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8th Annual international conference on Information Management and Big Data, SIMBig 2021

8th Annual International Conference on Information Managemen...

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8th Annual international conference on Information Management and Big Data, SIMBig 2021

ISBN: (纸本)9783031044465

The proceedings contain 27 papers. The special focus in this conference is on Information Management and Big Data. The topics include: CoffeeSE: Interpretable Transfer Learning Method for Estimating the Severity of Coffee Rust;plant Disease Classification and Severity Estimation: A Comparative Study of Multitask Convolutional Neural networks and First Order Optimizers;auditing algorithms: Determining Ethical Parameters of Algorithmic Decision-Making Systems in Healthcare;Calibration of Traffic Simulations Using Simulated Annealing and GPS Navigation Records;a Data-Driven Score Model to Assess Online News Articles in Event-Based Surveillance System;Model Comparison for the Classification of Comments Containing Suicidal Traits from Reddit via NLP and Supervised Learning;automatic Detection of Deaths from Social networking Sites;deep Learning vs Compression-Based vs Traditional Machine Learning Classifiers to Detect Hadith Authenticity;automatic Detection of Levels of Intimate Partner Violence Against Women with Natural Language Processing Using Machine Learning and Deep Learning Techniques;Quality Model for Educational Mobile Apps Based on SQuaRE and AHP;Enterprise Architecture Based on TOGAF for the Adaptation of Educational Institutions to e-Learning Using the DLPCA Methodology and Google Classroom;clustering Analysis for Traffic Jam Detection for Intelligent Transportation System;government Public Services Presence Index Based on Open Data;investigating Generative Neural-network Models for Building Pest Insect Detectors in Sticky Trap Images for the Peruvian Horticulture;Crack Detection in Oil Paintings Using Morphological Filters and K-SVD Algorithm;AmLDA: A Non-VAE Neural Topic Model;classical Machine Learning vs Deep Learning for Detecting Cyber-Violence in Social Media;multiphase Model Based on K-means and Ant Colony Optimization to Solve the Capacitated Vehicle Routing Problem with Time Windows;automatic Data Imputation in Time Series Processing Using Neural N

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Research and analysis of pruning algorithm

Research and analysis of pruning algorithm

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2022 international conference on algorithms, Microchips and network Applications

作者： Jin, Xin Ma, Xuanmin Tao, Li College of Communication and Information Technology Nanjing University of Posts and Telecommunications Nanjing210023 China Leicester International Institute Dalian University of Technology Panjin124221 China College of Computer Science Sichuan University Chengdu610207 China

ISBN: (纸本)9781510653290

In recent years, thanks to the development of GPU (Graphic Processing Unit) computing power, deep neural network (DNN) has drawn extensive attention from academia and industry and has been widely used in various fields of artificial intelligence. However, the mainstream deep learning models have some problems such as large storage space consumption and high computational complexity, which makes it difficult for the deep neural network model to be deployed to mobile devices with limited computing resources or applications with strict delay requirements. Therefore, on the premise of minimizing the loss of model accuracy, the algorithm researches of deep neural network compression and acceleration which can lighten the model has been carried out. In recent years, model compression methods such as pruning, quantification and knowledge distillation have emerged. This paper focuses on neural network pruning algorithm. Firstly, this paper expounds the basic methods and classification of neural network pruning algorithms. Then according to the classification of pruning granularity, a more detailed classification, analysis and comparison of specific models are carried out from the algorithm level. Then based on cifar-10 data set, validity tests of some neural network pruning algorithms and contrastive analyses of the experimental data from different models such as the parameters are carried out. Finally, in combination of the recent results of neural network pruning algorithm, we put forward research dilemmas and problems to be solved. Then the future research trends and methods of neural network pruning algorithm are prospected. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Deep neural networks

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9th EAI international conference on Advancement of Science and technology, ICAST 2021

9th EAI International Conference on Advancement of Science a...

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9th EAI international conference on Advancement of Science and technology, ICAST 2021

ISBN: (纸本)9783030937089

The proceedings contain 80 papers. The special focus in this conference is on Advancement of Science and technology. The topics include: Performance Analysis of Hybrid Beamforming Techniques in Large MU MIMO Systems;Narrow-Linewidth Compound Ring Fiber Laser Using HBF as a Feedback for Sensing and Communication Application;Design and Performance Analysis of 125 MW Floating Photovoltaic Power Plant in Ethiopia: Metema vs Lake Tana;Efficiency Analysis of a Solar Photovoltaic DC and Existing AC Distribution System for Bahirdar University Data Center;Design of Genetic Algorithm Based Robust LQG Controller for Active Magnetic Bearing System;Pitch Angle Control for Optimal Power of Horizontal Axis Variable Speed Wind Turbines Using Fuzzy Tuned PID Controller;A Concise Evaluation of Auto-tuned PID and Fuzzy Logic Controllers for Speed Control of a DC-Motor;Genetic Algorithm Tuned Super Twisted Sliding Mode Controller (STSMC) for Self-balancing Control of a Two-Wheel Electric Scooter;artificial Neural network Based Rotor Flux Estimation and Fuzzy-Logic Sensorless Speed Control of an Induction Motor;effect of Toasting and Natural Fermentation on the Phytochemical and Functional Properties of Oats Grown in Ethiopia;Performance Analysis of Microstrip Antenna with Semi-eliptical Slotted Patch and Defected Ground Structure at 28 GHz for 5G Communication Systems;Data-Driven Based Optimal Placement and Performance Evaluation of FD-MIMO for Enhanced 4G Mobile networks Under Realistic Environment;optimization of Dualband Microstrip mm-Wave Antenna with Improved Directivity for Mobile Application Using Genetic Algorithm;n-Neuron Simulation Using Multiprocessor Cluster;A SVM Based Model for COVID Detection Using CXR Image;Simultaneous Indoor Localization Based on Wi-Fi RSS Fingerprints.

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9th EAI international conference on Advancement of Science and technology, ICAST 2021

9th EAI International Conference on Advancement of Science a...

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9th EAI international conference on Advancement of Science and technology, ICAST 2021

ISBN: (纸本)9783030937119

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21st international conference on Next Generation Teletraffic and Wired/Wireless Advanced networks and Systems, NEW2AN 2021 and 14th conference on Internet of Things and Smart Spaces, ruSMART 2021

21st International Conference on Next Generation Teletraffic...

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21st international conference on Next Generation Teletraffic and Wired/Wireless Advanced networks and Systems, NEW2AN 2021 and 14th conference on Internet of Things and Smart Spaces, ruSMART 2021

ISBN: (纸本)9783030977764

The proceedings contain 41 papers. The special focus in this conference is on Next Generation Teletraffic and Wired/Wireless Advanced networks and Systems. The topics include: The Challenges with Internet of Things Security for Business;Using a Machine Learning Model for Malicious URL Type Detection;network Slice Degradation Probability as a Metric for Defining Slice Performance Isolation;Geometrical Approach to the Plane Tessellation in the IEEE 802.11 networks Channel Planning;Heuristic Design Algorithm for Scheduling of URLLC and eMBB Traffics in 5G Cellular networks;Application of Neural network to Demodulate SEFDM Signals;the Effect of Error Burst When Using a Decision Feedback Algorithm for Receiving Non-orthogonal Multi-frequency Signals;instantaneous Interference Evaluation Model for Smart Antennas in 5G Ultra-Dense networks;selecting a Receiver for Wideband Spectrum Sensing in Cognitive Radio Systems Based on an Assessment of the Signal Environment Complexity;smart Contract Enabled Decentralized Reputation System for E-Commerce Reviews;Analysis of Nonlinear Distortions of FTN Signals Transmitted Through TWT Amplifier;Application of Wavelet Transform for ECG Processing;investigation Methods of Dehydrated Protein Films for Biomolecular Electronics;Predicting Energy Consumption for UAV-Enabled MEC Using Machine Learning Algorithm;Deep Learning Approach for Predicting Energy Consumption of Drones Based on MEC;Simulation and Experimental Study of Multi-source Application Layer ARQ for FANET;fiber-Optic Recirculating Memory Loop for Wideband Microwave Signal;on Smart Greenhouse Issues;structural Shifts on Derivatives Markets at the Time of Increasing Digitalization and Post-pandemic Transformation of the Market;specifics of Forming an Innovation Sector When Developing Industry 4.0 technology;preface.

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Music Generation with AI technology: Is It Possible? 5

Music Generation with AI technology: Is It Possible?

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5th IEEE international conference on Electronics technology, ICET 2022

作者： Tang, Haowen Gu, Yikun Yang, Xinyu BNU-HKBU United International Colloge Division of Science and Technology Zhuhai China

ISBN: (纸本)9781665485081

Music generation techniques have made tremendous progress in recent years. Through deep learning neural network frameworks, algorithms can generate music that rivals humans. However, current music generation models lack mainstream algorithms and specifications, including algorithm design criteria and model evaluation criteria, and exactly how to evaluate that music generated by a deep learning model is a good piece of music. In this case, we did a literature review for the three most common deep learning models currently used in music generation. These three models are Biaxial-LSTM, DeepJ and MuseGAN. We compared their application scenarios and model evaluation methods to provide a reference standard for subsequent researchers. © 2022 IEEE.

关键词： Music

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Target Detection method for Based on Deep Learning 14

Target Detection method for Based on Deep Learning

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14th international conference on Measuring technology and Mechatronics Automation, ICMTMA 2022

作者： Chai, Yuan Liu, Jing Li, Yang Department of Network Engineering TJ E-Sports School of Network Science Haikou University of Economics Hainan Haikou571132 China Research Center for Healthcare Data Science Zhejiang Lab Zhejiang Hangzhou310000 China Foreign Languages Department Oriential School of International Trade and Foreign Languages Haikou University of Economics Hainan Haikou571132 China

ISBN: (纸本)9781665499781

Target detection is an important method in the field of deep learning. In view of the low efficiency and low accuracy of traditional target detection methods, this paper mainly focuses on the analysis of two-stage detection algorithm Faster R-CNN and single-stage detection algorithm Yolo. Based on the Paddle Detection model library, the above algorithms are replicated. Detecting the same image, the advantages and disadvantages of these algorithms will be compared in accuracy and efficiency. Based on the analysis of anchor frame and real frame, it is found that network mismatch and overfitting lead to low detection accuracy and low efficiency. In order to solve the above problems, this paper proposes the method of connecting multiple mixed detectors in the existing detection network, which can not only improve the quality of samples, but also keep the diversity of samples. Experimental results show that compared with traditional target detection methods, the accuracy of the proposed method is about 10% higher. The proposed algorithm can solve the problem of network mismatch as well as reduce the overfitting problem, effectively improve the efficiency and accuracy of network detection, and better meet the requirements of high precision and fast identification. © 2022 IEEE

关键词： Efficiency

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Graph-based adaptive node enhancement for Alzheimer’s disease prediction 16

Graph-based adaptive node enhancement for Alzheimer’s disea...

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16th international conference on Digital Image Processing, ICDIP 2024

作者： Sun, Guangming Wang, Huabin Yuan, Wei Shang, Dongxu Wang, Zilin Anhui Provincial International Joint Research Center for Advanced Technology in Medical Imaging School of Computer Science and Technology Anhui University Hefei Anhui230601 China Stony Brook Institute Anhui University Anhui230601 China

ISBN: (数字)9781510682917

ISBN: (纸本)9781510682900

Currently, there are issues of sample imbalance and insufficient sample quantity in graph-based Alzheimer's disease prediction methods. This can lead to classifiers being biased towards the majority class samples and result in overfitting. To address this problem, a graph-based data augmentation node expansion algorithm is proposed. Firstly, graph representation learning is used to reduce the original feature vectors to a low-dimensional space. This message aggregation method ensures that the low-dimensional vectors contain the potential structural information of the data, preventing structural damage that may arise from direct expansion on the original data. Secondly, in the low-dimensional space, an adaptive-weight node expansion algorithm is employed to generate new nodes, overcoming the boundary fuzziness issue of traditional oversampling algorithms. This weight expansion algorithm adjusts the priority of each expansion node to control the generation position and quantity of new nodes. Finally, the expanded graph is fed into a Graph Neural network classifier for prediction. Quantitative experiments on the Tadpole dataset and NACC dataset demonstrate that the proposed graph-based data augmentation model achieves the highest accuracy. The average accuracy was 93.84% vs 92.8% on the Tadpole dataset and 90.11% vs.88.29% on the NACC dataset. In addition, additional ablation experiments have demonstrated the effectiveness of node expansion in graph structures. © 2024 SPIE.

关键词： Graph neural networks

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4th international conference on Soft Computing and its Engineering Applications, icSoftComp 2022

4th International Conference on Soft Computing and its Engin...

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4th international conference on Soft Computing and its Engineering Applications, icSoftComp 2022

ISBN: (纸本)9783031276088

The proceedings contain 36 papers. The special focus in this conference is on Soft Computing and its Engineering Applications. The topics include: Explainable AI for Predictive Analytics on Employee Attrition;graph Convolutional Neural networks for Nuclei Segmentation from Histopathology Images;Performance Analysis of Cache Memory in CPU;extraction of Single Chemical Structure from Handwritten Complex Chemical Structure with Junction Point Based Segmentation;automatic Mapping of Deciduous and Evergreen Forest by Using Machine Learning and Satellite Imagery;RIN: Towards a Semantic Rigorous Interpretable Artificial Immune System for Intrusion Detection;SVRCI: An Approach for Semantically Driven Video Recommendation Incorporating Collective Intelligence;deep Learning Based Model for Fundus Retinal Image Classification;one True Pairing: Evaluating Effective Language Pairings for Fake News Detection Employing Zero-Shot Cross-Lingual Transfer;reliable network-Packet Binary Classification;semKnowNews: A Semantically Inclined Knowledge Driven Approach for Multi-source Aggregation and Recommendation of News with a Focus on Personalization;extraction and Analysis of Speech Emotion Features Using Hybrid Punjabi Audio Dataset;human Activity Recognition in Videos Using Deep Learning;Brain Tumor Classification Using VGG-16 and MobileNetV2 Deep Learning Techniques on Magnetic Resonance Images (MRI);five-Year Life Expectancy Prediction of Prostate Cancer Patients Using Machine Learning algorithms;an Ensemble MultiLabel Classifier for Intra-Cranial Haemorrhage Detection from Large, Heterogeneous and Imbalanced Database;A Method for Workflow Segmentation and Action Prediction from Video Data - AR Content;convolutional Neural network Approach for Iris Segmentation;reinforcement Learning algorithms for Effective Resource Management in Cloud Computing;FedCLUS: Federated Clustering from Distributed Homogeneous Data;corpus Building for Hate Speech Detection of Gujarati Language;a Software

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13th international conference on Applications and Techniques in Information Security, ATIS 2022

13th International Conference on Applications and Techniques...

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13th international conference on Applications and Techniques in Information Security, ATIS 2022

ISBN: (纸本)9789819922635

The proceedings contain 23 papers. The special focus in this conference is on Applications and Techniques in Information Security. The topics include: Enhancing Face Recognition Accuracy Using the ED-FFP Extraction Method and Ensemble Learning for Forensics and Cyber Security;intrusion Detection Using Federated Learning;analysis of Classification algorithms for Predicting Parkinson’s Disease and Applications in the Field of Cybersecurity;Optimization of Secured Cluster Based Charging Dynamics and Scheduling of EV Using Deep RNN;analysis and Prognosis of Water Quality for River Ganga Using Water Quality Index;detection of Android Ransomware Using Machine Learning Approach;cyber Security and Layering of Medical Data Using Machine Learning algorithms;analysis on Classification of Handwritten Devanagari Characters Using Deep Learning Models;analysis and Comparison of Different Frontend Frameworks;non-malleable Codes from Authenticated Encryption in Split-State Model;lightweight Capability-Based Access Control for Internet of Things (IoT);securing IoT Using Blockchain;VIKAS: A Multimodal Framework to Aid in Effective Disaster Management;discovery of Rare Itemsets Using Hyper-Linked Data Structure: A Parallel Approach;continuously Non-malleable Codes from Authenticated Encryptions in 2-Split-State Model;Deep Learning Based Differential Classifier of PRIDE and RC5;A Better MixColumns Matrix to AES Against Differential Fault Analysis Attack;variants of Crypto-Jacking Attacks and Their Detection Techniques;comparative Study of Sentiment Analysis on Cyber Security Related Multi-sourced Data in Social Media Platforms;modified Blowfish Encryption Algorithm for Wireless Body Area network;eyeEncrypt: A Cyber-Secured Framework for Retinal Image Segmentation.

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