced Video and Signal Based Surveillance (AVSS)

作者： George Azzopardi Antonio Greco Alessia Saggese Mario Vento University of Malta University of Salerno

The growing interest in recent years for gender recognition from face images is mainly attributable to the wide range of possible applications that can be used for commercial and marketing purposes. It is desirable that such algorithms process high resolution video frames acquired by using surveillance cameras in real-time. To the best of our knowledge, however, there are no studies which analyze the computational impact of the methods and the difficulties related to the processing of faces extracted from videos captured in the wild. We propose a novel face descriptor based on the gradient magnitudes of facial landmarks, which are points automatically extracted from the face contour, eyes, eyebrows, nose, mouth and chin. We evaluate the effectiveness and efficiency of the proposed approach on two new datasets, which we made available online and that consist of color face images and color video sequences acquired in real scenarios. The proposed approach is more efficient and effective than three commercial libraries.

关键词： Face Videos image color analysis Cameras Real-time systems Face recognition Support vector machines

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Development Prospects of the Visual Data Compression Technologies and Advantages of New Approaches 1

引用

9th KES International conference on Intelligent Interactive Multimedia systems and Services (IIMSS)

作者： Vostrikov, Anton Sergeev, Mikhail St Petersburg State Univ Aerosp Instrumentat Dept Comp Syst & Networks 67 Bolshaya Morskaya St St Petersburg 190000 Russia

ISBN: (数字)9783319393452

ISBN: (纸本)9783319393452;9783319393445

The static image and video information compression algorithms development over the last 15-20 years, as well as standardized and non-standardized formats for data storage and transmission have been analyzed;the main factors affecting the further development of approaches that eliminate the redundancy of transmitted and stored visual information have been studied. The conclusion on the current prospects for the development of image compression technologies has been made. New approaches that use new low-level quasi-orthogonal matrices as transform operators have been defined. The advantages of such approaches opening new fundamentally different opportunities in the field of applied processing of digital visual information have been identified and presented.

关键词： image compression Video compression Protection against unauthorized access M-matrices Audiovisual information coding Metadata

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An integral design strategy combining optical system and image processing to obtain high resolution images 12

An integral design strategy combining optical system and ima...

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conference on Remotely Sensed Data Compression, Communications, and processing XII

作者： Wang, Jiaoyang Wang, Lin Yang, Ying Gong, Rui Shao, Xiaopeng Liang, Chao Xu, Jun Xidian Univ Sch Phys & Optoelect Engn Xian 710071 Shaanxi Peoples R China Ordnance Ind Res Inst China 203 Xian 710065 Shaanxi Peoples R China

ISBN: (纸本)9781510601154

In this paper, an integral design that combines optical system with image processing is introduced to obtain high resolution images, and the performance is evaluated and demonstrated. Traditional imaging methods often separate the two technical procedures of optical system design and imaging processing, resulting in the failures in efficient cooperation between the optical and digital elements. Therefore, an innovative approach is presented to combine the merit function during optical design together with the constraint conditions of image processing algorithms. Specifically, an optical imaging system with low resolution is designed to collect the image signals which are indispensable for imaging processing, while the ultimate goal is to obtain high resolution images from the final system. In order to optimize the global performance, the optimization function of ZEMAX software is utilized and the number of optimization cycles is controlled. Then Wiener filter algorithm is adopted to process the image simulation and mean squared error (MSE) is taken as evaluation criterion. The results show that, although the optical figures of merit for the optical imaging systems is not the best, it can provide image signals that are more suitable for image processing. In conclusion. The integral design of optical system and image processing can search out the overall optimal solution which is missed by the traditional design methods. Especially, when designing some complex optical system, this integral design strategy has obvious advantages to simplify structure and reduce cost, as well as to gain high resolution images simultaneously, which has a promising perspective of industrial application.

关键词： integral design optical figures of merit Wiener filter mean squared error optimization cycles

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No-reference wavelet based retinal image quality assessment 5th

No-reference wavelet based retinal image quality assessment

引用

5th Eccomas Thematic conference on Computational Vision and Medical image processing, Vipimage 2015

作者： Abdel Hamid, L.S. El-Rafei, A. El-Ramly, S. Michelson, G. Hornegger, J. Electronics and Communications Department Misr International University Cairo Egypt Engineering Physics and Mathematics Department Ain Shams University Cairo Egypt Electronics and Communication Engineering Department Ain Shams University Cairo Egypt Department of Ophthalmology Friedrich-Alexander University Erlangen-Nuremberg Germany Pattern Recognition Laboratory Department of Computer Science Friedrich-Alexander University Erlangen-Nuremberg Germany

ISBN: (纸本)9781138029262

Retinal image Quality Assessment (RIQA) is an essential preliminarily step in Automatic Retinal Screening systems (ARSS) to avoid misdiagnosis of retinal disease. In this work, a no-reference wavelet based RIQA algorithm suitable for real-time ARSS is introduced. Retinal images are classified into good and bad quality images using two proposed metrics. These measures are extracted from the wavelet decomposition subbands of the image to reflect sharpness and contrast. Wavelet level and regional analyses are performed to determine the most relevant levels and retinal region to be used in the RIQA. The algorithm is tested on two publicly available datasets with different resolutions. Area under the ROC curve (AUC) of 1 and 0.985 are obtained for the low and high resolution datasets respectively with runtime ranging between 0.1 and 2 seconds depending on image resolution. Comparison with other RIQA algorithms shows superiority of the proposed algorithm in both performance and time. © 2016 Taylor & Francis Group, London.

关键词： Real time systems

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Hybrid object detection system for X-ray radiographs 17

Hybrid object detection system for X-ray radiographs

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conference on Radiation Detectors - systems and Applications XVII

作者： Vita, Joshua A. Wantuch, Andrew C. Jimenez, Edward S. Bray, Iliana E. Sandia Natl Labs POB 5800Mail Stop 0932 Albuquerque NM 87185 USA

ISBN: (数字)9781510603301

ISBN: (纸本)9781510603295;9781510603301

While object detection is a relatively well-developed field with respect to visible light photographs, there are significantly fewer algorithms designed to work with other imaging modalities. X-ray radiographs have many unique characteristics that introduce additional challenges that can cause common image processing and object detection algorithms to begin to fail. Examples of these problematic attributes include the fact that radiographs are only represented in gray scale with similar textures and that transmission overlap occurs when multiple objects are overlaid on top of each other. In this paper we not only analyze the effectiveness of common object detection techniques as applied to our specific database, but also outline how we combined various techniques to improve overall performance. While significant strides have been made towards developing a robust object detection algorithm for use with the given database, it is still a work in progress. Further research will be needed in order to deal with the specific obstacles posed by radiographs and X-ray imaging systems. Success in this project would have disruptive repercussions in fields ranging from medical imaging to manufacturing quality assurance and national security.

关键词： Radiography Databases Detection and tracking algorithms X-rays image segmentation Algorithm development X-ray imaging Sensors Machine learning Photography

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Content-Based image Retrieval Using Deep Search 23rd

Content-Based Image Retrieval Using Deep Search

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23rd International conference on Neural Information processing (ICONIP)

作者： Zhou, Zhengzhong Zhang, Liqing Shanghai Jiao Tong Univ Dept Comp Sci & Engn Key Lab Shanghai Educ Commiss Intelligent Interac Shanghai Peoples R China

ISBN: (纸本)9783319466729;9783319466712

The aim of Content-based image Retrieval (CBIR) is to find a set of images that best match the query based on visual features. Most existing CBIR systems find similar images in low level features, while Text-based image Retrieval (TBIR) systems find images with relevant tags regardless of contents in the images. Generally, people are more interested in images with similarity both in contours and high-level concepts. Therefore, we propose a new strategy called Deep Search to meet this requirement. It mines knowledge from the similar images of original queries, in order to compensate for the missing information in feature extraction process. To evaluate the performance of Deep Search approach, we apply this method to three different CBIR systems (HOF [5], HOG and GIST) in our experiments. The results show that Deep Search greatly improves the performance of original algorithms, and is not restricted to any particular methods.

关键词： CBIR Deep search image semantics

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