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Improved cross-media relevance model for automatic image annotation

ICIC Express Letters, Part B: Applications 2012年第5期3卷 1231-1237页

作者： Song, Haiyu Li, Xiongfei Wang, Pengjie Bao, Cuizhu Liu, Yongkui Xu, Lu Institute of Computer Graphics and Image Processing Dalian Nationalities University No. 18 Liaohe Road Economic and Technological Development Zone-Dalian 116600 China Key Laboratory of Symbol Computation and Knowledge Engineering Ministry of Education Jilin University No. 2699 Qianjin Avenue Changchun 130012 China

Automatic image annotation has been an active research topic in the last decade due to its potentially large impact on image retrieval, object recognition and image understanding. Many approaches have been proposed for image annotation in recent years. The most influential annotation model is relevance model, whose representative algorithm is Cross-Media Relevance Model (CMRM). In this paper, to overcome the shortcomings of the original CMRM, we propose improved CMRM. In the improved CMRM, the annotation word distribution is estimated using binary probability, the significance of blob is discriminately depicted using TF-IDF (term frequency-inverse document frequency) schemes, and the similarity measurement of blob is based on blob and continuousvalued feature vector. The experimental results on the standard Corel5K dataset show that our proposed approach outperforms the original CMRM by about 111% and 73% in terms of F1 and N+ measures respectively. The improved CMRM can get better performance in specific domains such as cultural heritage and special necessities digitization for ethnic minorities. © 2012 ICIC International.

关键词： image retrieval

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M3YOLOv5: Feature enhanced YOLOv5 model for mandibular fracture detection

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computers in Biology and Medicine 2024年 173卷 108291-108291页

作者： Zhou, Tao Wang, Hongwei Du, Yuhu Liu, Fengzhen Guo, Yujie Lu, Huiling School of Computer Science and Engineering North Minzu University Yinchuan750021 China School of Medical Information and Engineering Ningxia Medical University Yinchuan750004 China Key Laboratory of Image and Graphics Intelligent Processing of State Ethnic Affairs Commission North Minzu University Yinchuan750021 China

Background: It is very important to detect mandibular fracture region. However, the size of mandibular fracture region is different due to different anatomical positions, different sites and different degrees of force. It is difficult to locate and recognize fracture region accurately. Methods: To solve these problems, M3YOLOv5 model is proposed in this paper. Three feature enhancement strategies are designed, which improve the ability of model to locate and recognize mandibular fracture region. Firstly, Global-Local Feature Extraction Module (GLFEM) is designed. By effectively combining Convolutional Neural Network (CNN) and Transformer, the problem of insufficient global information extraction ability of CNN is complemented, and the positioning ability of the model to the fracture region is improved. Secondly, in order to improve the interaction ability of context information, Deep-Shallow Feature Interaction Module (DSFIM) is designed. In this module, the spatial information in the shallow feature layer is embedded to the deep feature layer by the spatial attention mechanism, and the semantic information in the deep feature layer is embedded to the shallow feature layer by the channel attention mechanism. The fracture region recognition ability of the model is improved. Finally, Multi-scale Multi receptive-field Feature Mixing Module (MMFMM) is designed. Deep separate convolution chains are used in this modal, which is composed by multiple layers of different scales and different dilation coefficients. This method provides richer receptive field for the model, and the ability to detect fracture region of different scales is improved. Results: The precision rate, mAP value, recall rate and F1 value of M3YOLOv5 model on mandibular fracture CT data set are 97.18%, 96.86%, 94.42% and 95.58% respectively. The experimental results show that there is better performance about M3YOLOv5 model than the mainstream detection models. Conclusion: The M3YOLOv5 model can effectiv

关键词： Fracture

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image Encryption Using 2D Sine-Piecewise Linear Chaotic Map

Image Encryption Using 2D Sine-Piecewise Linear Chaotic Map

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International Conference on Wavelet Analysis and Pattern Recognition (ICWAPR)

作者： Yan-Ru Zhong Hua-Yi Liu Xi-Yan Sun Ru-Shi Lan Xiao-Nan Luo School of Computer Science and Information Security Guilin University of Electronic Technology Guilin China School of Information and Communication Guilin University of Electronic Technology Guilin China Guangxi Colleges and Universities Key Laboratory of Intelligent Processing of Computer Image and Graphics Guilin University of Electronic Technology Guilin China

In this paper, a new image encryption algorithm is proposed by integrating Sine and piecewise linear chaotic maps. In order to realize the effect of encrypted image, the security key and 2D Sine-piecewise linear chaotic map (SPLCM) are used to encrypt the image by using random sequence and random matrix, and then using the replacement operation and the diffusion operation of the original image. The proposed image encryption algorithm is simple and practical, and the simulation results show that this algorithm is able to encrypt different types of digital images into unidentifiable random images. The security analysis also shows that this algorithm has a higher security level.

关键词： Encryption Two dimensional displays Digital images Chaotic communication

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Pagml: Precise Alignment Guided Metric Learning for Sketch-Based 3d Shape Retrieval

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SSRN 2023年

作者： Bai, Shaojin Bai, Jing Xu, Hao Tuo, Jiwen Liu, Min School of Computer Science and Engineering North Minzu University Yinchuan750021 China National Ethnic Affairs Commission Image graphics intelligent processing laboratory Yinchuan750021 China School of Mechanical Engineering Purdue University West Lafayette47907 United States

Sketch-based 3D shape retrieval has always been a hot research topic in the computer vision community. The main challenge is to alleviate the cross-modality discrepancies such that the retrieval accuracy can be improved. In this paper, we propose a novel Precise Alignment Guided Metric Learning (PAGML) method based on master-auxiliary cross-modality retrieval framework. An auxiliary learning network is developed to indirectly guide the master learning model to extract features of rich semantic information, so as to achieve a semantic alignment between the cross-modality data. Furthermore, considering that the unbalanced data distributions led to the poor uniformity in the common embedding space, a loss function dedicated for the imbalanced cross-modality data is designed to achieve a rigid alignment between sketches and 3D shapes of the same category by pulling their rich semantic representations to the rigid center of the category. As a result, a more precise alignment between the cross-modality embedding features of same category is approached gradually, which further alleviates the cross-modality discrepancies and improves the cross-modality retrieval accuracies. Extensive experiments on two public benchmark datasets demonstrate that the proposed PAGML surpasses the state-of-the-art methods in retrieval accuracy and has excellent generalization abilities to unseen classes. © 2023, The Authors. All rights reserved.

关键词： Embeddings

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Portable lensless wide-field microscopy imaging platform based on digital inline holography and multi-frame pixel super-resolution

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Light(Science & Applications) 2015年第1期4卷 152-162页

作者： Antonio C Sobieranski Fatih Inci H Cumhur Tekin Mehmet Yuksekkaya Eros Comunello Daniel Cobra Aldo von Wangenheim Utkan Demirci Demirci Bio-Acoustic-MEMS in Medicine(BAMM)Laboratory Division of Biomedical EngineeringDivision of Renal MedicineDepartment of MedicineBrigham and Women’s HospitalHarvard Medical SchoolBostonMAUSA Demirci Bio-Acoustic-MEMS in Medicine(BAMM)Laboratory Division of Infectious DiseasesBrigham and Women’s HospitalHarvard Medical SchoolBostonMAUSA INCoD–National Brazilian Institute for Digital Convergence/LAPIX Image Processing and Computer Graphics LabFederal University of Santa CatarinaBrazil Demirci Bio-Acoustic-MEMS in Medicine(BAMM)Laboratory Stanford University School of MedicineCanary Center at Stanford for Cancer Early DetectionPalo AltoCAUSA Present Address:Department of Biomedical Engineering Faculty of Engineering Bas¸kent UniversityAnkaraTurkey VisionLab Master in Applied ComputingUniversity of Itajaı´ValleyBrazil CERTI Foundation FlorianopolisBrazil

In this paper,an irregular displacement-based lensless wide-field microscopy imaging platform is presented by combining digital in-line holography and computational pixel super-resolution using multi-frame *** samples are illuminated by a nearly coherent illumination system,where the hologram shadows are projected into a complementary metal-oxide semiconductor-based imaging *** increase the resolution,a multi-frame pixel resolution approach is employed to produce a single holographic image from multiple frame observations of the scene,with small planar *** are resolved by a hybrid approach:(i)alignment of the LR images by a fast feature-based registration method,and(ii)fine adjustment of the sub-pixel information using a continuous optimization approach designed to find the global optimum *** method for phase-retrieval is applied to decode the signal and reconstruct the morphological details of the analyzed *** presented approach was evaluated with various biological samples including sperm and platelets,whose dimensions are in the order of a few *** obtained results demonstrate a spatial resolution of 1.55 μm on a field-of-view of<30 mm^(2).

关键词： digital in-line holography image registration lensless imaging point-of-care platform pixel super-resolution

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Research Progress of Encoder-Decoder Network in image Fusion

SSRN

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SSRN 2023年

作者： Zhou, Tao Zhang, Xiangxiang Cheng, Qianru Li, Qi Lu, Huiling School of Computer Science and Engineering North Minzu University Yinchuan750021 China Key Laboratory of Image and Graphics Intelligent Processing of State Ethnic Affairs Commission North Minzu University Yinchuan750021 China School of Science Ningxia Medical University Yinchuan750004 China

A B S T R A C Timage fusion is a research hotspot in the field of computer vision, which obtains complementary information from the different modal images and then presents it in a comprehensive, highly information-cohesive fused image. Encoder-decoder networks are an important technical method in the field of image fusion. This paper reviewed the research status and development of the Encoder-decoder networks in the field of image fusion from the following aspects: Firstly, the18 image fusion-related datasets and the 22 open-source codes of deep learning-based image fusion are summarized. Secondly, the model structure of encoder-decoder networks and the basic principles for image fusion based on the encoder-decoder network are described. Thirdly, encoder-decoder networks fusion models are summarized into 4 aspects: Convolutional Auto-encoder network(CAE Net), Sparse Auto-encoder network(SAE Net), U-shape Encoder-decoder network(U-net) and Variational Auto-encoder network(VAE Net),in U-net, there are 5 types: U-net incorporating residual connection mechanism (Res U-net), U-net incorporating dense connection mechanism (Dens U-net), U-net incorporating multiscale connection mechanism (MS U-net), U-net incorporating attention mechanism (Att U-net) and U-shaped Encoder-decoder networks(U-net) combined with Generative Adversarial Network(GAN U-net). Fourthly, the existing image fusion evaluation metrics are summarized from both subjective and objective aspects. Fifthly, the application of Encoder-decoder network in 5 kinds of image fusion, such as multi-exposure image fusion, multi-focus image fusion, infrared and visible image fusion, medical image fusion and remote sensing image fusion are summarized. Finally, there is a discussion of the main challenges faced by encoder-decoder networks in the image fusion domain and an outlook on future directions. This paper systematically analyzed the application of encoder-decoder networks in the image fusion areas, which has posi

关键词： Deep learning

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Teeth Yolact: A Model Fusing Deep-Shallow, Local-Global And Edge Features

SSRN

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SSRN 2024年

作者： Zhou, Tao Wang, Yaxing Chai, Wenwen Pan, Yunfeng Zhang, Zhe Lu, Huiling Xia, Yong School of Computer Science and Engineering North Minzu University Yinchuan750021 China School of Medical Information and Engineering Ningxia Medical University Yin Chuan750004 China Key Laboratory of Image and Graphics Intelligent Processing State Ethnic Affairs Commission North Minzu University Yinchuan750021 China School of Computer Northwestern Polytechnical University Xi’an710072 China

Background and ObjectiveThe instance segmentation of impacted tooth in the oral panoramic X-ray images is research hot. However, impacted tooth in panoramic X-Ray images lead to teeth deformities, low contrast between the tooth and periodontal tissue. In this paper, a Teeth YOLACT instance segmentation model is *** main contributions of this paper are as follows: Firstly, a Multi-scale Res-Transformer Module (MRTM) is designed, in the module, the depth-wise separable convolution with different perceptive fields are used to improve the model sensitivity to the lesion size, the Vision Transformer are used to improve the model perception ability about global features. Secondly, the Context Interaction-awareness Module (CIaM) is designed to fuse deep and shallow features. The shallow spatial features are guided by the deep semantic features. Then the shallow spatial features are embedded into the deep semantic features, and the cross-weighted attention mechanism is used to efficiently aggregate the deep and shallow features, richer context information are obtained. Thirdly, the Edge-preserving perception Module(E2PM) is designed to enhance the teeth edge features. The first order differential operator is used to get the tooth edge weight, perception ability of tooth edge features is improved. The shallow spatial feature is fused by linear mapping, weight concatenation and matrix multiplication operations to preserve the tooth edge information. Finally, comparison experiments and ablation experiments are conducted on the oral panoramic X-ray image *** results show that the APdet, APseg, ARdet, ARseg, mAPdet and mAPseg indicators of the proposed model are 89.9%, 91.9%, 77.4%, 77.6%, 72.8% and 73.5%, *** are some positive significances about the dental computer-aided diagnosis based on panoramic oral X-ray images. © 2024, The Authors. All rights reserved.

关键词： computer aided diagnosis

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Suspicious face detection based on key frame recognition under surveillance video

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2016年 9712 LNCS卷 645-652页

作者： Zheng, Xiaohui Ning, Yi Chen, Xianjun Zhan, Yongsong Guangxi Colleges and Universities Key Laboratory of Intelligent Processing of Computer Image and Graphics Guilin University of Electronic Technology GuilinGuangxi541004 China Guangxi Experiment Center of Information Science Guilin University of Electronic Technology GuilinGuangxi541004 China Guangxi Colleges and Universities Key Laboratory of Cloud Computing and Complex Systems Guilin University of Electronic Technology GuilinGuangxi541004 China Guangxi Key Laboratory of Trusted Software Guilin University of Electronic Technology GuilinGuangxi541004 China

ISBN: (纸本)9783319409993

Surveillance video is characterized by large amount of data and redundancy, which makes the suspicious face detection to be a problem. To solve the problem above we proposed suspicious face detection based on key frame. Surveillance video has the type of fixed background, so this paper used the frame difference method with low computational complexity and small computation to extract the key frame. We proposed a new method combined DPM with skin color detection to detect the suspicious face in the key frames. To solve the speed bottleneck of the traditional DPM, we proposed to use the fast HOG LUT feature extraction and the near optimal cost sensitive decision making improving the traditional method. Meanwhile we used YCrCb + otsu skin color segmentation. Since the otsu is easily affected by the illumination, we proposed an improved skin color detection. Experiment results show that the proposed algorithms are robust and accurate for real-time. © Springer International Publishing Switzerland 2016.

关键词： Face recognition

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Testing Cross-Platform Streaming of Video Games over Wired and Wireless LANs

Testing Cross-Platform Streaming of Video Games over Wired a...

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International Conference on Advanced Information Networking and Applications Workshops (AINAW)

作者： Audrius Jurgelionis Francesco Bellotti Alessandro De Gloria Jukka-Pekka Laulajainen Philipp Fechteler Peter Eisert Haggai David Department of Biophysical and Electronic Engineering University of Genoa Genoa Italy Universita degli Studi di Genova Genova Liguria IT Converging Networks Laboratory VTT Technical Research Center of Finland Oulu Finland Computer Vision & Graphics Fraunhofer-Institute for Telecommunications Berlin Germany Computer Vision & Graphics Image Processing Department Heinrich-Hertz-Institute Fraunhofer Institute of Telecommunications Berlin Germany Converging Networks Laboratory VTT Technical Research Centre of Finland Oulu Finland R&D Department Exent Technologies Ltd. Petach Tikva Israel

In this paper we present a new cross-platform approach for video game delivery in wired and wireless local networks. The developed 3D streaming and video streaming approaches enable users to access video games on set top boxes and handheld devices that natively are not capable to run PC games. During the development of the distributed gaming system we have faced a number of challenges and problems posed by the hardware and network limitations. In order to solve these problems we have developed a multilevel testing methodology which is based on user assessment and technical measures for the system under development. In this paper we focus on the technical measures and instrumentation that we use for the system's performance measurement and testing. The benefits of our testing methodology are demonstrated through examples from the development and testing work.

关键词： Streaming media Games Wireless LAN System testing computer graphics Hardware Cloud computing Delay image coding computer architecture

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Performance of the H.263 Video Compression Standard

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Journal of VLSI Signal processing Systems for Signal, image, and Video Technology 1997年第2-3期17卷 101-111页

作者： Girod, Bernd Steinbach, Eckehard Färber, Nikolaus Telecommunications Institute University of Erlangen-Nuremberg 91058 Erlangen Cauerstrasse 7 Germany Georgia Institute of Technology United States University of Hannover Germany Inst. F. Theor. N. University of Hannover Germany Massachussetts Inst. of Technology Cambridge MA United States Research Laboratory of Electronics United States Department of Media Technology Media Laboratory Germany Department of Computer Graphics Germany Academy of Media Arts Cologne Germany Computer Science Section Cologne University Germany Digital Signal Processing Group Georgia Institute of Technology Atlanta GA United States Dept. of Elec. Eng./Telecom. University of Erlangen-Nuremberg Germany Telecommunications Institute Germany Vivo Software Inc. Waltham MA United States University of Karlsruhe Germany University of Essex United Kingdom ESIEE Paris France Image Communication Group Telecommunications Institute University of Erlangen-Nuremberg Germany University of Munich Germany Telecommunications Institute University of Erlangen-Nuremberg Germany Image Communication Group

The draft international standard ITU-T H.263 is closely related to the well known and widely used ITU-T Recommendation H.261. However, H.263 does provide the same subjective image quality at less than half the bit-rate. In this paper we investigate to what extend single enhancements of H.263 contribute to this performance gain, and consider the trade-off quality vs. complexity. Based on typical test sequences, H.263 with its various modes is compared to H.261 on the basis of rate distortion curves at bit-rates up to 128 kbps. At 64 kbps, the performance gain of H.263 in its default mode compared to H.261 is approximately 2 dB. This improvement is achieved with only little increase of complexity, and is mainly due to more accurate motion compensation with half-pel accuracy. Considering the trade-off quality vs. complexity, the combination of the optional coding-modes "Advanced prediction mode" and "PB-frames mode" is a good compromise, resulting in an additional performance gain of 1.5 dB PSNR at 64 kbps. The "Syntax-based arithmetic coding mode" on the other hand, offers only a very small performance gain (0.1 dB at 64 kbps) for its increased computational complexity. Results from profiling an H.263 software codec are presented in order to support complexity considerations of the optional coding-modes.

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