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共 6215 条记录，以下是201-210 订阅

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A Neural Network-based Method for Eliminating Stripe Noise 4

A Neural Network-Based Method for Eliminating Stripe Noise

引用

4th IEEE international conference on Electronic Communications, internet of Things and Big Data, ICEIB 2024

作者： Qiu, Shuaihui Wang, Haitao Li, Junhua Chi, Mingwei Harbin Xinguang Optic-electronics Technology Co. Ltd. Harbin150028 China Geely University of China Chengdu641423 China

ISBN: (纸本)9798350360721

The uneven photoelectric response of the infrared imaging detector system due to the level of craftsmanship results in a fixed deviation in the response of each pixel to the incident light signal. The deviation appears as a stripe noise on the output image, seriously reducing image quality. Infrared images with stripe noise seriously affect application results, therefore the original details of the image need to be effectively preserved by removing all stripe noise artifacts and balancing real-time performance. We proposed a new method for removing stripe noise using the correlation between adjacent column signals to remove independent column stripe noise. Deep neural networks were used to implement this method, using the estimated noise output from the previous network iteration as the input to the next iteration of the network. This approach effectively reduced the search space for function approximation and allowed for effective training on larger datasets. This method can be used to estimate the stripe noise of infrared images and preserve scene details to a large extent. A large number of experimental results showed that the proposed research method has significant effects. © 2024 IEEE.

关键词： Iterative methods

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A Novel Three-Stage PolSAR Ship Detection Framework based on Deep Learning 2

A Novel Three-Stage PolSAR Ship Detection Framework based on...

引用

2nd IEEE international conference on signal, Information and Data Processing, ICSIDP 2024

作者： Xue, Junfan Yin, Junjun Yang, Jian University of Science and Technology Beijing School of Computer & Communication Engineering Beijing China Tsinghua University Department of Electronic Engineering Beijing China

ISBN: (纸本)9798331515669

Polarimetric Synthetic Aperture Radar (PolSAR) image ship detection is one of the crucial applications of PolSAR systems and holds significant research value. However, current deep learning-based polarimetric SAR image ship detection methods face challenges such as difficult post-processing and slow detection speed. To solve the above problems, we propose a novel Three-Stage Polarimetric SAR Ship Detection Framework based on deep learning. The main concept is to use a sliding window to extract image slice samples, then employ the Ship Coarse Location Module (SCLM) to identify slice samples containing ships. Next, the Polarization Feature Enhancement Module (PFEM) enhances the features of these slice samples to reduce the feature distance of pixels of the same category and increase the feature distance of pixels of different categories. Afterward, the enhanced slice samples are fed into the KAN Vision Transformer Detection Module (KVITDM) for patch-level detection. Finally, decision fusion is applied to combine the detection results generated from different initial sliding window positions. Experimental results show that the proposed method has good performance in different scenes and outperforms traditional and existing deep learning-based polarimetric SAR ship detection methods. © 2024 IEEE.

关键词： Deep learning

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Supervision system on internet advertising based on artificial intelligence technology 8

Supervision system on Internet advertising based on artifici...

引用

8th international conference on Information systems Engineering, ICISE 2023

作者： Qin, Dongyang Li, Zuyang Yan, Yu Wuhan Donghu University School of Literature and Law Wuhan China

ISBN: (纸本)9798350307009

With the rapid development of internet advertising, regulatory issues have become increasingly acute, and traditional regulatory methods have been failed to meet the changing needs of internet advertising. Therefore, this paper, based on artificial intelligence technologies such as natural language processing, image recognition, machine learning and data tracking, designs an internet advertising supervision system for strengthening supervision, improving recognition rates, establishing a unified database and data prediction system. This study is conducive to the optimization and upgrading of advertising supervision and the sound development of the internet advertising industry. © 2023 IEEE.

关键词： Marketing

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A YOLOv9-based Night-Time signal Light Detection Method in Carla Environment

A YOLOv9-Based Night-Time Signal Light Detection Method in C...

引用

2024 IEEE international conference on Unmanned systems, ICUS 2024

作者： Wan, He Ruan, Jiageng An, Weichuan Hao, Ruohan Beijing University of Technology Beijing China

ISBN: (纸本)9798350384185

With the continuous progress of machine learning technology, automatic driving perception technology is gradually becoming mature. As a guarantee of normal traffic operation, signal lights can effectively guide vehicles to pass correctly. The recognition of signal lights mainly relies on pure visual target detection technology. And the correct recognition of traffic signals can reduce the occurrence of traffic accidents and provide safety for unmanned driving. However, the recognition effect of small targets at night is poor, and is prone to misdetection and omission, etc. Therefore, the pure visual target detection technology for traffic signals still faces great challenges to accurately identify targets in special scenes. In this paper, the latest YOLOv9 image target recognition technology is used to improve the target detection ability in harsh environments. The advantages and disadvantages of different algorithms in low illumination environments such as night time are evaluated by using YOLOv8 and YOLOv9 target detection algorithms. Carla simulation environment was conducted to validate the recognition effectiveness of YOLOv9. The results show that the YOLOv9 algorithm is better at recognizing signal lights at night and the detection accuracy exceeds that of the previous versions of the series, ensuring the recognition accuracy of signal lights in different environments. © 2024 IEEE.

关键词： Traffic signals

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Towards reliable medical image analysis based on deep learning with XAI

Towards reliable medical image analysis based on deep learni...

引用

2023 international conference on image, signal Processing, and Pattern Recognition, ISPP 2023

作者： Hao, Jingbo School of Information and Artificial Intelligence Nanchang Institute of Science & Technology 998 Gezaoshan Ave. Honggutan District Nanchang China

ISBN: (纸本)9781510666351

Deep learning-based medical image analysis (DLB-MIA) has achieved great success hitherto, but is in urgent need of model interpretability. Explainable artificial intelligence (XAI) can be used for improving model interpretability and is expected to help in providing crucial trustworthiness in DLB-MIA. To expedite the utilization of XAI technology for reliable DLB-MIA, the current status of XAI methods and toolkits is introduced firstly. The application of XAI technology in DLB-MIA tasks is then discussed with close attention in respect of method taxonomies and adversarial robustness respectively. © 2023 SPIE.

关键词： Deep learning

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Case study of digital innovation process improvement, using BPMN, case-based reasoning, and text mining 16

Case study of digital innovation process improvement, using ...

引用

16th international conference on signal-image technology and internet-based systems (SITIS)

作者： Proskurin, Maksym Monticolo, Davy Boly, Vincent Marche, Brunelle Univ Lorraine ERPI EA 3767 Nancy France

ISBN: (纸本)9781665464956

Managers of digital products frequently receive feature requests from customers, end users, C-suite executives, and other company officials. They need to collect, process, and implement such requests to implement the most valuable features. Moreover, it is often difficult to decide which requests should be applied The product backlog prioritization strategy is a well-known method widely utilized to enhance this process. However, it is time-consuming because ofthe large amount of data and is also subject to the human factor. Moreover, the current literature lacks models allowing automated recommendations to help speed up feature request processing, especially for digital startups with a lack ofresources. In this paper, we used BPMN to illustrate a case study of redesigning an innovation process in a digital startup. Furthermore, based on the To-Be Process model, we created an approach to recommend new features using case-based reasoning and text mining.

关键词： Innovation process BPMN 2.0 case-based reasoning text mining software as a services

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SELF-POWERED REAL-TIME WIRELESS COMMUNICATION SYSTEM USING WEARABLE FABRIC based TRIBOELECTRIC NANOGENERATOR AND INDUCTOR 37

SELF-POWERED REAL-TIME WIRELESS COMMUNICATION SYSTEM USING W...

引用

37th IEEE international conference on Micro Electro Mechanical systems (MEMS)

作者： Yun, Jonghyeon Kim, Daewon Kyung Hee Univ Dept Elect & Informat Convergence Engn Seoul South Korea Kyung Hee Univ Dept Elect Engn Seoul South Korea

ISBN: (纸本)9798350357929

With the rapid growth of internet of Things, self-powered wireless communication systems are crucial. This paper demonstrates a self-powered wearable system with real-time wireless communication (SWRC) using a fabric-based triboelectric nanogenerator (F-TENG). The proposed system utilizes an ambient mechanical energy and it can conduct a wireless communication for 150 cm with a signal-to-noise ratio (SNR) of 2.62 dB. Notably, the SWRC demonstrate a 70 ms faster operation than commercial force sensors in contact states. Considering these results, our proposed system is expected to be utilized at the industrial field in near future due to its great potential.

关键词： Self-powered wireless communication real-time communication triboelectric nanogenerator wearable system

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Kinect-based Data Processing Noncontact Robotic Arm Control System 16

Kinect-based Data Processing Noncontact Robotic Arm Control ...

引用

16th international conference on signal-image technology and internet-based systems (SITIS)

作者： Cheng, Xu Kimoto, Tadahiko Toyo Univ Grad Sch Sci & Engn Kawagoe Saitama Japan

ISBN: (纸本)9781665464956

We propose a method to control the motion of a robotic arm in real-time by using Kinect sensors to identify, track and simulate the motion of a human arm. This method uses Kinect's 3D skeleton tracking technology to obtain joint data and controls the motion of the robot arm after processing the data. The biggest attempt of this research is to apply the spatial 3D shear transformation to the actual manipulator control, hoping to correct the arm data of different heights, arm lengths, and arm swing amplitudes into a unified operation unit space, and to limit the position of robot arm through the joint angle. In addition, by adding two-hand gesture recognition conditions to assist control, increase control functions as much as possible, and improve the control system. In this way, the cost of relying on external equipment in the traditional manipulator control scheme is reduced, which also proves the feasibility of such a method.

关键词： Kinect 3D Shear Contactless Control Gesture Recognition Robotic Arm Control Data Processing Cost of Production

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Experimental Evaluation of LED-based Wearable Transmitter for Optical Camera Communications systems 17

Experimental Evaluation of LED-based Wearable Transmitter fo...

引用

17th international conference on Telecommunications (ConTEL)

作者： Niarchou, Eleni Matus, Vicente Rabadan, Jose Guerra, Victor Perez-Jimenez, Rafael IDeTIC ULPGC Las Palmas Gran Canaria Spain Pi Lighting Valais Switzerland

ISBN: (纸本)9798350302233

In this paper, we experimentally demonstrate an optical camera communications (OCC) system for wearable light-emitting diode (LED) as the transmitter. Wearable devices are powerful tools for supporting internet of Things (IoT) systems because of their sensing, processing, and communication capability. The term "wearable devices" refers to a wide range of products that can be integrated into clothing and accessories, thus allowing real-time data detection, storage, and exchange without human intervention. This paper presents the practical evaluation of an LED-based wearable transmitter for an OCC system to demonstrate its feasibility. In particular, an LED array attached to the body is modulated using on-off keying to transmit data via visible light, and a smartphone camera captures video of the user wearing the device while slightly moving in a static position in the room. Finally, the data is decoded from the video frames using an image processing algorithm that tracks the source and demodulates the signal.

关键词： Optical camera communications (OCC) visible light communications (VLC) internet of Things (IoT) wearable devices image processing

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Trustworthiness and explainability of a watermarking and machine learning-based system for image modification detection to combat disinformation 24

Trustworthiness and explainability of a watermarking and mac...

引用

19th international conference on Availability, Reliability, and Security (ARES)

作者： Rosales, Andrea Malanowska, Agnieszka Araghi, Tanya Koohpayeh Kuribayashi, Minoru Kowalczyk, Marcin Blanche-Tarrago, Daniel Mazurczyk, Wojciech Megias, David Univ Oberta Catalunya Internet Interdisciplinary Inst IN3 Barcelona Spain Warsaw Univ Technol Warsaw Poland Univ Oberta Catalunya Ctr Cybersecur Res Catalonia CYBERCAT Internet Interdisciplinary Inst IN3 Barcelona Spain Tohoku Univ Ctr Data Driven Sci & Artificial Intelligence Sendai Japan

ISBN: (纸本)9798400717185

The widespread use of digital platforms, prioritising content based on engagement metrics and rewarding content creators accordingly, has contributed to the proliferation of disinformation and its far-reaching social and political impact. In addition, digital platforms often operate as black boxes, concealing their decision-making processes from users and prioritizing investor interests over ethical and social considerations. Consequently, this has contributed to the erosion of general trust in verification systems. To mitigate this issue, our project proposes a two-stage verification system. The first stage allows media industries to watermark their image and video content. The second stage involves implementing a machine-learning-based manipulation detection system for suspicious content. We present findings from an international user experience study, where potential online news consumers verified the authenticity of images on a prototype version of our system. In this paper, we reflect on critical issues of explainability addressed by participants in our user study and how we addressed this issue in the platform's design.

关键词： Integrity Authentication Watermarking Disinformation Fake news Forensic tools Machine learning

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