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Design of the breast carcinoma cell bank system

Design of the breast carcinoma cell bank system

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International conference on e-health Networking, Applications and Services (HealthCom)

作者： Heung-Kook Choi Hae-Gil Hwang Min-Kyung Kim Tae-Yeun Kim School of Computer Engineering Inje University South Korea Graduate School of Medical Image Science Inje University South Korea

ISBN: (纸本)0780384539

We describe a cell bank construction which was designed by a content-based image retrieval system using SQL database and XML for breast carcinoma images. However, the conventional pathological images for storage, management and data sharing have been done by a manual handling. We attempted to find a solution for the occurred processing problems by constructing a computerized standard system and a large dataset for the breast carcinoma images. It is possible that the system could classify the images according to the categorized cancer, text retrieval- and content-based retrieval system color- and texture features were applied. The software was designed and developed by using visual Basic and the database constructed by using SQL the extract the texture features from the images. That was then stored in XML for MPEG-7 based retrieval standard system.

关键词： Breast image retrieval Content based retrieval image databases XML image storage Information retrieval Pathology Cancer Software design

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3D image Reconstruction with Single-Slice CT using Improved Marching Cube Algorithm

3D Image Reconstruction with Single-Slice CT using Improved ...

引用

Biomedical Instrumentation and Technology conference (IBITeC), International

作者： Ignatius Luddy Indra Purnama Alva Edy Tontowi Herianto Herianto Department of Mechanical & Industrial Engineering Gadjah Mada University Yogyakarta Indonesia

ISBN: (数字)9781728133393

ISBN: (纸本)9781728133409

Single-slice CT is still widely used in many hospitals because it prolongs the life cycle of the CT device components, especially that of x-ray. Using CT 3D image, it can be very helpful for a doctor in diagnosing medical information. In the development of 3D image reconstruction and computer technology, it is possible for the doctor to communicate with the patient through gadget media. This paper presents the determination of the threshold in single-slice Computerized Tomography (CT) for interactive 3D image reconstruction without user interface. The 3D image reconstruction method is the improved marching cube algorithm. The medical image object that consists of skull bone and sternum-pelvis in Digital Imaging and communications in Medicine (DICOM) format is taken from single-slice CT. The resulting threshold for bone 3D image object is 200, except for the 3D image with quantity slice less than 10 can not be reconstructed. The difference in the surface volume and surface area between the 3D image reconstruction output from InVesalius software and project, for skull bone and sternum-pelvis is less than 0.5%. The justification of the visual shape match from three radiology doctors for skull bone and sternum-pelvis is approximately 99% match. processing time to reconstruct the 3D image is around five minutes.

关键词： Three-dimensional displays image reconstruction Computed tomography Bones Surface reconstruction Software Biomedical imaging

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Single image Dehazing Using CycleGAN Based on Feature Fusion

Single Image Dehazing Using CycleGAN Based on Feature Fusion

引用

Chinese Control and Decision conference, CCDC

作者： Xiaofei Jin Dengyin Zhang Songhao Lu Dingxu Guo Wenye Ni Xu Li School of Communications and Information Engineering Nanjing University of Posts and Telecommunications Nanjing China School of Internet of Things Nanjing University of Posts and Telecommunications Nanjing China

Due to the difficulty of obtaining paired data sets from the real world to train the network, most of the current dehazing networks are trained by synthetic hazy data sets, which will have drawbacks such as poor generalization ability to natural haze scenes and loss of depth details. This paper proposes an image dehazing method using CycleGAN based on improved feature fusion to solve the problem. The method is designed with an encoder-decoder structure in the generator network, enabling more feature information to be extracted at multiple scales. In order to restore the detailed information of the image, this paper introduces the residual dense block instead of the convolution module to extract and fuse the feature information under different receptive fields in each stage of the network. Aiming at the complexity of the fog distribution in the actual scene, this paper introduces an improved channel and spatial attention mechanism in the skip connection of the network to accomplish non-uniform processing of haze areas with different concentrations. At the same time, to improve the quality of the generated image, this paper introduces perceptual loss to enhance the detailed information of the output features, making the generated image more realistic. The experimental findings suggest that the proposed method can achieve better subjective visual effects and image details, and the outcomes of objective indicators are also improved.

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Tomographical scene reconstruction in the active safety car project

Tomographical scene reconstruction in the active safety car ...

引用

International conference on Intelligent Transportation

作者： Joerg Velten Sam Schauland Alexandros Gavriilidis Tim Schwerdtfeger Fritz Boschen Anton Kummert Chair of Communication Theory Faculty of Electrical Information and Media Engineering Bergische Universitat Wuppertal Wuppertal Germany RIEDEL Communications GmbH & Co. KG Wuppertal Germany

Tomographical reconstruction algorithms can be applied to camera based measurements and thus reconstruct the scenery without knowledge about included objects. The latter is interesting in the domain of driver assistance systems that have to monitor the driveway independently from a priori knowledge about possibly appearing objects. The paper presents tomographical background information, the transfer from radiographing to visual light rays and its negative impacts, and some first result obtained by applying the presented algorithm to images of a from view camera.

关键词： image reconstruction Cameras Tomography Signal processing algorithms Vehicles visualization Biomedical imaging

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Practical evaluation of a radial soft hash algorithm

Practical evaluation of a radial soft hash algorithm

引用

International conference on Information Technology: Coding and Computing (ITCC)

作者： F.-X. Standaert E. Lefebvre G. Rouvroy B. Macq J.-J. Quisquater J.-D. Legat Crypto Group Univ. Catholique de Louvain Belgium Laboratoire de Télécommunications et Télédétection Université Catholique de Louvain Belgium Laboratoire de Microélectronique Université Catholique de Louvain Belgium

This paper presents a practical evaluation of a radial soft hash algorithm, an image hashing technique used for image and visual content authentication. First we evaluate its collision resistance and susceptibility to geometrical deformations and image processing attacks. Second we investigate its actual efficiency on different platforms. Although software implementations allow managing sizes and throughput for most applications, they suffer from some troubles for real time applications such as video and for images in high definition. For these more constrained contexts, we propose hardware implementations. In practice, throughput up to 2/sup 18/ (resp. 2/sup 26/) pixels/sec are managed in a single SW (resp. HW) implementation.

关键词： Cryptography Robustness Authentication Throughput Application software Content management Watermarking Digital signatures image coding Videoconference

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A context-based privacy preserving framework for wearable visual lifeloggers

A context-based privacy preserving framework for wearable vi...

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IEEE Annual conference on Pervasive Computing and communications Workshops (PerCom)

作者： Eisa Zarepour Mohammadreza Hosseini Salil S. Kanhere Arcot Sowmya School of Computer Science and Engineering University of New South Wales Sydney Australia AICT Innovation Center Sharif University of Technology Tehran Iran

The ability of wearable cameras to continuously capture the first person viewpoint with minimal user interaction, has made them very attractive in many application domains. Wearable technology today is available and useful but not widely used and accepted due to various challenges mainly privacy concerns. In this paper, we introduce a novel efficient privacy-aware framework for wearable cameras that can protect all sensitive subjects such as people, objects (e.g, display screens, license plates and credit cards) and locations (e.g, bathrooms and bedrooms). It uses the contextual information obtained from the wearable's sensors and recorded images to identify the potential sensitive subjects in each image. Using image processing techniques, first the sensitive subjects are recognized and then blurred or eliminated. Finally the edited image is ready to publish. Using a practical case study, we experimentally evaluate the proposed framework. Our experimental results show that the proposed system can detect and blur the sensitive subjects among around 300 images with around 70% accuracy.

关键词： Privacy Credit cards Detectors Legged locomotion Neural networks Cameras image recognition

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The Potential Utility of image Descriptions: User Identity Linkage across Social Networks Based on MultiModal Self-Attention Fusion

The Potential Utility of Image Descriptions: User Identity L...

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IEEE International conference on Performance, Computing and communications (IPCCC)

作者： Yunfeng Li Gaopeng Gou Gang Xiong Zhen Li Mingxin Cui Chinese Academy of Sciences Institute of Information Engineering School of Cyber Security University of Chinese Academy of Sciences

The task of user identity linkage across social networks aims to predict whether users from different social networks refer to the same person. This task plays a crucial role in cross-social network information dissemination and intelligent recommendations. However, existing user identity linkage tasks suffer from several challenges: 1) excessive reliance on social network topology, neglecting users’ visual modality information; 2) inadequate handling of noise in user feature data; and 3) ineffective fusion of users’ multimodal information. To address these issues, we investigated a method that utilizes heterogeneous multimodal posts, including user-generated text, images, and check-in messages, to achieve user identity linkage across social networks. We innovatively leveraged a pre-trained model for image-to-text conversion to further explore users’ image data and proposed an adversarial learning model based on the multimodal self-attention mechanism (AMSA). The AMSA model consists of four components: user feature extraction, user feature processing, user feature fusion, and adversarial learning. Specifically, AMSA initially employed advanced pre-trained models to extract features from multiple modalities of users, including images and text. Subsequently, it utilized multiple mechanisms, such as multi-head self-attention, to process data from each modality separately and then fused them into user representation vectors. Finally, AMSA employed adversarial learning to enhance the model’s learning capacity and mitigate semantic disparities in user information across different platforms. We conducted model performance evaluations on publicly available datasets, and experimental results demonstrated the superiority of the proposed AMSA model.

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A Study on visual Interpretation of Network In Network

A Study on Visual Interpretation of Network In Network

引用

International Joint conference on Neural Networks

作者： Satoshi Suzuki Hayaru Shouno University of Electro-Communications

ISBN: (纸本)9781509061839

In recent years, Deep convolutional neural networks (DCNNs) have shown excellent performance in the image recognition field. A DCNN is one of the types of multi-layer neural networks, which can automatically obtain feature representation from input data. The Neocognitron, proposed by Kunihiko Fukushima in the 1980s, is a prototype of a DCNN. It was inspired by the hierarchical structure in the mammalian primary visual cortex. On the other hand, a method called Network In Network (NIN) has recently been proposed. This is a network architecture that embeds some translational symmetric micro networks in a DCNN, and it has been experimentally clarified that with it higher classification accuracy is obtained than in a conventional DCNN. However, it cannot be said that NIN has been as sufficiently analyzed from a physiological point of view compared to DCNNs. We focused on the similarities between the processing of NIN, which accumulates the feature extraction filter of a DCNN, and the operation of a mammalian visual structure called an "orientation continuity" which means preferred orientations of neighboring cells changes continuously, and pointed out the relationships between them. We also studied and pointed out the relevance of the neurophysiological knowledge and the process results obtained with high layer of NIN.

关键词： Feature extraction visualization Convolution Neurons Brain modeling Physiology Training

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Embedded video processing and data acquisition for unmanned aerial vehicle

Embedded video processing and data acquisition for unmanned ...

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International conference on Computers, communications, and Systems (ICCCS)

作者： Vrunal Mhatre Siddhesh Chavan Aaron Samuel Akshay Patil Ashish Chittimilla Naveen Kumar Fr. Conceicao Rodrigues College of Engineering(I.T) Mumbai India Fr. Conceicao Rodrigues College of Engineering (Pr) Mumbai India Fr. Conceicao Rodrigues College of Engineering (ECE) Mumbai India

ISBN: (纸本)9781467397575

Drone technology has advanced to aid applications in field of defense, emergency, disaster relief and digital imaging. Inheriting all such applications for Unmanned Aerial Vehicle (UAV) in low cost scale to make system for ubiquitous for all domains is the motive for our system. Hence, embedding high quality video feed and controlling flight data characteristics to execute several applications. Our system has been devised specifically for air navigation and hence, seamless performance of all the components placed on-board is maintained with high compactness in form factor. First Person View (FPV) is provided for pilots for to achieve long distance mission execution along with image processing for accurate data analysis of flight characteristics. Along with this, the telemetry data procured from Arduino integrated with sensors viz., GPS, Altimeter, IMU assists the pilot for maintaining steady flight characteristics. Our system has been rigorously tested and has also been presented for Society of Automotive Engineers (SAE) Aero Design competition to accomplish humanitarian relief operation. The low-cost general processing boards like Raspberry Pi and Arduino facilitates versatility in embedding various sensors based on requirements of the pilot. Along with the on-board the telemetry system, the Ground Control System (GCS) provides first person visual aid on base station. The JavaFx interface is platform independent with features like FPV video streaming in real-time, representation of UAV's altitude, orientation and position at every instance of time. Moreover, the trans-receiver communication allows controlling flight characteristics from the interface, increasing the scope of applications with UAV.

关键词： Unmanned aerial vehicles Streaming media Cameras Sensors Global Positioning System Telemetry Real-time systems

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Oversampled A/D conversion of non-bandlimited signals with finite rate of innovation

Oversampled A/D conversion of non-bandlimited signals with f...

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

作者： I. Jovanovic B. Beferull-Lozano Audio-Visual Communications Laboratory Swiss Federal Institute of Technology Lausanne Switzerland

We consider the problem of A/D conversion for non-bandlimited signals that have a finite rate of innovation, in particular, the class of a continuous periodic stream of Diracs, characterized by a set of time positions and weights. Previous research has only considered the sampling of these signals, ignoring quantization which is necessary for any practical application (e.g. UWB, CDMA). In order to achieve accuracy under quantization, we introduce two types of oversampling, namely, oversampling in frequency and oversampling in time. High accuracy is achieved by enforcing the reconstruction to satisfy either three convex sets of constraints related to (1) sampling kernel, (2) quantization and (3) periodic streams of Diracs, which is then said to provide strong consistency, or only the first two, providing weak consistency. We propose three reconstruction algorithms, the first two achieving weak consistency and the third one achieving strong consistency. For these three algorithms, respectively, the experimental MSE performance for time positions decreases as O(1/R/sub t//sup 2/ R/sub f//sup 3/), and O(1/R/sub t//sup 2/ R/sub f//sup 4/), where R/sub t/ and R/sub f/ are the oversampling ratios in time and in frequency, respectively. It is also proved theoretically that our reconstruction algorithms satisfying weak consistency achieve an MSE performance of at least O(1/R/sub t//sup 2/ R/sub f//sup 3/).

关键词： Technological innovation Quantization Sampling methods Frequency Kernel Reconstruction algorithms Multiaccess communication Laboratories Streaming media Communication systems

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