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检索条件"任意字段=IEEE International Conference on Signal Image Technology and Internet Based Systems"

共 20446 条记录，以下是111-120 订阅

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AeroDehazeNet: Exploiting Selective Multi-Scale Transformers for Aerial image Dehazing 20

AeroDehazeNet: Exploiting Selective Multi-Scale Transformers...

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20th ieee international conference on Advanced Video and signal-based Surveillance (AVSS)

作者： Gonde, Kartik Patil, Prashant W. Vipparthi, Santosh Kumar Murala, Subrahmanyam Patil, Pramod Kimbahune, Vinod Dr DY Patil Inst Technol Pimpri India Indian Inst Technol Guwahati Gauhati India Indian Inst Technol Ropar CVPR Lab Rupnagar India Trinity Coll Dublin Sch Comp Sci & Stat CVPR Lab Dublin Ireland

ISBN: (纸本)9798350374292;9798350374285

Remote sensing is the task of analyzing and acquiring useful information from satellite images captured at a far distance from the earth's surface. These images are vulnerable to degradation due to the presence of mist or haze. Existing methods either make use of prior information to estimate haze free images, or use CNN architectures based on generative adversarial networks (GANs) or Transformers. Though the state-of-the-art transformer-based architectures helped to dehaze the aerial images, they lacked the ability to capture multi-scale dependencies of the image. Identifying this shortcoming, we propose AeroDehazeNet based on a transformer that captures multi-scale dependencies along with global dependencies of the image. Our network comprises of three key components: (1) a multi-scale selective attention (MScA) network to attentively process the multi-scale information in an image, (2) residual attention network (RAN in feed forward network responsible for distilling non-degraded features passed from MScA, and (3) high frequency dominant skip connection (HFDS) block for passing diverse features (low frequency and high frequency) prominent with multi-scale edge features from encoder levels to adjacent decoder levels. The extensive quantitative and qualitative comparisons with existing methods on synthetic and realworld data plus exhaustive ablation study demonstrate the efficacy of our proposed network over transformer based state-of-the-art architectures with comparatively less number of parameters and FLOPs. Testing code is available at https://***/KartikGonde/AeroDehazeNet.

关键词： Aerial photography

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A NEW EFFICIENT SPLIT & MERGE ALGORITHM FOR EMBEDDED systems 31

A NEW EFFICIENT SPLIT & MERGE ALGORITHM FOR EMBEDDED SYSTEMS

引用

2024 international conference on image Processing

作者： Maurice, Nathan Sopena, Julien Lacassagne, Lionel Sorbonne Univ LIP6 Paris France

ISBN: (纸本)9798350349405;9798350349399

This article presents a new image segmentation algorithm based on a Split & Merge approach. By nature, the execution time of Split & Merge algorithms is data-dependent, as their halting conditions are tied to the homogeneity of each region. While previous algorithms made the Split step less sensitive to input data, the execution time of the more complex Merge step remains highly sensitive to image content. This paper tackles the sensitivity and performance problems from a system and architecture perspective. Memory reallocations due to array fusions are eliminated with the introduction of a TTA (Three Table Array) structure in the Merge step. As iterating over entries in this structure causes a loss of memory locality, we propose two new mechanisms that implement a software cache to mitigate this. An experimental study on an embedded system (Nvidia Jetson Xavier NX) has shown our Merge algorithm to be 10.6 times faster than the state-of-the-art Split & Merge algorithm for 960 x 720 images. Moreover, the execution time of our algorithm is also more resistant to image characteristics.

关键词： image segmentation Merging Embedded systems Data structures

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From Blackboards to Byteboards: Adapting to the Digital Age in Undergraduate Education on Campus 17

From Blackboards to Byteboards: Adapting to the Digital Age ...

引用

17th international conference on signal-image technology and internet-based systems, SITIS 2023

作者： Anannya, Tasmiah Tamzid Mahmud, Sharifa Rania Khan, Shahriar Rahman Zaman, Syed Rohit Jalal, Md. Shah Sharmin, Sadia Bangladesh University of Engineering and Technology Department of Computer Science and Engineering Bangladesh Military Institute of Science and Technology Department of Computer Science and Engineering Bangladesh American International University Department of Computer Science Bangladesh

ISBN: (纸本)9798350370911

In the current educational landscape, maintaining student engagement is a persistent challenge. This paper addresses this issue and investigates the potential of attention engineering as a solution to enhance engagement among undergraduate students. The main goal is to investigate the use of attention engineering techniques in undergraduate education to find effective methods and measure their impact on student engagement and academic performance. This research conducts a thorough literature review to assess the feasibility and effectiveness of these techniques in undergraduate classrooms, exploring the utilization of personalized content, interactive tools, and data-driven insights to maintain student attention. To improve attention and learning, several technology tools, and strategies such as online videos and tutorials, interactive multimedia content, gamification, flipped learning, social network tools, and Learning Management systems (LMS) are studied. This research addresses three key research questions, the impact of technology integration and interactive activities on student engagement and comprehension, effective technology-based tools for learning environments, and the influence of attention-centric teaching strategies on student learning outcomes. This research identifies focused technologies and approaches, as well as the country attaining and the most utilized technology from current works. Our research has also proposed some findings that offer valuable guidance for educators and institutions seeking to optimize teaching methods and ultimately improve the learning experience in undergraduate education. © 2023 ieee.

关键词： Students

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Design of JPEG2000 image Compression System based on ADV212 for Satellites

Design of JPEG2000 Image Compression System Based on ADV212 ...

引用

2024 ieee international conference on Control Science and systems Engineering, ICCSSE 2024

作者： Li, Enshi Zhou, Li Zhu, Yan National Space Science Center of Chinese Academy of Sciences Bejing China

ISBN: (纸本)9798331517199

Due to the limitations of spacecraft data processing capabilities and the data transmission rate to the ground, the image compression system is essential for imaging payloads on satellites. JPEG2000, with its advantages of high compression ratio, high signal-to-noise ratio, support for progressive transmission, and absence of mosaic distortion, is a preferred algorithm for image compression in spaceborne cameras. In response to the complexity of the JPEG2000 algorithm and the challenges of hardware implementation, this paper presents an image compression system based on the ADV212 image compression chip for realizing JPEG2000 compression. The FPGA is utilized for image buffering and control of the compression system, while the ADV212 chip performs the compression functions. The experimental results validate the high performance and compatibility of the system. This system boasts advantages such as simple hardware and software implementation, high efficiency, superior performance, short development cycle, and low cost, which makes it suitable for aerospace applications, particularly in commercial space satellites. © 2024 ieee.

关键词： image compression

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VIZECGNET: VISUAL ECG image NETWORK FOR CARDIOVASCULAR DISEASES CLASSIFICATION WITH MULTI-MODAL TRAINING AND KNOWLEDGE DISTILLATION 31

VIZECGNET: VISUAL ECG IMAGE NETWORK FOR CARDIOVASCULAR DISEA...

引用

2024 international conference on image Processing

作者： Nam, Ju-Hyeon Park, Seo-Hyung Kim, Su Jung Lee, Sang-Chul Inha Univ Dept Elect & Comp Engn Incheon South Korea

ISBN: (纸本)9798350349405;9798350349399

An electrocardiogram (ECG) captures the heart's electrical signal to assess various heart conditions. In practice, ECG data is stored as either digitized signals or printed images. Despite the emergence of numerous deep learning models for digitized signals, many hospitals prefer image storage due to cost considerations. Recognizing the unavailability of raw ECG signals in many clinical settings, we propose VizECGNet, which uses only printed ECG graphics to determine the prognosis of multiple cardiovascular diseases. During training, cross-modal attention modules (CMAM) are used to integrate information from two modalities - image and signal, while self-modality attention modules (SMAM) capture inherent long-range dependencies in ECG data of each modality. Additionally, we utilize knowledge distillation to improve the similarity between two distinct predictions from each modality stream. This innovative multi-modal deep learning architecture enables the utilization of only ECG images during inference. VizECGNet with image input achieves higher performance in precision, recall, and F1-Score compared to signal-based ECG classification models, with improvements of 3.50%, 8.21%, and 7.38%, respectively.

关键词： Deep Learning signal Processing Multi-Modality Learning ECG Classification

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JPEG ENCRYPTION WITH DC PREDICTION AND RUN-based RS PAIRS PERMUTATION 49

JPEG ENCRYPTION WITH DC PREDICTION AND RUN-BASED RS PAIRS PE...

引用

49th ieee international conference on Acoustics, Speech, and signal Processing (ICASSP)

作者： Wang, Yanyixiao Li, Peiya Jinan Univ Coll Cyber Secur Guangzhou Peoples R China

ISBN: (纸本)9798350344868;9798350344851

JPEG image encryption technology converts original images into noise-like images that do not contain any useful information, ensuring the security and privacy of valuable images. At present, most existing work may not achieve a good balance between file size preservation and security. Therefore, in order to solve this issue, we present a new JPEG image encryption scheme. In our scheme, we first perform predictions on the DC coefficients, and then implement averaging operation on the prediction error, which provides security effects while effectively decreases the encoding length. To further strengthen the diffusion performance, block permutation excluding the DC coefficients is executed. In addition, in order to control the file size growth, AC coefficients are protected by the run-based RS (run/size) pairs permutation. The experimental results show that the proposed scheme can not only effectively preserve the image file size, but also offers satisfactory security.

关键词： image encryption JPEG image DC prediction RS pairs permutation File size preservation

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Multi-angle image Fusion in Ground-based Radar Lunar Imaging based on image Kurtosis 2

Multi-angle Image Fusion in Ground-based Radar Lunar Imaging...

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

作者： Yang, Yuewen Liu, Peiyao Zhu, Kaiwen Wang, Zhen Sun, Tao Ding, Zegang Beijing Institute of Technology School of Information and Electronics Beijing China Ministry of Education Beijing China

ISBN: (纸本)9798331515669

The fusion of multi-angle lunar images can provide more comprehensive lunar topography information than original images, and ground-based (GB) radar has the ability to acquire multi-angle lunar images. In GB radar multi-angle lunar image fusion, proper radar trajectories should be selected, and image fusion algorithm should be used. In this paper, the multi-angle lunar image fusion technique for GB synthetic aperture radar (SAR) based on image kurtosis is proposed. To begin with, the echo signal model considering space-variant backscattering coefficient is established to reflect lunar topography feature. After that, a multi-angle radar trajectory selection method based on K-means algorithm is proposed to acquire multi-angle lunar images. Thereafter a multi-angle lunar image fusion algorithm based on image kurtosis and gradient descent is proposed to acquire the fused image. Finally, computer simulation results validate the effectiveness of the proposed technique. © 2024 ieee.

关键词： image fusion

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Automated Corn Leaf Disease Diagnosis using ResNet-based Convolutional Neural Network 2

Automated Corn Leaf Disease Diagnosis using ResNet-based Con...

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2nd international conference on Intelligent Cyber Physical systems and internet of Things (ICoICI)

作者： Kant, Vishnu Chitkara Univ Inst Engn & Technol Rajpura 140401 Punjab India

ISBN: (纸本)9798331540661;9798331540678

Corn leaf diseases, consisting Common Rust, Gray Leaf Spot, and Blight, pose significant threats to worldwide farming by affecting crop harvest and standards. Blight causes rapid defoliation of plants;Common Rust brought on by Puccinia sorghi and Grey Leaf Spot reduces photosynthesis and yields losses. Early and accurate detection is crucial for timely intervention, reducing chemical dependency, and ensuring food security. This study leverages Residual Networks (ResNet) to advance disease detection. ResNet's deep residual learning architecture efficiently handles complex image classification tasks. Trained on maize leaf images, the ResNet model achieved 96% accuracy in classifying leaves into common rust, gray leaf spot, blight, and healthy categories. A model's high precision and recall significantly enhance detection accuracy. This work supports sustainable agriculture, promotes resilient agricultural practices, and contributes to food security by improving disease control and crop management through advanced technology.

关键词： Artificial Intelligence Residual Networks (ResNet) image Classification Deep Learning Crop Yield Sustainable Agriculture Food Security Disease Detection Precision Agriculture Agricultural Sustainability Machine Learning Plant Pathology

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Power internet of Things Access System based on Low Power Communication technology 14

Power Internet of Things Access System Based on Low Power Co...

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14th ieee international conference on Communication systems and Network Technologies, CSNT 2025

作者： Jiang, Zhigang Ren, Liming Zhu, Bing Jiang, Jiafeng School of Computer Science and Technology University of Science and Technology of China Anhui Hefei230000 China School of Department of Electronic Information and Electrical Engineering Hefei University Anhui Hefei230000 China School of Computer and Information Hefei University of Technology Anhui Hefei230000 China School of Information Engineering Inner Mongolia University of Science and Technology Inner Mongolia Baotou014017 China

ISBN: (纸本)9798331531935

In response to the issues of data transmission energy efficiency and network coverage in the power internet of Things system, this study introduces an access scheme based on low-power communication technology. By optimizing the network architecture and communication protocol, the aim is to improve the energy efficiency of sensor nodes in the power internet of Things and reduce communication latency. Firstly, an access scheme based on low power wide area network (LPWAN) technology is designed. LoRa (Long Range Radio) or NB-IoT (Narrow Band internet of Thing) is selected as the communication protocol. By optimizing the working mode of sensor nodes, periodic transmission and event-driven mechanism are adopted. Secondly, an adaptive data transmission mechanism is designed to dynamically adjust the transmission frequency and rate according to environmental changes to ensure reliability under different network conditions. Furthermore, deep sleep mode and power consumption scheduling algorithm are adopted, and the network architecture adopts star topology to ensure the efficiency of signal coverage and data forwarding, and the secure transmission of data information is guaranteed by encryption and authentication mechanism. Finally, through simulation and actual deployment, the performance of the scheme in the actual environment is verified, and its stability and data transmission efficiency under different network scales are evaluated. The battery life of periodic wake-up mode is significantly lower than that of deep sleep mode. Under low-frequency transmission (once an hour), the battery life is 320 days. In periodic wake-up mode, the average power consumption of sensor nodes is significantly higher than that of deep sleep mode. At low frequency transmission, average power consumption is 3.5 mW and battery life drops to 75 days. The power internet of Things access system based on low-power communication technology proposed in this work effectively solves the bottleneck pr

关键词： internet of things

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Application of internet of Thing (IoT) for Precision Farming 16

Application of Internet of Thing (IoT) for Precision Farming

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

作者： Songruk, Apidat Arunrungrusmi, Somchai Tunlasakun, Khanchai Suwannakhum, Sirimonpak Mungkungline, Narong Poonthong, Wittawat Yuji, Toshifumi King Mongkuts Univ Technol Thonburi Dept Elect technol Educ Bangkok Thailand King Mongkuts Univ Technol Thonburi Fac Ind Educ & Technol Bangkok Thailand

ISBN: (纸本)9781665464956

With the increasing popularity of the internet of Things (IOT) and devices getting smarter, this research has presented an idea to reform the weather information for precision farming. In this study, the information of weather forecast was prepared for air quality control systems using the sensor of network systems to increase the quality of organic vegetable in Thailand under the condition of Thailand weather The prototype model was described by the devices of embedded systems, which is gotten from the temperature and humidity sensor. Therefore, if there is any data from the input sensor, the users are allowed to access and granted to use this system, then, the log data are transmitted by the internet to the designation website by using a Wi-Fi module (ESP8266). As a result, it can be used the machine learning algorithms for implementing of monitor controller, which is applied for analyzing and collecting data to air quality control in green house

关键词： internet of Thing Arduino smart agriculture

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