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共 5064 条记录，以下是111-120 订阅

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Enhancing Lymph Node Classification in Rectal Cancer MRI Images Through a Multi-Model Approach

Enhancing Lymph Node Classification in Rectal Cancer MRI Ima...

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2024 IEEE International Conferences of AI, science, eng.neering, and Technology, AIxSET 2024

作者： Gupta, Rishit Iwahori, Yuji Funahashi, Kenji Bhuyan, M.K. Bhatt, Manish Kijsirikul, Boonserm Wang, Aili Ouchi, Akira Shimizu, Yasuhiro Indian Institute of Technology Guwahati Dept. of Electronics & Electrical Eng. Assam Guwahati India Chubu University Dept. of Computer Science Kasugai Japan Nagoya Institute of Technology Dept. of Computer Science Nagoya Japan Chulalongkorn University Dept. of Computer Engineering Bangkok Thailand Harbin University of Science and Technology Higher Educational Key Laboratory Harbin China Aichi Cancer Center Hospital Dept. of Gastroenterological Surgery Nagoya Japan

ISBN: (纸本)9798350390995

Rectal cancer remains to be a major issue worldwide, necessitating accurate and precise methods for proper classification of lymph nodes in MRI scan images to guide treatment decisions. The use of deep learning based techniques can help with the task of classification. This research focuses on enhancing the process of lymph node classification in rectal cancer MRI images by using a multi-model approach. Firstly, we explore the use of diffusion models in data augmentation, to produce synthetic lymph node images to counter the issue of limited dataset size. Secondly, Real-ESRGAN and Swin2SR super-resolution techniques are examined for their ability to improve image quality and hence enhance the accuracy of lymph node classifications. Lastly, ConvNeXt is employed as an advanced technique used to improve overall performance at classifying lymph nodes for rectal cancer. Through a series of detailed experiments on the dataset consisting of T2-Weighted Axial MRI scans from 54 patients, we demonstrate the effectiveness of our approach in classification of lymph nodes. The metrics like accuracy and precision exhibit significant improvements, highlighting the superiority of our multi-model approach. © 2024 IEEE.

关键词： Magnetic resonance imaging

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Robust Detection in Power Systems: Iterative Reinforcement Learning Based Adversarial Training 50

Robust Detection in Power Systems: Iterative Reinforcement L...

引用

50th Annual Conference of the IEEE Industrial elec.ronics Society, IECON 2024

作者： Paudel, Bipin Amariucai, George Zare, Alireza Shadmand, Mohammad Dept. of Computer Science Kansas State University ManhattanKS United States Dept. of Electr. and Comp. Eng. University of Illinois at Chicago ChicagoIL United States

ISBN: (纸本)9781665464543

Stealthy cyberattacks pose a significant threat to modern power systems by exploiting advanced techniques to manipulate system behavior while avoiding detection by traditional security measures. In this study, we focus on the impact of Deep Reinforcement Learning (DRL) based attackers on a sample microgrid and develop robust detectors to mitigate these threats. Leveraging an iterative training process, we enhance the capabilities of successive attackers and detectors, resulting in improved system security. Our experiments demonstrate that DRL-based attackers can effectively disrupt system operations, highlighting the importance of robust detection mechanisms. Subsequently, we develop robust detection mechanisms, making new attacker attempts unsuccessful. We show that detectors developed through our mechanism are more effective in mitigating system impact and quickly identifying anomalies. © 2024 IEEE.

关键词： Deep reinforcement learning

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Design of 2 × 2 MIMO Antenna for Sub-5G IoT Applications 10

Design of 2 × 2 MIMO Antenna for Sub-5G IoT Applications

引用

10th International Conference on Emerging Trends in eng.neering and Technology - Signal and Information Processing, ICETET-SIP-22 2022

作者： Alblooshi, Aamna Ali Yousaf, Jawad Abu Dhabi University Dept. of Elec Computer and Biomedical Eng. Abu Dhabi United Arab Emirates

ISBN: (纸本)9781665467414

This paper presents a 2 × 2 multiple-input multiple-output (MIMO) antenna designed as a potential candidate for sub-fifth generation (5G) network and 5G enabled internet of things (IoT) devices. The proposed design consists of two rectangular microstrip antennas operate in sub-5G dedicated bands and resonates at 2.6 GHz and 3.5 GHz respectively. Microstrip structure are etched on Taconic RF-35A2 substrate. MIMO antenna is designed and numerically analyzed using finite difference time domain method in CST MWS. The realized MIMO antenna structure is simulated in the frequency range of 2-4 GHz. Very good isolation is observed with greater than -30dB S21 in the whole analyzed frequency range. The maximum observed directivity of proposed structure at 3.5 GHz is 7.05 dBi with 3 dB beam width of around 90 degree. © 2022 IEEE.

关键词： fifth Generation Internet of Things Microstrip antenna MIMO antenna

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Improved Survival Probability for Coded Compressed Sensing in Unsourced Random Access

Improved Survival Probability for Coded Compressed Sensing i...

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International Symposium on Information Theory and Its Applications, ISITA

作者： Shan Lu Hiroshi Kamabe Dept. of Elec. Elec. and Computer Eng. Gifu University Gifu Japan

ISBN: (数字)9784885523410

ISBN: (纸本)9781665499071

In the unsourced random access (U-RA), many users with only a certain number are active in the same time slot. Each user employs the same codebook, and the task of the decoder is to recover a list of transmitted messages regardless of the user’s identity. The compressed sensing(CS) approach is straightforward but with high computational complexity in addressing the U-RA problem. A concatenated coding approach called a coded compressed sensing scheme is a low complexity method that splits each message into L sub-slots. First, an outer tree code connects the messages of all sub-slots. Then, the active users send a column from an inner CS matrix in each sub-slot. However, there is a limitation that the inner CS decoding only decodes the support of a sparse vector, which leads to each user at the same sub-slot must send a different message, and the maximum tolerable active user number is *** consider the inner CS decoding scheme that first decodes the amplitudes of a sparse vector and quantity them to show the number of active users choosing the same columns. Therefore, the constraint of each user sending different messages at the same sub-slot vanishes, and the maximum tolerable number of active users increases. We first show the maximum tolerable active user number with various codeleng.hs. Next, we improve the survival probabilities’ upper and lower bounds of the outer tree encoder.

关键词： Codes Vectors Encoding Decoding Sensors Sparse matrices Computational complexity

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Household Energy Consumption Prediction: A Deep Neuroevolution Approach 23

Household Energy Consumption Prediction: A Deep Neuroevoluti...

引用

3rd International Conference on Artificial Intelligence, Automation and Algorithms, AI2A 2023

作者： Soudaei, Alexander Zhang, Jianhua Elmi, Mohamed Tsechoev, Mikael Khan, Zishan Osman, Ahmed Dept. of Computer Science Oslo Metropolitan University Oslo Norway Dept. of Mechanical Electronic and Chemical Eng. Oslo Metropolitan University Oslo Norway

ISBN: (纸本)9798400707605

Accurate energy consumption prediction can provide insights to make better informed decisions on energy purchase and generation. It also can prevent overloading and make it possible to store energy more efficiently. In this work, we propose a new deep learning model to predict the household energy consumption. In the new model, we employ differential evolution (DE) algorithm to automatically determine the optimal architecture of the deep neural network. The energy prediction results are presented and analyzed to show the effectiveness of the deep neuroevolution model constructed. © 2023 Owner/Author.

关键词： Evolutionary algorithms

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Low-Cost Permittivity Determination of Liquid Materials Using Transmission-Only Measurements 22

Low-Cost Permittivity Determination of Liquid Materials Usin...

引用

22nd IEEE Mediterranean Microwave Symposium, MMS 2023

作者： Hasar, Ugur Cem Nayyeri, Vahid Ramahi, Omar Mustafa Gaziantep University Electrical and Electronics Eng. Dept. Gaziantep Turkey School of Advanced Technologies Iran University of Science and Technology Tehran Iran University of Waterloo Electrical and Computer Eng. Dept. Waterloo Canada

ISBN: (纸本)9798350308471

A low-cost microwave non-resonant measurement setup is proposed for permittivity (ϵr) determination of liquid samples with substantial leng.hs using transmission-only amplitude measurements. The proposed method does not require any dispersion model or applies machine-learning method which requires a training process for each new material (time-consuming and complex). A graphical method is applied to monitor the possibility of extracting ϵr. It is shown that it is possible to extract ϵr using samples with different leng.hs. A low-cost measurement setup, implemented by an SDR unit, with coaxial cables, and waveguide sections, was constructed to validate our method. Post-processing techniques were applied to remove redundant ripples in measurement due to a simple normalization procedure. © 2023 IEEE.

关键词： Permittivity

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Bridging the Capacity Gap for Online Knowledge Distillation 6

Bridging the Capacity Gap for Online Knowledge Distillation

引用

6th IEEE International Conference on Multimedia Information Processing and Retrieval, MIPR 2023

作者： Wang, Maorong Yu, Hao Xiao, Ling Yamasaki, Toshihiko The University of Tokyo Dept. Inf. Commun. Eng. Tokyo Japan Boston University Dept. of Computer Science Boston United States

ISBN: (纸本)9798350307818

Online knowledge distillation (KD) has drawn increasing attention in recent years. However, little attention has been paid to the capacity gap that exists between the models in the online KD paradigm. In this work, we investigate the impact of the capacity gap and experimentally verified that a large capacity gap can have a detrimental effect on performance. Moreover, to address this issue, we propose Auxiliary Branch assisted Mutual Learning (ABML), which leverages auxiliary branches to mitigate performance deterioration caused by the capacity gap. Experimental results show that our ABML can significantly improve the performance of online KD even when a capacity gap is present. Our code is available at https://***/maorongwang/ABML. © 2023 IEEE.

关键词： Distillation

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Recognition of Handwritten Punjabi Characters Using Machine Learning Techniques 1

Recognition of Handwritten Punjabi Characters Using Machine ...

引用

1st IEEE International Conference on Advances in Computing, Communication and Networking, ICAC2N 2024

作者： Kaushik, P. Kaushik, Manas Manglik Chauhan, Yuvraj Singh Kumar, Narendra Kumar, Ashwani Rathore, Rachna Chandigarh University Dept. of CSE Chandigarh India Manipal University Dept. of Mechanical and Industrial Eng Karnataka India Chandigarh University Dept. of Computer Science Engineering Chandigarh India Usha Martin University Dept. of Computing and IT Jharkhand India Mangalayatan University Dept. of Computer Eng. and Applications Aligarh India Shrimant Madhav Rao University Dept. of Mathematics Gwalior India

ISBN: (纸本)9798350356816

Detecting handwritten Punjabi alphabets (PbAD) presents significant challeng.s for text detection systems due to the similarity among many characters and their complex curves and edges. Existing automatic detection systems often struggle to deliver high accuracy with real-world data. In this study, we propose an approach for PbAD that synthesizes various techniques reviewed from existing literature to optimize accuracy. Our methodology involves evaluating and combining multiple classification and feature extraction techniques, as identified through an extensive literature review. Unlike many studies that rely on manually created datasets, our approach will leverage both available online datasets and those developed in previous research. Previous research has reported accuracies ranging from 80% to 99%, and our goal is to advance these results by integrating and refining the best practices from the literature. © 2024 IEEE.

关键词： Adversarial machine learning

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Enhancing OCR Accuracy Using Convolutional Neural Networks: A Study on Spelling Correction in Handwritten Numerals 1

Enhancing OCR Accuracy Using Convolutional Neural Networks: ...

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1st IEEE International Conference on Advances in Computing, Communication and Networking, ICAC2N 2024

作者： Kaushik, Priyanka Dewal, Inder Singh Singh Rathore, Sajjan Singh, Vinay Kumar, Sani Bhavani, P.M. Sindhu Chandigarh University Dept. of Computer Science Engineering Chandigarh India Madhav University Dept. of Humanities & S.Science Pindwara India Usha Martin University Dept. of Com. & Information Technology Jharkhand India Mangalayatan University Dept. of Computer Eng. & Applications Aligarh India Meenakshi A.H.Edu. & Research Dept. of Humanities & Science Chennai India

ISBN: (纸本)9798350356816

Artificial neural networks have transformed machine learning and had a significant impact on a wide range of industries, including robotics, deep learning, healthcare, sports, and surveillance. Convolutional Neural Networks (CNNs) are unique among these developments because they combine cutting-edge deep learning methods with conventional Artificial Neural Networks (ANNs). CNNs are essential for tasks like data analysis, text classification, speech and face recognition, and pattern recognition in a variety of fields. In order to improve spelling correction, this article uses a dataset that was upgraded from the National Institute of Standards & Technology (NIST) and includes 70,000 grayscale pictures of handwritten numbers. © 2024 IEEE.

关键词： Convolutional neural networks

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WIP: From Passive to Passionate: Using Genuine Projects to Motivate Students 54

WIP: From Passive to Passionate: Using Genuine Projects to M...

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54th IEEE Frontiers in Education Conference, FIE 2024

作者： McGarry, Michael P. Seeling, Patrick University of Texas at El Paso Dept. of Electrical and Computer Eng. El PasoTX79968 United States Central Michigan University Department of Computer Science Mount PleasantMI48823 United States

ISBN: (纸本)9798350351507

This innovative practice WIP paper presents our work to increase student motivation and eng.gement using real-world projects. Specifically, we assigned final projects to students that came from a genuine need from our research program on campus. The team projects were assigned in a networking course offered to undergraduate and graduate students. Anecdotally, the students seemed more motivated to complete the projects because they knew the requested designs were novel and provided local utility. Student performance toward project completion was, anecdotally, exceptional compared to traditional projects. We surveyed students to assess their perceptions of their mo-tivation and subsequent eng.gement. The survey results suggest that the students perceived what we also perceived: students had more motivation from these types of projects than the typical contrived recycled projects typically assigned. In this paper, we provide the details behind these projects, how we managed the students to complete them, how we attempted to make the process mirror a commercial environment, and analyze the results of the student survey data. We also outline our experimental design to be executed in future course offerings to better understand how student motivation and eng.gement is affected by these types of projects in comparison with typical contrived recycled projects. Lastly, we outline how we intend to scale up across campuses and to create an experiential learning environment outside of formal course work. © 2024 IEEE.

关键词： Students

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