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Impact of Image Pre-processing Operations on Wheat Canopy Segmentation 2022

Impact of Image Pre-processing Operations on Wheat Canopy Se...

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14th international conference on Contemporary Computing, IC3 2022

作者： Gupta, Ankita Kaur, Lakhwinder Kaur, Gurmeet Department of Computer Science and Engineering Punjabi University Punjab Patiala India Department of Electronics and Communication Engineering Punjabi University Punjab Patiala India

ISBN: (纸本)9781450396752

this research work is an exploratory study of imaging methodologies that could aid in the development of wheat canopy segmentation and water stress detection systems. through the planned experimentation process, it was found that the chlorophyll fluorescence images needed to be pre-processed before being given as input to the segmentation algorithm for efficient extraction of regions of interest. For efficient canopy extraction, the enhancement associated with contrast and removal of random noise must be done. Multiple pipelines were constructed and it was empirically verified that the TV-L1 denoising with Primal-Dual algorithm is best suited for denoising. the contrast stretching method, also referred to as Min-Max, is the most appropriate operation for pre-processing the images. these pre-processing methods were extremely useful for extracting the area of an image that has maximum photosynthetic activity. the criteria for the selection of pre-processing methods are based on the quality of the segmentation algorithm that is computed using the metric Intersection Over Union. the work demonstrates a most constructive way to separate the wheat canopy from the chlorophyll fluorescence images, for the creation of an automatic drought detection system. © 2022 ACM.

关键词： Extraction

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Intelligent Archive Construction Driven by Artificial Intelligence

Intelligent Archive Construction Driven by Artificial Intell...

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international conference on Computational Intelligence and communication networks (CICN)

作者： Fucheng Zhu Fan Zhang Yong Liu College of information management Zhengzhou University of Aeronautics Zhengzhou CHINA

ISBN: (纸本)9781665487726

In this paper, starting from the perspective of information service, the artificial intelligence, wisdom, archives as the research object, by using the method of literature research and Internet research focuses on the artificial intelligence in the wisdom of the construction of archives, mining analysis existing wisdom archives construction cases at home and abroad, from theory to practice, the wisdom of the comprehensive analysis based on artificial intelligence archives construction facing the opportunities and challenges. It is concluded that the application of artificial intelligence technology makes it more convenient for users to consult archives, and also improves the efficiency of archivists.

关键词： Information services Internet communication networks Artificial intelligence Computational intelligence

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Cross-Layer Optimization for Underlay Cognitive Radio systems with Multicarrier Transmission

Cross-Layer Optimization for Underlay Cognitive Radio System...

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international conference on Computational Intelligence and communication networks (CICN)

作者： Nour Mansour Vaddadi V.K. Praneeth Dirk Dahlhaus Communications Laboratory University of Kassel

ISBN: (纸本)9781665487726

A novel scheme to enhance the spectral efficiency (SE) for an underlay cognitive radio system (UCRS) is proposed. A cross-layer optimization (CLO) of both the physical layer (PHY) and the data link control layer (DLC) of a secondary user (SU) transmission is considered. the transceiver uses discrete Fourier transform modulated filter banks. An optimum scheme for joint bit and power loading (JBPL) as well as coding adaptation (CA) using punctured convolutional codes is employed at the PHY. At the DLC, a truncated automated repeat request (TARQ) is implemented to ensure reliable transmission. A lower bound on the SE for coded transmission is derived analytically and maximized subject to different quality-of-service (QoS) and stochastic chance-based constraints as well as third-party colored Gaussian interference at the SU receiver. the system performance is analyzed in terms of the number of retransmissions and the achievable SU SE. It turns out that the bound tightens for increasing values of the average energy-per-bit-to-noise-ratio.

关键词： Cross layer design Spectral efficiency System performance Quality of service Receivers Transceivers systems simulation

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Robust Exudate Segmentation in Retinal Fundus Images using the combination of Efficient-Net and U-Net Model

Robust Exudate Segmentation in Retinal Fundus Images using t...

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international conference on communication systems and Network Technologies (CSNT)

作者： Debasish Deb R. Murugan Department of Electronics and Communication Engineering Biomedical Imaging Laboratory National Institute of Technology Silchar Silchar Assam

ISBN: (数字)9798331531935

ISBN: (纸本)9798331531942

Diabetic retinopathy (DR) is an eye disease. Lesions like exudates play a major role while grading DR. Hence, it’s important for accurate segmentation of exudate, as it plays a significant role in detecting and segmenting lesions. the exudates are smaller in shape and size, which are often irregular, and the contrast is also not high. therefore, it is challenging to identify the exudate’s actual location to get exudates in fundus images. Here in the paper, we present a novel deep neural network architecture that focuses a combination of EfficientNet and U-net architecture to accurately segmenting the exudate present in the fundus image. the proposed framework combines a U-shaped structure with residual connections to capture the subtle features of exudates. Here, in this paper, we proposed model has been utilized using Karas and Tensor-Flow tools, and it provides accurate results in identifying exudates, even small in size. this model has been trained and evaluated on the Indian Diabetic Retinopathy Image Dataset (IDRID). the experimental results show a novel precision (pre) value of 96.79%, Area Under Curve(AUC) value of 90.57%, a dice coefficient value of 96.87%, and an IOU value of 95.63%, this method demonstrates a significant improvement, outperforming the other states-of-art approaches in terms of accuracy and performance or efficiency.

关键词： Deep learning Image segmentation Diabetic retinopathy Accuracy Shape communication systems Artificial neural networks Retina Eye diseases Lesions

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A 5G-Enabled E-Infrastructure for Multipoint Videoconferencing in Higher Education Institutions of Burkina Faso 14th

A 5G-Enabled E-Infrastructure for Multipoint Videoconferenc...

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14th EAI international conference on Towards new e-Infrastructure and e-Services for Developing Countries, AFRICOMM 2022

作者： Sanou, Bernard Armel Konfé, Abdoul-Hadi Poda, Pasteur Université Nazi BONI Bobo-Dioulasso Burkina Faso

ISBN: (纸本)9783031348952

Many actors in public institutions of higher education in Burkina Faso and around the world have used videoconferencing applications during the Covid-19 pandemic to conduct courses, pedagogical activities, participate in conferences and many other scientific activities. However, in the context of Burkina Faso where most of the actors use mobile Internet, the comfort of use of the different videoconference applications is often not satisfactory due to connectivity issues. In this paper, we propose a cutting-edge e-infrastructure to improve the usability of multipoint videoconferencing while preserving the mobility of users. the proposed e-infrastructure consists of a logical extension of the National Research and Education Network (FasoREN) access network such that multipoint videoconference calls initiated within a 5G network are routed towards FasoREN. It can be applied to any netwotk of type FasoREN a priori and in particular to those whose actors are more inclined to use the mobile Internet. © 2023, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： 5G mobile communication systems

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Processing of Images Based on Machine Learning to Avoid Unauthorized Entry

Processing of Images Based on Machine Learning to Avoid Unau...

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international conference on Computational Intelligence and communication networks (CICN)

作者： Cesar Peña Ciro Rodriguez Israel Arellano Romero Facultad de Ingeniería Electrónica Universidad Nacional Federico Villarreal UNFV Lima Peru Department of Software Engineering Universidad Nacional Mayor de San Marcos UNMSM Lima Peru

ISBN: (纸本)9781665487726

the proposal of a facial recognition system to increase security, through facial recognition with multiple utilities such as facilitating the access of people with adequate protection measures in times of Covid-19, as well as security when seeking to hide their identity. the methodology considers the use of tools such as Python and OpenCV, as well as models such as Eigen Faces, Fisher Faces, and LBPH Faces, as units of analysis are considered photographs and portions of the video that capture facial expressions that then their patterns are trained with facial recognition algorithms. the results obtained show that the LBPH Faces obtained confidence values lower than 70, with a 95% certainty of recognition and a shorter recognition time, improving the accuracy of facial recognition, also with the increase of the data was achieved to improve the accuracy of recognition as well as improve confidence regarding the safety of people.

关键词： Image recognition Webcams Face recognition Streaming media Real-time systems Libraries Safety

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NN-Based Channel Equalization and Symbol Estimation for SC-FDMA with Channel Coding and Higher-Order Modulation

NN-Based Channel Equalization and Symbol Estimation for SC-F...

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international ITG conference on Source and Channel Coding (SCC)

作者： Oemer Karakas Pouya Fakharizadeh Marco Breiling Wolfgang Gerstacker Broadband and Broadcasting Department Fraunhofer IIS Erlangen Germany Institute for Digital Communication Friedrich-Alexander-Universität Erlangen Germany

ISBN: (数字)9798331522896

ISBN: (纸本)9798331522902

We design a fully connected neural network (FNN)-based scheme for joint channel equalization and symbol es-timation tasks in Single-Carrier Frequency Division Multiple Access (SC-FDMA) transmission over a dispersive block-fading channel. It is demonstrated that the proposed scheme is a reliable estimator in terms of soft estimation quality and it can be seamlessly combined with channel decoders that take a posteriori probability (APP) as input. the proposed scheme is evaluated against linear minimum mean-squared error (MMSE) equalization and demonstrates superior performance for BPSK, QAM16, and QAM64 modulations in terms of bit error rate (BER) and block error rate (BLER) for the 5G Clustered Delay Line (CDL) channel model.

关键词： 5G mobile communication Equalizers Bit error rate Modulation Channel estimation Symbols Estimation Artificial neural networks Channel models Signal to noise ratio

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AI-Driven Channel Estimation Using Geo-spatial Data With Modified DMRS

AI-Driven Channel Estimation Using Geo-spatial Data With Mod...

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international conference on communication systems and Network Technologies (CSNT)

作者： Ayush Kashyap Amit Munjal Amanpreet Kaur Dept. of Electronics and Communication TIET Patiala India

ISBN: (数字)9798331531935

ISBN: (纸本)9798331531942

Accurate channel estimation is very important in wireless communication systems and particularly with the increasing demand for enhanced connectivity in diversified environment (multiple). Traditional techniques that often rely on complex mathematical models, which struggles to balance for dynamic and noisy conditions, especially in multicarrier signal transmission/propagation. this paper will explore the application of a fully connected deep neural network (DNN) for better channel estimation across various scenarios, include urban areas like Tokyo and Bengaluru, as well as rural and semi-urban regions like Bastar and Patiala. MATLAB 2024b as the primary simulation tool, the proposed AI-based approach eliminates the need of complex and twisted channel modeling and adapt to real-world like conditions. Once the model is trained on specific scenario and environmental parameters, the DNN model will then demonstrates superior performance and accuracy compared to the traditional methods, even in challenging different propagation environments. By leveraging data-driven and insights, the AI model can achieve lower mean squared error (MSE) notably, which showcase its hidden potential to address the limitations of traditional techniques. this study will highlight efficiency and comparison of AI-driven channel estimation with traditional method in ensuring better communication across different environment scenarios. Our findings will later be useful in easily integrating it into 5G and beyond, due to its effectiveness.

关键词： Wireless communication 6G mobile communication Adaptation models Accuracy Computational modeling Channel estimation Artificial neural networks Mathematical models Artificial intelligence MATLAB

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Evaluation for Elevation Angle-Dependent Beam Size in NR NTN systems

Evaluation for Elevation Angle-Dependent Beam Size in NR NTN...

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international conference on Information and communication Technology Convergence (ICTC)

作者： Sangmin Han Wonjae Shin Jae-Hyun Kim Department of Artificial Intelligence Convergence Network Ajou University Suwon Republic of Korea School of Electrical Engineering Korea University Seoul Republic of Korea Department of Electrical and Computer Engineering Ajou University Suwon Republic of Korea

Appropriate beam design plays a vital role in satellite-based Non-Terrestrial networks (NTN) towards beyond 5G. In this paper, we propose an evaluation for elevation angle-based major-semi axis beam radius. To deal with this, we calculate beam major semi-axis radius with elevation angle and differential delay in NTN, based on 3rd Generation Partnership Project (3GPP) New Radio (NR) standards. Using the evaluation method, within NR standards, the differential delay-based beam major semi-axis radius can be independent of the elevation angle in some elevation angle intervals. Furthermore, we compare the differential delay-based beam results with the 3dB beamwidth results. the comparison shows that the differential delay-based beam major semi-axis radius can be more critical according to the preamble structure, subcarrier spacing, and elevation angle.

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AI Virtual Assistant for Online Laboratory Experiments Based on Multi-threshold Technique and Genetic Algorithm for Analyzing the Student's Mouse Interaction Activities

AI Virtual Assistant for Online Laboratory Experiments Based...

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international conference on Computational Intelligence and communication networks (CICN)

作者： Mahmoud M. Elmesalawy Ahmed M. Abd El–Haleem Alaa Hamdy Electronics and Communications Engineering Department Faculty of Engineering Helwan University Cairo Egypt Faculty of Computer Science Misr International University Cairo Egypt

ISBN: (纸本)9781665487726

there is a great interest in online learning systems, especially due to COVID-19 pandemic. However, there are a lot of limitations and challenges of online laboratory learning systems. this paper presents an efficient technique that provides an intelligent virtual tutor for online laboratory environment, as in engineering and science sectors. Based on the analysis of the student's mouse activities, the AI virtual Assistant or virtual tutor will automatically estimate the difficulties that the student stuck during conducting the steps of lab's experiment. Hence, the virtual tutor can assist the student, accordingly. the technique is based on multi-threshold that are used to discriminate different levels of difficulties. the values of these thresholds are estimated and optimized via the genetic algorithm. the experimental results show that discrimination between different student behaviors can be achieved accurately and efficiently.

关键词： Learning systems Pandemics Virtual assistants Laboratories Estimation Evolutionary computation Feature extraction

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