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4th international conference on Artificial Intelligence and Electromechanical automation, AIEA 2023

作者： Yang, Juan Huang, Zhiyi Wang, Yao Yang, Yin School of Computer Science and Information Engineering Hefei University of Technology Anhui Hefei230601 China

ISBN: (纸本)9781510666412

Effective image semantic segmentation is an important task. In recent years, deep convolutional neural networks have played a major role in improving the effectiveness of semantic segmentation. However, previous works capture local contexts by multi-scale feature fusion which ignore the global dependencies. Moreover, as the layers deepen, the loss of feature is inevitable. Multy-Scale Dual Attention Refine Network (MSDARNet) is proposed. Specifically, we firstly append two types of attention modules on top of dilated FCN, which model the global semantic interdependencies in spatial and channel dimensions respectively. Secondly, multi-scale feature fusion is added to extract local dependencies in the above attention module. We conduct extensive experiments to validate the effectiveness of our network on three challenging semantic segmentation datasets and obtain great improvements. In particular, our MSDARNet attains mIoU accurary of 50.3% on NYUDv2, 71.1% on Person-Part. © 2023 SPIE.

关键词： Semantic Segmentation

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Exploring the Impact of Image Quality on Convolutional Neural Networks: A Study on Noise, Blur, and Contrast 7

Exploring the Impact of Image Quality on Convolutional Neura...

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7th IEEE international conference of computer science and Information technology, ICOSNIKOM 2023

作者： Ghoben, Marwa Kareem Muhammed, Lamia Abed Noor College of Computer Science IT University of Al-Qadisiyah Department of Computer Science Al-Diwaniyah Iraq

ISBN: (纸本)9798350360752

Convolutional neural networks (CNNs) have recently revolutionized several computer vision tasks, including object detection and image categorization. The secret to their astounding success is their capacity to automatically recognize and extract features from intricate data representations. However, the caliber of the input images significantly affects how well CNNs work. The critical importance of image quality in the context of CNNs is explored in depth in this study, emphasizing how blur, noise, and contrast affect the overall performance of CNNs. The classification performance of degraded images is also demonstrated by this study to be influenced by the picture quality of training data for a classification network. © 2023 IEEE.

关键词： Convolutional neural networks

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Development of Hydroponic IoT-based Monitoring System and Automatic Nutrition Control using KNN

Development of Hydroponic IoT-based Monitoring System and Au...

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2023 international conference on computer science, Information technology and Engineering, ICCoSITE 2023

作者： Albert, Matthew Christopher Hans, Hubertus Karteja, Herlangga Widianto, Mochammad Haldi School of Computer Science Bina Nusantara University Computer Science Department Bandung Campus Jakarta11480 Indonesia

ISBN: (纸本)9798350320954

Hydroponic farming is limited by inefficient monitoring and maintenance, which can affect plant growth and yield. This paper proposes using IoT technology, specifically a combination of STM32 microcontroller and sensors with 4G connection to cloud, to automate the monitoring and maintenance of hydroponic plants. The system monitors water and air temperature, pH, and TDS, and controls the hydroponics by adding nutrient in the form of AB mix. An automatic decision maker is built using KNN with an accuracy of 92.86% based on Euclidean distance algorithm. This technology could optimize the growth of hydroponic plants, as it provides continuous monitoring and maintenance. © 2023 IEEE.

关键词： Hydroponics

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Government Infra Assessment System

Government Infra Assessment System

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2023 IEEE international Students' conference on Electrical, Electronics and computer science, SCEECS 2023

作者： Thakur, Reena Gadbail, Abhijeet Gomkale, Akash Jambhulkar, Tanuksha Bhujade, Harshal Charpe, Aditya Jhulelal Institute of Technology Department of Computer Science and Engineering Nagpur India

ISBN: (纸本)9798350398748

Without involving any other parties and abstaining from any other compromised operations across India, Government Infra Assessment System would provide all the necessary information regarding Government Infrastructure to the Government itself. Government employees will not only benefit from time savings, but also from the ability to view the database whenever they want without waiting. © 2023 IEEE.

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Enhancing Shift-Invariance for Accurate Brain MRI Skull-Stripping using Adaptive Polyphase Pooling in Modified U-Net 2

Enhancing Shift-Invariance for Accurate Brain MRI Skull-Stri...

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2nd international conference on automation, Computing and Renewable Systems, ICACRS 2023

作者： Padalia, Adish Shah, Tanish Pujari, Pratik Karande, Aarti Department of Information Technology Sardar Patel Institute of Technology Mumbai India Department of Computer Engineering Sardar Patel Institute of Technology Mumbai India Department of Computer Science and Engineering Sardar Patel Insitute of Technology Mumbai India

ISBN: (纸本)9798350340235

Image segmentation is an essential aspect of image processing, where regions of interest (ROI) are identified by employing feature descriptors like edges, color, and texture. Medical images often contain unwanted segments, necessitating preprocessing steps to extract valuable information. In the realm of medical image segmentation, skull-stripping in 3D volumetric Brain MRI images holds significant importance. This study delves into supervised learning techniques to extract crucial brain features from non-brain tissues. The approach involves a modified U-net that operates on 2D slices of the brain MRI, yielding a skull-stripped image with superior accuracy compared to existing methods. The architecture incorporates Adaptive Polyphase Pooling layers, enhancing the architecture’s robustness and the model’s generalization. These Adaptive Polyphase Pooling layers ensure shift-invariance in the predicted output, maintaining consistency even if the single view of the Brain MRI shifts along the two axes in the plane. © 2023 IEEE.

关键词： Adaptive Polyphase Pooling Brain Magnetic Resonance Imaging skull-stripping Supervised-learning U-net

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IoT-based Smart Home automation Systems for Energy Conservation 7

IoT-based Smart Home Automation Systems for Energy Conservat...

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7th international conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2023

作者： Sudhakar, K.N. Devadarshini, P.T. Ramu, K.N. Deshveer Suryanarayana, N.V.S. Kanakala, V Raviteja Cmr Institute of Technology Department of Ise Karnataka Bengaluru560037 India Easwari Engineering College Department of Artificial Intelligence and Data Science Tamil Nadu Chennai India S.A. Engineering College Department of Mechanical Engineering Tamil Nadu Thiruverkadu India Ganga Institute of Technology and Management Department of Electrical Engineering Haryana Kablana India Central Tribal University of Andhra Pradesh Administrative Officer Vizianagaram India Koneru Lakshmaiah Education Foundation Department of Computer Science and Engineering Andhra Pradesh Vaddeswaram India

ISBN: (纸本)9798350341485

This research study explores the numerous components of smart home automation systems, including actuators, sensors, and controllers, and the integration of these components with Internet of Things (IoT) technology. To demonstrate the system's ability to reduce energy consumption, this study involves an experimental analysis of a prototype system. In order to scientifically evaluate the system's performance, the test data must be statistically analysed. The results of this research study have the potential to contribute towards the enhancement of energy efficiency and sustainability of the proposed system by offering insights for the construction of sustainable residential settings. This study investigates the effects of the residential environments. The use of complex and innovative systems has the potential to significantly improve the efforts to save energy and promote a sustainable future. © 2023 IEEE.

关键词： Actuators

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Anti-jamming Research of UAV Communication Based on Link-16 Datalink 6

Anti-jamming Research of UAV Communication Based on Link-16 ...

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6th international conference on computer Network, Electronic and automation, ICCNEA 2023

作者： Liu, Lijun Fu, Yanfang Li, Qinjie Lu, Ying Cao, Zijian Chen, Yifan Xi'an Technological University School of Computer Science and Engineering Shaanxi Xi'an710021 China

ISBN: (纸本)9798350305388

In the context of Link-16 datalink UAV operation, aiming at the communication interference problem in UAV combat, taking the suppressive interference model as an example, the three-layer modeling model of UAV communication jammer based on Link-16, Link11 and Link-22 datalink is constructed on the OPNET software simulation platform. The model details the parameter meanings of each layer of the model, and uses suitable simulation scenarios for experimental verification. Through the comparative analysis of the experimental results, it is proved that Link-16 has strong anti-interference. The study of anti-jamming of Link-16 datalink has been a popular issue, and the experimental comparative study in this paper can provide a good understanding of the relevant communication capabilities of this datalink. Link-16's stronger anti-jamming study lays the groundwork for subsequent jamming studies. Its unique immunity to jamming aids militarized warfare. © 2023 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Customized Touch UI Development for E-Cockpit in Automobile 3

Customized Touch UI Development for E-Cockpit in Automobile

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3rd international conference on Smart Technologies, Communication and Robotics, STCR 2023

作者： Sivaraj, D. Rathika, P.D. Jayasree, D. Dwarkesh Psg College of Technology Department of Electronics and Communication Engineering Coimbatore India Psg College of Technology Department of Robotics and Automation Engineering Coimbatore India Psg Polytechnic College Department of Electronics and Communication Engineering Coimbatore India Psg College of Technology Department of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350370867

In recent times, the automotive industry has made significant steps towards digitization by focusing on electronic cockpits (E-Cockpits) to enhance the driving experience, comfort and safety. The incorporation of Touch-Based User Interface (UI) technologies has played a crucial role in revolutionizing Driver-Vehicle interaction [10]. The project of E-Cockpit represents a concept that consolidates various internal car systems onto one unified digital platform, enabling seamless control and access to essential infotainment, safety features, and connectivity services [14]. For the realization of the complete potential of an E-Cockpit, it is important to develop an innovative and User-Friendly touch UI as this directly influences both user experience and safety concerns. © 2023 IEEE.

关键词： User interfaces

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Hybrid cloud storage system with enhanced multilayer cryptosystem for secure deduplication in cloud

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international Journal of Intelligent Networks 2023年第1期4卷 301-309页

作者： Mageshkumar, Nagappan Swapna, J. Pandiaraj, A. Rajakumar, R. Krichen, Moez Ravi, Vinayakumar Department of Computer Science and Technology Madanapalle Institute of Technology and Science Madanapalle India Department of Computer Science & Engineering Veltech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Chennai India Department of Computing Technology SRM Institute of Science and Technology Kattankulathur chennai India Al-Baha University Alaqiq 65779-7738 Saudi Arabia ReDCAD Laboratory University of Sfax Sfax3038 Tunisia Center for Artificial Intelligence Prince Mohammad Bin Fahd University Khobar34754 Saudi Arabia Centre for Automation School of Computer Science and Engineering Vellore Institute of Technology Chennai Campus Chennai India

Data deduplication is a crucial technique in the field of data compression that aims to eliminate redundant copies of recurring data. This technique has gained significant popularity in the realm of cloud storage due to its ability to effectively reduce storage requirements and optimize bandwidth utilization. To ensure the safeguarding of sensitive data while simultaneously facilitating deduplication, researchers have put forth the concept of convergent encryption as a potential solution. This technique involves encrypting the data prior to its outsourcing, thereby enhancing the confidentiality of the information. In this work, an earnest endeavor is undertaken to formally tackle the issue of authorized data deduplication, with the aim of enhancing data security. Our approach combines the Diffie-Hellman algorithm and symmetrical external decision to protect and popularize information, ensuring end-to-end encryption to encourage user adoption of cloud storage. The proposed model employs block-level deduplication and guarantees the randomness of ciphertexts by generating encryption keys using the Diffie-Hellman algorithm. This method effectively counters both internal and external brute-force attacks, enhancing data security while reducing computational costs. An extensive experimentation is carried out to demonstrate that our approach is particularly beneficial in scenarios with multiple privilege sets. Overall, the proposed model offers an elaborate framework that maintains data privacy and strengthens security measures, contributing to a more efficient and secure cloud-based document search. © 2023 The Author(s)

关键词： Cryptography

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Automatic Speech Recognition Based on Conformer with Convolution Enhanced Channel Attention Block 4

Automatic Speech Recognition Based on Conformer with Convolu...

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4th international conference on computer Vision and Data Mining, ICCVDM 2023

作者： Sun, Yiming Li, Bingyi Liu, Wei Changchun University of Science and Technology Changchun130000 China

ISBN: (纸本)9781510674448

Conformer has demonstrated outstanding performance in the field of speech recognition, representing a highly effective improvement over the Transformer model. Subsequently, research on the integration of encoder blocks emerged, such as Blockformer. In this paper, we investigated the integration method of Conformer's encoder blocks and proposed a more efficient approach for leveraging information from multiple blocks, which we refer to as Convolution-Enhanced Channel Attention Block Integration. We achieved a Character Error Rate (CER) of 4.58% on the Aishell-1 dataset. © 2024 SPIE.

关键词： Convolution

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