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image RETRIEVAL WITH LINGUAL AND visual PARAPHRASING VIA GENERATIVE MODELS

IMAGE RETRIEVAL WITH LINGUAL AND VISUAL PARAPHRASING VIA GEN...

引用

ieee International conference on image processing (ICIP)

作者： Yanagi, Rintaro Togo, Ren Ogawa, Takahiro Haseyama, Miki Hokkaido Univ Grad Sch Informat Sci & Technol Sapporo Hokkaido Japan Hokkaido Univ Educ & Res Ctr Math & Data Sci Sapporo Hokkaido Japan Hokkaido Univ Fac Informat Sci & Technol Sapporo Hokkaido Japan

ISBN: (纸本)9781728163956

A new approach that improves text-based image retrieval (hereinafter referred to as TBIR) performance is proposed in this paper. TBIR methods aim to retrieve a desired image related to a query text. Especially, recent TBIR methods allow us to retrieve images considering word relationships by using a sentence as a query. In these TBIR methods, it is necessary to uniquely identify a desired image from similar images using a single query sentence. However, the diverse expressive styles for a query sentence make it difficult to uniquely identify a desired image. In this paper, we propose a novel TBIR method with paraphrasing on multiple representation spaces. Specifically, by paraphrasing a query sentence on lingual and visual representation spaces, the proposed method can retrieve a desired image from various perspectives and then it can uniquely identify a desired image from similar images. Comprehensive experimental results show the effectiveness of the proposed method.

关键词： Text-based image retrieval paraphrasing vision and language generative model

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Nearly Reversible image-to-image Translation Using Joint Inter-Frame Coding and Embedding

Nearly Reversible Image-to-Image Translation Using Joint Int...

引用

ieee visual communications and image processing (VCIP)

作者： Xinzhu Cao Yuanzhi Yao Nenghai Yu University of Science and Technology of China Hefei China

ISBN: (纸本)9781728173221

image-to-image translation tasks which have been widely investigated with generative adversarial networks (GAN) aim to map an image from the source domain to the target domain. The translated image can be inversely mapped to the reconstructed source image. However, existing GAN-based schemes lack the ability to accomplish reversible translation. To remedy this drawback, a nearly reversible image-to-image translation scheme where the reconstructed source image is approximately distortion-free compared with the corresponding source image is proposed in this paper. The proposed scheme jointly considers inter-frame coding and embedding. Firstly, we organize the GAN-generated reconstructed source image and the source image into a pseudo video. Furthermore, the bitstream obtained by inter-frame coding is reversibly embedded in the translated image for nearly lossless source image reconstruction. Extensive experimental results and analysis demonstrate that the proposed scheme can achieve a high level of performance in image quality and security.

关键词： image quality image coding visual communication Generative adversarial networks Security Task analysis image reconstruction

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The Retinex Decomposition Model for X-ray Coronary Angiographic Sequences 6

The Retinex Decomposition Model for X-ray Coronary Angiograp...

引用

6th International conference on Signal and image processing, ICSIP 2021

作者： Xia, Shaoyan Liu, Xiaoli Zhu, Haogang Beihang University School of Computer Science and Engineering Beijing China Beihang University School of Biological Science and Medical Engineering Beijing China

ISBN: (纸本)9780738133737

Since the coronary angiographic vessel images take the low image contrast, the severe artefact, and blurred vascular structures, the complex background structure makes the image quality extremely poor. These shortcomings make it much more difficult to analyze angiographic vessels than the general vessel, such as OCT fundus vessels. To obtain high quality coronary angiographic images for post-processing, we propose the Retinex decomposition model. In this model, the foreground vessel and background part of the angiographic data can be regarded as the image reflectance and illumination, respectively. By using y direction gradient for the prior representation of coronary angiographic sequences, the feature matrix of coronary angiographic sequences in the log-transform domain is decomposed. Different from existing works, the proposed model can remove artefacts with the good visual performance. Moreover, the proposed model can perverse the vessel structure to some extent. Synthetic experiment experiment demonstrate the effectiveness of the proposed model compared to state-of-the-art methods both subjective and objective assessments. © 2021 ieee.

关键词： image enhancement

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visual Detection of Cells in Brain Tissue Slice for Patch Clamp System 11

Visual Detection of Cells in Brain Tissue Slice for Patch Cl...

引用

11th ieee Annual International conference on CYBER Technology in Automation, Control, and Intelligent Systems, CYBER 2021

作者： Ma, Yuxin Cai, Yunyao Wang, Zeyu Sun, Mingzhu Zhao, Xin College of Artificial Intelligence Nankai University Tianjin300071 China Inst. of Robotics and Automat. Info. System and the Tianjin Key Laboratory of Intelligent Robotic Nankai University Tianjin300350 China

ISBN: (纸本)9781665425278

Whole-cell patch clamping is the gold-standard technology for electrical activities recordings of living single cells. Since it is difficult to train patch clamp operators, automatic patch clamp technologies have gained much attention. The key step in fully automated patch clamping is visual detection of cells in brain tissue slice under view of differential interference contrast (DIC) microscope. This paper proposes a cell detection method based on DIC images, which includes image classification based on image clarity and visual detection of cells in brain tissue slice based on machine learning. Firstly, combining the gray features and texture features of DIC images, we define a clarity evaluation function based on principal component analysis (PCA). Afterwards, by using K-Means Algorithm, DIC images can be divided into clear class and blurred class. The precision of this method is 99.1% in test set, which indicates that it can select the images with clear cell contour from a series of DIC images for subsequent processing. Secondly, we design a neuron detection process based on sliding window and pre-Trained classifier to take cell detection in the selected clear images. We finally choose GoogLeNet as classifier in the detection process after comparing the advantages and disadvantages of classification methods based on support vector machine (SVM) and deep learning. The results show that the detected cells are basically operable living cells. The proposed cell detection technology in this paper provides an effective visual tool for fully automated patch clamping. © 2021 ieee.

关键词： image classification

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Human Action Recognition on Raw Depth Maps

Human Action Recognition on Raw Depth Maps

引用

ieee visual communications and image processing (VCIP)

作者： Jacek Trelinski Bogdan Kwolek AGH University of Science and Technology Kraków Poland

ISBN: (纸本)9781728173221

We propose an effective framework for human action recognition on raw depth maps. We leverage a convolutional autoencoder to extract on sequences of deep maps the frame-features that are then fed to a 1D-CNN responsible for embedding action features. A Siamese neural network trained on repre-sentative single depth map for each sequence extracts features, which are then processed by shapelets algorithm to extract action features. These features are then concatenated with features extracted by a BiLSTM with TimeDistributed wrapper. Given the learned individual models on such features we perform a selection of a subset of models. We demonstrate experimentally that on SYSU 3DHOI dataset the proposed algorithm outperforms considerably all recent algorithms including skeleton-based ones.

关键词： Solid modeling Three-dimensional displays image recognition visual communication Neural networks Benchmark testing Feature extraction

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Laser cleaning of multilayer paint coatings applied to aluminum alloys

Laser cleaning of multilayer paint coatings applied to alumi...

引用

2022 International conference on Electrical, Computer, communications and Mechatronics Engineering, ICECCME 2022

作者： Tofil, Szymon Witkowski, Grzegorz Laser Research Processing Centre Faculty of Mechatronics and Mechanical Engineering Kielce University of Technology Tysiąclecia Państwa Polskiego 7 Kielce Poland

ISBN: (数字)9781665470957

ISBN: (纸本)9781665470957

The paper presents a comparison of the effects of laser coating removal with the use of various laser devices. Laser cleaning of the surface layer for the aluminum alloy has been performed. Using different patch trajectory, power densities of the laser beam emitted by the pulsed Nd: YAG laser for the tested material, the best treatment conditions were selected for their cleaning. Basic research included microscopic analysis of surface topography and analysis of chemical composition in micro-areas. In order to clean the surface of contamination, laboratory comparative studies of the removal of coatings were carried out using the surface layer cleaning technique using pulsed laser TruMicro 5325c with UV radiation (343nm). Samples covered with various technological coatings were subjected to several variants of laser treatment (different laser power densities and different numbers of pulses). The paper presents selected results from laboratory tests. A Hirox KH-8700 microscope with digital image analysis was used to observe the cleaned surface layer. The JEOL JSM-7100f device was also used, enabling scanning electron microscopy (SEM) with the possibility of analyzing the chemical composition of the surface layer before and after laser cleaning. The cleaned surface does not have traces of laser melting, and only the effects of cleaning the coating are visible. After cleaning, a highly clean surface was obtained. In the case of very thick coatings, the cleaning process should be repeated several times. In order to intensify the purification process, a laser with a higher average power can also be used. © 2022 ieee.

关键词： Laser ablation

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A Basic Psychophysics Study of visual Masking Effect on Kanji Recognition for image Recognition Technology 18

A Basic Psychophysics Study of Visual Masking Effect on Kanj...

引用

ieee International conference on Mechatronics and Automation (ieee ICMA)

作者： Dai, Qi Yao, Lichang Hattori, Ikue Wu, Qiong Yang, Jiajia Takahashi, Satoshi Ejima, Yoshimichi Wu, Jinglong Okayama Univ Grad Sch Interdisciplinary Sci & Engn Hlth Syst 3-1-1 Tsushima Naka Okayama 7008530 Japan Suzhou Univ Sci & Technol Sch Educ Suzhou 215009 Peoples R China

ISBN: (纸本)9781665441018

The masking paradigm is the most used method for generating subliminal stimuli. When both the target stimulus and the mask stimulus are composed of spatial pattern, the mask reduces the visibility of the target. It was called pattern masking effect. Japanese kanji as special visual semantic information, especially when kanji as a subliminal visual stimulus, it is not clear whether Kanji is regulated by the pattern masking effect. Therefore, in this study, we measured the sensitivity index of Kanji detection or discrimination in the masking paradigm using the calculation method of SDT (Signal Detection Theory). By this way, present study investigated the intensity of the masking effect. Results suggested that the sensitivity index of Kanji have the significant difference between the different target presentation time both of detection and discrimination task. As the presentation time is longer, the sensitivity index increases. Results also showed that there is a difference in the cognitive process between detection and discrimination of stimuli, and even if the stimuli can be detected, they may not be discriminated. In addition, as the intensity of the stimulus increased, the intensity of the masking effect became weaker, and it was found that the pattern mask also produces a masking effect in the detection and discrimination of Kanji. According to the research on human visual processing characteristics, it is hoped to help improve the efficiency of computer vision recognition technology.

关键词： visual masking effect Japanese kanji Signal Detection Theory visual detection and discrimination task Subliminal stimuli

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Video Coding Pre-processing Based on Rate-Distortion Optimized Weighted Guided Filter

Video Coding Pre-Processing Based on Rate-Distortion Optimiz...

引用

ieee visual communications and image processing (VCIP)

作者： Xi Huang Luheng Jia Han Wang Kebin Jia Faculty of Information Technology Beijing University of Technology Beijing China

ISBN: (纸本)9781728173221

In video coding, it is always an intractable problem to compress high frequency components including noise and visually imperceptible content that consumes large amount bandwidth resources while providing limited quality improvement. Direct using of denoising methods causes coding performance degradation, and hence not suitable for video coding scenario. In this work, we propose a video pre-processing approach by leveraging edge preserving filter specifically designed for video coding, of which filter parameters are optimized in the sense of rate-distortion (R-D) performance. The proposed pre-processing method removes low R-D cost-effective components for video encoder while keeping important structural components, leading to higher coding efficiency and also better subjective quality. Comparing with the conventional denoising filters, our proposed pre-processing method using the R-D optimized edge preserving filter can improve the coding efficiency by up to −5.2% BD-rate with low computational complexity.

关键词： Video coding Degradation image coding image resolution visual communication Noise reduction Rate-distortion

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MobiDeep: Mobile DeepFake Detection through Machine Learning-based Corneal-Specular Backscattering

MobiDeep: Mobile DeepFake Detection through Machine Learning...

引用

Consumer communications and Networking conference, CCNC ieee

作者： Muhammad Mohzary Khalid J Almalki Baek-Young Choi Sejun Song School of Science and Engineering University of Missouri Kansas City MO USA Department of Computer Science Jazan University Jazan Saudi Arabia College of Computing and Informatics Saudi Electronic University Riyadh Saudi Arabia

DeepFake has accomplished notable advancement with the AI-leveraged production and manipulation techniques of fictitious human facial images. Despite many benign and fun applications, the generated fake images can negatively influence the authenticity of online information by originating deception, manipulation, persecution, and seduction, defying societal quality and human rights, which becomes critical security and privacy threat in social networks. Hence, real-time DeepFake detection and limitation technologies on the mobile platform are essential to building a controlled, harmless DeepFake ecosystem. This paper presents a real-time, cloudless, lightweight mobile app for human visual DeepFake detection using machine learning technologies named MobiDeep (Mobile DeepFake Detection through Machine Learning-based Corneal-Specular Backseat-tering). MobiDeep stems from a hypothesis that the existing DeepFake creation methods, including replacement, editing, and synthesis, lack the ensemble with the reflective objects. Focusing on the most reflective area of a human face, corneal-specular backscatter images of eyes, we seek the similarity and consistency with multiple surrounding environment features, including color components, shapes, and textures. We have implemented a cross-platform mobile application to evaluate the performance using various input parameters and lightweight Deep Neural Network (DNN) architectures. The empirical results show that MobiDeep achieves high accuracy (98.7%) and rapid detection speed (less than 200 ms) in detecting sophisticated DeepFake images within a subsecond.

关键词： Deep learning Deepfakes visualization Shape image color analysis Neural networks Focusing

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SDE-DualENet: A Novel Dual Efficient Convolutional Neural Network for Robust Stereo Depth Estimation

SDE-DualENet: A Novel Dual Efficient Convolutional Neural Ne...

引用

ieee visual communications and image processing (VCIP)

作者： Rithvik Anil Mansi Sharma Rohit Choudhary Mechanical Engineering IIT Madras Electrical Engineering IIT Madras

ISBN: (纸本)9781728173221

Stereo depth estimation is dependent on optimal correspondence matching between pixels of stereo-pair image to infer depth. In this paper, we attempt to revisit the stereo depth estimation problem in a simple dual convolutional neural network (CNN) based on EfficientNet that avoids the construction of a cost volume in stereo matching. This has been performed by considering different weights in otherwise identical towers of the CNN. The proposed algorithm is dubbed as SDE-DualENet. The architecture of SDE-DualENet eliminates the construction of cost-volume by learning to match correspondence between pixels with a different set of weights in the dual towers. The results are demonstrated on complex scenes with high details and large depth variations. The SDE-DualENet depth prediction network outperforms state-of-the-art monocular and stereo depth estimation methods, both qualitatively and quantitatively on challenging scene flow dataset. The code and pre-trained models will be made publicly available.

关键词： Costs Codes visual communication image processing Poles and towers Estimation Prediction algorithms

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