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international conference on Data Sciences, Security and Applications, ICDSSA 2019

International Conference on Data Sciences, Security and Appl...

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international conference on Data Sciences, Security and Applications, ICDSSA 2019

ISBN: (纸本)9789811503719

The proceedings contain 38 papers. The special focus in this conference is on Data Sciences, Security and Applications. The topics include: Classification and analysis of real-world earthquake data using various machine learning algorithms;how to help johnny to travel in a brimming train?;soft computing paradigms based clustering in wireless sensor networks: A survey;ann model for liver disorder detection;design flaws and cryptanalysis of elliptic curve cryptography-based lightweight authentication scheme for smart grid communication;distributed authentication security for iot using dass and loki91;macro factors affecting cloud computing readiness: A cross-country analysis;controller area network for battlefield-of-things;an experimental approach to unravel effects of malware on system network interface;smart ticketing for academic campus shuttle transportation system based on rfid;design of big data privacy framework—a balancing act;crime data set analysis using formal concept analysis (fca): A survey;robust speaker recognition based on low-level- and prosodic-level-features;classification of astronomical objects using various machine learning techniques;soundex algorithm for hindi language names;how do innovation lifecycle phases affect the innovation success of it firms?;behavioral analysis of active facebook users using the neo pi-r model;forecasting air quality of delhi using arima model;etsp: Enhanced trust-based security protocol to handle blackhole attacks in opportunistic networks;proposed model for distributed storage automation system using kubernetes operators;a feature-based kinship verification technique using convolutional neural network;image encryption using permutation–diffusion approach;analyzing the patterns of delhi’s air pollution;facial recognition using deep learning;review-based topic distribution profile for recommender systems.

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Dimensionality Reduction for Insect Bites pattern recognition 2nd

Dimensionality Reduction for Insect Bites Pattern Recognitio...

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2nd international conference on Smart IoT Systems: Innovations and computing, SSIC 2019

作者： Khan, Abdul Rehman Rakesh, Nitin Matam, Rakesh MINT Evolution NoidaUttar Pradesh India Department of CSE Amity University NoidaUttar Pradesh India Department of CSE Indian Institute of Information Technology Guwahati India

ISBN: (纸本)9789811384059

Dimensionality reduction has been widely developed for machine learning and if we consider features extracted from images, approach with which the data needs to be processed should be unambiguous. In this paper we will be discussing some of the dimensionality reduction techniques on dataset, which could be used for training any classification model to recognize which class the image belongs and provide mathematical acumen behind them. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Classification (of information)

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Application of Variable-Valued Logic to Correct pattern recognition Algorithms 10th

Application of Variable-Valued Logic to Correct Pattern Reco...

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10th Annual international conference on Biologically Inspired Cognitive Architectures, BICA 2019

作者： Lyutikova, Larisa A. Shmatova, Eleva V. St. Shortanova 89 a NalchikKBR360000 Russia

ISBN: (纸本)9783030257187

In this work the logical analysis is carried out for the predetermined subject domain, that represents an object and its describing characteristics in terms of variable-valued logic, besides the set of algorithms operating at the given domain is studied. The study developed logical procedure for creation of the correct algorithms that analyze subject domain, model the knowledge base for the set objects, minimize it and allocate a unique feature set for each object. © 2020, Springer Nature Switzerland AG.

关键词： Knowledge based systems

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Application of Common ANN for Similar Datatypes in On-line Monitoring and Security Estimation of Power System

Application of Common ANN for Similar Datatypes in On-line M...

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Springer international conference on Emerging Technologies in Data Mining and Information Security (IEMIS)

作者： Tiwary, Shubhranshu Kumar Pal, Jagadish Chanda, Chandan Kumar IIEST Dept EE Sibpur 711103 Howrah India

ISBN: (纸本)9789811319518;9789811319501

Monitoring a power network is an important task which is very complicated. To monitor the power systems, the developed nations are relying and shifting more and more towards soft-computing and pattern recognition techniques with the rapid improvements in the computation. In the work elaborated here, a report on the employment of a common multilayer feed-forward net, to the security estimation of a power network has been reported. The model built, is a 5-bus system, developed on the Simulink environment of a MATLAB R2013a version 32-bit software. The outcome was confirmed on a Hardware-In-Loop (HIL) device, on RT Lab Simulator of OPAL RT Technologies. The analysis is presented in this work for the perusal of the readers.

关键词： soft computing

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Bangla Handwritten Basic Character recognition Using Deep Convolutional Neural Network 8

Bangla Handwritten Basic Character Recognition Using Deep Co...

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Joint 8th international conference on Informatics, Electronics and Vision (ICIEV) / 3rd international conference on Imaging, Vision and pattern recognition (icIVPR) / international conference on Activity and Behavior computing (ABC)

作者： Saha, Chandrika Faisal, Rahat Hossain Rahman, Md Mostafijur Univ Barishal Dept Comp Sci & Engn Barishal Bangladesh

ISBN: (纸本)9781728107882

Bangla is one of the mostly spoken languages all over the world, nonetheless, efforts on Bangla handwritten character recognition is not adequate. The use of Deep Convolutional Neural Network (DCNN) based classifiers has become a triumph over the state of art machine learning techniques. Using DCNN model to classify Bangla isolated basic characters can provide better output because of its ability to detect many hidden features from an image. In this paper, a new DCNN model, namely, BBCNet-15 is proposed for Bangla handwritten basic character recognition. the proposed model consists of 6 convolution layers, 6 max pooling layers, 2 fully connected layers followed by the softmax output unit. To avoid overfitting dropout regularization technique is used. The implementation of the proposed DCNN model is evaluated on a benchmark dataset, CMATERdb 3.1.2 which contains 50 character classes including 39 consonants and 11 vowels. The experimental evaluation of BBCNet-15 on the dataset provides a recognition accuracy of 96.40% which outperforms some prominent techniques in existence.

关键词： Deep learning Convolutional Neural Network pattern recognition Optical Character recognition Bangla Handwritten Character recognition

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Maiden Application of Hybrid Crow Search Algorithm with pattern Search Algorithm in LFC Studies of a Multi-area System Using Cascade FOPI-PDN Controller 9th

Maiden Application of Hybrid Crow Search Algorithm with Patt...

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9th international conference on soft computing for Problem Solving, SocProS 2019

作者： Babu, Naladi Ram Saikia, Lalit Chandra Raju, Dhenuvakonda Koteswara Electrical Engineering Department NIT Silchar Silchar India

ISBN: (纸本)9789811532894

This article demonstrates the hybridization of crow search algorithm with pattern search (HCA-PS) algorithm in automatic generation control of an unequal three-area thermal system. A new secondary controller named as fractional order proportional-integral cascaded with proportional-derivative with filter (FOPI-PDN) is proposed for the system. The controller gains and other parameters are simultaneously optimized by using HCA-PS algorithm. Comparison of system dynamics for FOPI-PDN controller is compared with that of PID, FOPI, FOPID controller reveals better performance of FOPI-PDN controller. It is also seen that when HVDC tie-line is connected in parallel to the AC tie-line, the system dynamic is found better than that with AC tie-line alone. Sensitivity analysis explores that the HCA-PS optimized with FOPI-PDN controller parameters at nominal conditions is found to be robust and tough enough against discrepancy in system inertia and loading conditions. The superiority of HCA-PS algorithm is also observed in terms of dynamic responses and convergence characteristics when compared to that obtained with firefly, cuckoo search and crow algorithms in the system comprising of AC-HVDC tie-lines with FOPI-PDN controller. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Controllers

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Bangladeshi License Plate recognition Using Adaboost Classifier 8

Bangladeshi License Plate Recognition Using Adaboost Classif...

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作者： Dhar, Prashengit Abedin, Md Zainal Karim, Razuan Fatema-Tuj-Johora Hossain, Mohammad Shahadat Univ Sci & Technol Chittagong Dept Comp Sci & Engn Chattogram Bangladesh Univ Chittagong Dept Comp Sci & Engn Chittagong 4331 Bangladesh

ISBN: (纸本)9781728107882

License plate recognition (LPR) is a technology for the authentication of a vehicle by locating and recognizing the license plate number in an image through computer vision techniques and machine learning models. To develop intelligent traffic management such as vehicle monitoring, LPR is a key component. However, due to the diversity of layouts and characters of plates, universal solution is not possible. So, this research focuses on development of an algorithm for the recognition of license plate of Bangladesh by using image processing's and machine learning model. This algorithm executes in three steps: detection of the plate with shape verification, tilt correction and recognition of the number. For detection, RGB color space, median filtering, binarization, morphological analysis, region properties for filtering are applied. To discard noisy object, shape verification is done through robust distances to borders vectors. Before character segmentation, horizontal tilt correction is applied. Then, characters are extracted by using bounding box parameters from the extracted plate. Finally, the recognition is implemented by using the blending of Histogram Oriented Gradient (HOG) and Local Binary pattern (LBP) features and adaptive boosting (Adaboost) classifier is used to categorize the characters. The proposed algorithm is simulated on the images which are captured from different roads of Bangladesh. The experimental result shows that the detection and recognition accuracy is noteworthy.

关键词： License Plate recognition (LPR) RGB Color Model Distance to Borders (DtBs) Character Segmentation HOG (Histogram of Oriented Gradient) Local Binary pattern (LBP) Adaboost

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An Enhanced Coarse-to-Fine Framework for the Segmentation of Clinical Target Volume 23rd

An Enhanced Coarse-to-Fine Framework for the Segmentation of...

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Anatomical Brain Barriers to Cancer Spread: Segmentation from CT and MR Images Challenge, ABCs 2020, Learn2Reg Challenge, L2R 2020 and Thyroid Nodule Segmentation and Classification in Ultrasound Images Challenge, TN-SCUI 2020 held in conjunction with 23rd international conference on Medical Image computing and Computer-Assisted Intervention, MICCAI 2020

作者： Chen, Huai Qian, Dahong Liu, Weiping Li, Hui Wang, Lisheng Institute of Image Processing and Pattern Recognition Department of Automation Shanghai Jiao Tong University Shanghai200240 China School of Biomedical Engineering Shanghai Jiao Tong University Shanghai200240 China Department of Algorithm and Research Shanghai Aitrox Technology Co. Ltd. Shanghai China National Key Laboratory of Science and Technology on Nano/Micro Fabrication Key Laboratory for Thin Film and Micro Fabrication of the Ministry of Education Institute of Micro-Nano Science and Technology Shanghai Jiao Tong University Shanghai200240 China

ISBN: (纸本)9783030718268

In radiation therapy, obtaining accurate boundary of the clinical target volume (CTV) is the vital step to decrease the risk of treatment failures. However, it is a time-consuming and laborious task to obtain the delineation by hand. Therefore, an automatic algorithm is urgently needed to realize accurate segmentation. In this paper, we propose an enhanced coarse-to-fine frameworkto automatically fuse the information of CT, T1 and T2 images to get the target region. This framework includes a coarse-segmentation stage to identify the region of interest (ROI) of targets and a fine-segmentation stage to iteratively refine the segmentation. In the coarse-segmentation stage, the F-loss is proposed to keep the high recall rate of the ROI. In the fine segmentation, the ROI of target will be first cropped according to the ROI obtained by coarse-segmentation and be fed into a 3D-Unet to get the initial results. Then, the prediction and medium features will be set as additional information for the next one network to refine the results. When evaluated on the validation dataset of challenge of Anatomical Brain Barriers to Cancer Spread (ABCs), our method won the 3th place in the public leaderboard. © 2021, Springer Nature Switzerland AG.

关键词： Iterative methods

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Banknote Issuing Country Identification Using Image Processing and Neural Networks 13th

Banknote Issuing Country Identification Using Image Processi...

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13th international conference on Application of Fuzzy Systems and soft computing (ICAFS)

作者： Khashman, Adnan Ahmed, Waleed Mammadli, Sadig ECRAA Mersin 10 Nicosia Turkey Final Int Univ Mersin 10 Kyrenia Turkey Univ Kyrenia Mersin 10 Kyrenia Turkey Odlar Yurdu Univ AZ-1008 Baku Azerbaijan

ISBN: (纸本)9783030041649

The work in this paper investigates developing an identification system for 21 countries using images of their banknotes and neural network classifiers. We consider the banknotes of 19 Asian countries, the European Union (EU), and the USA. Our motivation to investigate the Asian currencies is the increased global interaction in tourism and international trading with these countries where they have diverse and impressive banknote designs;thus making it difficult to identify by foreign visitors or traders. Our database comprises 504 original and pre-processed images of 6 banknotes of each of the 21 currencies. The investigated 19 Asian countries in this work are Afghanistan, Armenia, Azerbaijan, Bangladesh, Bhutan, Brunei, Burma, Cambodia, China, India, Kuwait, Maldives, Pakistan, Saudi Arabia, Sri Lanka, Syria, Tajikistan, Turkey, and United Arab Emirates. Most existing banknote identification systems aim to identify the currency value or decide whether a banknote is counterfeit. Our presented work is novel as it focuses on identifying the issuing country. Furthermore, we apply two pattern-averaging methods using (5 x 5) and (10 x 10) kernels, and follow two learning schemes to train and test the proposed neural identification models by using (50: 50) and (75: 25) training-to-validation data ratios. The obtained experimental results are considered as successful.

关键词： Artificial intelligence Image processing pattern averaging Neural networks Banknote identification Currency recognition

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13th international conference on Genetic and Evolutionary computing, ICGEC 2019

13th International Conference on Genetic and Evolutionary Co...

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13th international conference on Genetic and Evolutionary computing, ICGEC 2019

ISBN: (纸本)9789811533075

The proceedings contain 64 papers. The special focus in this conference is on Genetic and Evolutionary computing. The topics include: Research on optimizing parameters of pitch angle controller based on genetic algorithm;research and simulation analysis of brake energy recovery control strategy for pure electric vehicles;research on coupling vibration of disk crack and shaft crack of rotor system based on finite element method;structure design and analysis of elderly electric vehicle based on solar energy;structural design and analysis of ring steering wheel for old-age walking vehicle;rule-based graded braking for unsignalized intersection collision avoidance via vehicle-to-vehicle communication;a novel measure for trajectory similarity;Ts-DBSCAN: To detect trajectory anomaly for transportation vehicles;abnormal Analysis of Electricity Data Acquisition in Electricity Information Acquisition System;ant Colony Optimization Algorithm for Network Planning in Heterogeneous Cellular Networks;a method of power network security analysis considering cascading trip;construction Area Identification Method Based on Spatial-Temporal Trajectory of Slag Truck;study on hazardous scenario analysis of high-tech facilities and emergency response mechanism of science and technology parks based on IoT;power flow calculation based newton-raphson calculation;research on the application of instance segmentation algorithm in the counting of metro waiting population;Implementation of android audio equalizer based on FFmpeg;can deep neural networks learn broad semantic concepts of images?;A fast data hiding algorithm for H.264/AVC video in bitstream domain;an efficient pattern recognition technology for numerals of lottery and invoice;An improved YOLOV3 algorithm for pedestrian detection on UAV imagery.

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