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Facial Expression Recognition Using Improved Adaptive Local Ternary Pattern 3rd

Facial Expression Recognition Using Improved Adaptive Local ...

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3rd international conference on Computer Vision and Image processing (CVIP)

作者： Saurav, Sumeet Singh, Sanjay Saini, Ravi Yadav, Madhulika Acad Sci & Innovat Res AcSIR Chennai Tamil Nadu India CSIR Cent Elect Engn Res Inst Pilani Rajasthan India Banasthali Vidyapith Dept Elect Vidyapith Rajasthan India

ISBN: (纸本)9789813292918;9789813292901

Recently, there has been a huge demand for assistive technology for industrial, commercial, automobile, and societal applications. In some of these applications, there is a requirement of an efficient and accurate system for automatic facial expression recognition (FER). Therefore, FER has gained enormous interest among computer vision researchers. Although there has been a plethora of work available in the literature, an automatic FER system has not yet reached the desired level of robustness and performance. In most of these works, there has been the dominance of appearance-based methods primarily consisting of local binary pattern (LBP), local directional pattern (LDP), local ternary pattern (LTP), gradient local ternary pattern (GLTP), and improved local ternary pattern (IGLTP). Keeping in view the popularity of appearance-based methods, in this paper, we have proposed an appearance-based descriptor called Improved Adaptive Local Ternary Pattern (IALTP) for automatic FER. This new descriptor is an improved version of ALTP, which has been proved to be effective in face recognition. We have investigated ALTP in more details and have proposed some improvements like the use of uniform patterns and dimensionality reduction via principal component analysis (PCA). The reduced features are then classified using kernel extreme learning machine (K-ELM) classifier. In order to validate the performance of the proposed method, experiments have been conducted on three different FER datasets using well-known evaluation measures such as accuracy, precision, recall, and F1-Score. The proposed approach has also been compared with some of the state-of-the-art works in literature and found to be more accurate and efficient.

关键词： Facial expression recognition (FER) Adaptive local ternary pattern (ALTP) Principal component analysis (PCA) Kernel extreme learning machine (K-ELM)

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Assessing the investment risk of virtual it company based on machine learning 3rd

Assessing the investment risk of virtual it company based on...

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3rd international conference on Data Stream and Mining and processing, DSMP 2020

作者： Lipyanina, Hrystyna Maksymovych, Valeriya Sachenko, Anatoliy Lendyuk, Taras Fomenko, Andrii Kit, Ivan Ternopil National Economic University Lvivska Str. 11 Ternopil46000 Ukraine Dnipropetrovsk State University of Internal Affairs Gagarin Avenue 26 Dnipro Ukraine

ISBN: (纸本)9783030616557

A module for assessing the investment risks of a virtual IT company has been developed. It enables to reduce the time spent on assessing the inves-tor’s risks of a virtual IT company. A detailed justification of each selected risk parameter that influences on the success of the investment project of the virtual IT Company has done. A developed algorithm for assessing the investment risk of the virtual IT company is based on machine learning and using the expert scoring method (10 experts from 20 implemented projects were involved) by 23 risk parameters. Forecasting of investment risk assess-ment modeling of the virtual IT company using machine learning is based on eight methods: Support Vector Classifier, Stochastic Gradient Decent Classifier, Random Forest Classifier, Decision Tree Classifier, Gaussian Na-ive Bayes, K-Neighbors Classifier, Ada Boost Classifier, Logistic Regression. In addition, a module was developed to support decision-making based on three methods with the best forecast, namely: Support Vector Classifier, Random Forest Classifier, K-Neighbors Classifier. © 2020, Springer Nature Switzerland AG.

关键词： machine learning

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GPON Traffic Analysis with TensorFlow 43

GPON Traffic Analysis with TensorFlow

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43rd international conference on Telecommunications and signal processing (TSP)

作者： Oujersky, Vaclav Tomasov, Adrian Holik, Martin Skorpil, Vladislav Horvath, Tomas Jurcik, Michal Brno Univ Technol Dept Telecommun Brno Czech Republic

ISBN: (纸本)9781728163765

The paper presents the latest research results of gigabit passive optical network analysis using machine learning algorithms. TensorFlow has been used to learn the frames of GPON management traffic of the G.984.3 protocol and detect outliers to the standard. The frames are captured by FPGA programmable network card and processed with a software parser and further processed with the TensorFlow using JSON format. The proposed technique can bring a way how to test if vendors of network devices follow the standard and if the content of the frames can be treated as secure and trustworthy.

关键词： analysis detection gpon machine learning tensorflow

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Daphnet Freezing Recognition with Gait Data by Using machine learning Algorithms 43

Daphnet Freezing Recognition with Gait Data by Using Machine...

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43rd international conference on Telecommunications and signal processing (TSP)

作者： Guney, Selda Boluk, Busra Baskent Univ Fac Engn Elect Elect Engn Ankara Turkey

ISBN: (纸本)9781728163765

The aim of this study was to test the success of the data set obtained by a wearable health assistant developed for the symptom of freezing (FOG) in gait of Parkinson's patients and to increase the success of the system. The system was tested with different machine learning methods to measure the success of the wearable health assistant system. For all patients (ten patients), the highest success value was obtained and the mean sensitivity and specificity values of the system were calculated and compared with the results obtained in the literature review. In the literature, mean sensitivity and specificity were 73.1% and 81.6%, respectively;In this study, mean sensitivity and specificity were 91.9% and 71.14%, respectively. In order to better analyze the success of the system, two patients with successful and unsuccessful results were selected for the data set in line with the results obtained in the literature review. The success of the system was tested by using different machine learning methods on the data sets of two patients. Finally, the successes obtained by feature extraction methods were tried to be increased. Among the different machine learning methods on the data sets used for patient 8 and patient 3, the most successful method was obtained by combining the models (ensemble). The highest achievement value obtained by attribute extraction methods was obtained when PCA was applied. However, the success value obtained with raw data could not be increased. All results are tabulated and presented.

关键词： Parkinsons disease daphnet freezing wearable health assistant machine learning feature extraction

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3rd international conference on Computational Vision and Bio Inspired Computing, ICCVBIC 2019

3rd International Conference on Computational Vision and Bio...

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3rd international conference on Computational Vision and Bio Inspired Computing, ICCVBIC 2019

ISBN: (纸本)9783030372170

The proceedings contain 147 papers. The special focus in this conference is on Computational Vision and Bio Inspired Computing. The topics include: Fruit classification using traditional machine learning and deep learning approach;blind guidance system;a novel multimodal biometrics system with fingerprint and gait recognition traits using contourlet derivative weighted rank fusion;implementation of real-time skin segmentation based on K-means clustering method;an image processing based approach for monitoring changes in webpages;Vehicle detection using point cloud and 3D LIDAR sensor to draw 3D bounding box;An experiment with random walks and GrabCut in one cut interactive image segmentation techniques on MRI images;a comprehensive survey on web recommendations systems with special focus on filtering techniques and usage of machine learning;a review on business intelligence systems using artificial intelligence;image completion of highly noisy images using deep learning;virtual vision for blind people using mobile camera and sonar sensors;supervised and unsupervised learning applied to Crowdfunding;study on performance of classification algorithms based on the sample size for crop prediction;global normalization for fingerprint image enhancement;recurrent neural network for content based image retrieval using image captioning model;using deep learning on satellite images to identify deforestation/afforestation;an application of cellular automata: Satellite image classification;morlet wavelet threshold based glow warm optimized X-means clustering for forest fire detection;advance assessment of neural network for identification of diabetic nephropathy using renal biopsies images;advanced techniques to enhance human visual ability – A review;FSO: Issues, challenges and heuristic solutions.

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Score Genaration for Taiko no Tatsujin based on machine learning 3

Score Genaration for Taiko no Tatsujin based on Machine Lear...

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IEEE 3rd international conference on Multimedia Information processing and Retrieval (IEEE MIPR)

作者： Li, Rongfeng Chen, Yijun Beijing Univ Posts & Telecommun Beijing Key Lab Network Syst & Network Culture Beijing Peoples R China

ISBN: (纸本)9781728142722

Taiko no Tatsujin is one of the most popular rhythm-based games. Players simulate playing a drum in time with music. In order for players to play songs, an additional percussion part need to be composed based on the audio an existing song, the additional percussion part is not exactly the original percussion part of the song, but it is related to the melody, rhythm and other feathers of the song. This paper introduces two ways to generate the score of the additional percussion part that follow beat and melody of songs. One is that we split the raw audio into many measures, record some certain features of each measure, and build a database for measures and a database for features whose relationship is one on one. Using KNN model, we find every predicted measure for a target song which becomes the score in a whole. In another way, we pre-process the raw audio to extract MFCCs feature and utilize onset detection using CNN to classify notes at any time. Through these approaches, the score can be created in 5 seconds while its approach 86% similarity of the human written score.

关键词： Score generation Taiko No Tatsujin MFCC CNN

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Bidirectional Boost: On Improving Tibetan-Chinese Neural machine Translation with Back-Translation and Self-learning 3

Bidirectional Boost: On Improving Tibetan-Chinese Neural Mac...

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3rd international conference on Algorithms, Computing and Artificial Intelligence, ACAI 2020

作者： Duanzhu, Sangjie Zhang, Rui Jia, Cairang Key Laboratory of Tibetan Information Processing Ministry of Education China

ISBN: (纸本)9781450388115

Despite the remarkable success of Neural machine Translation system, such challenges as its drawback in low-resourced conditions persist. In recent years, working mechanism of exploiting either one or both source and target side monolingual data within the Neural machine Translation framework gained much attention in the field. Among many supervised and unsupervised proposals, back translation is increasingly seen as one of the most promising methods to improve low-resource NMT performance. Regardless of its simplicity, the effectiveness of back translation is highly dependent on performance of the backward model which is initially trained on available parallel data. To address the dilemma of back translation practices in low resource scenarios, we propose to employ target-side monolingual data to improve both backward and forward models by step-wise adoption of self-learning and back translation, which we refer to as Bidirectional *** experiments on a Tibetan-Chinese translation task attested the proposed approach with a result of producing 3.1 and 8.2 BLEU scores, respectively, both on forward and backward models over vanilla Transformers trained on genuine parallel data under supervised settings. © 2020 ACM.

关键词： Neural machine translation

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Contact Sensing via Active Oscillatory Actuation 3

Contact Sensing via Active Oscillatory Actuation

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IEEE 3rd international conference on Mechatronics, Robotics and Automation (ICMRA)

作者： Mitra, Rahul Boyd, Kirkland Subedi, Divas Chitrakar, Digesh Aldrich, Edwin Swamy, Ananya Huang, Kevin Trinity Coll Dept Engn Hartford CT 06106 USA

ISBN: (纸本)9781728190327

Collaborative robotic approaches seek to incorporate either direct human intervention in tasks previously suited for isolated robot devices, or to use precise machines (cobots) to assist in sensitive tasks. Cobots work alongside humans to extend the scope of robot assistance to spaces such as service and dynamic industrial or assembly tasks. With that said, the close proximity of humans with machines necessitates safe interaction, which can be achieved via lightweight materials and novel sensing capabilities. The inherent physical strength needed in some robot tasks, such as in assembly, make contact sensing of particular concern when introducing a human collaborator. A minimally intrusive method that can be seamlessly subsumed into extant devices is desired. In this paper, such a contact sensor is prototyped and tested. The sensor is bidirectional in that it actively provides an oscillatory actuation signal to a rigid link while simultaneously recording and analyzing the mechanical vibration of said link. Natural oscillation frequency shifts and energy concentration changes due to damping are congruent with different types of contact with the rigid link. The method is lightweight, low-cost and can be quickly incorporated into various manipulators. The developed configuration is advantageous as it does not require any delicate sensors on the robot body and relies primarily on actuated oscillations of the manipulator. Oscillatory acceleration data is collected and subsequently used to train and classify different contact locations using frequency-based features. Three separate classes are distinguished according to contact location. Results are promising and show excellent classification of both contact and contact location.

关键词： active sensing sensors collaborative robots collision detection machine learning

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Thyroid Nodules Stratification Based on Orientation Characteristics Using machine learning Approach 3

Thyroid Nodules Stratification Based on Orientation Characte...

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3rd international conference on Computer and Informatics Engineering, IC2IE 2020

作者： Nugroho, Hanung Adi Frannita, Eka Legya Hutami, Augustine Herini Tita Universitas Gadjah Mada Faculty of Engineering Department of Electrical and Information Engineering Yogyakarta Indonesia

ISBN: (纸本)9781728182476

Patients with thyroid nodules should undergo further assessment to define malignancy stratification. One of the assessments is conducted using ultrasound. There are ten characteristics of thyroid nodules in the ultrasound examination. One of the characteristics is orientation. The orientation characteristic has its perks as it can tell the malignancy state from the growth direction to the orientation category. This study develops an approach to determine the stratification of the thyroid nodules based on orientation characteristics. The proposed approach consists of pre-processing, segmentation, feature extraction, and classification by using a support vector machine. Nine geometrical and moment features are used to describe orientation characteristics. Furthermore, the features are trained to differentiate two classes, namely are parallel and non-parallel. The testing results achieve more than 0.98 for accuracy, sensitivity, and NPV, respectively, while specificity and PPV achieve a perfect score. Looking by the results, it can be concluded that the proposed method has a good performance in differentiating orientation characteristics into a parallel and non-parallel category. © 2020 IEEE.

关键词： Support vector machines

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Analytical review of methods for identifying emotions in text data 3

Analytical review of methods for identifying emotions in tex...

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3rd international conference on R. Piotrowski's Readings in Language Engineering and Applied Linguistics, PRLEAL 2019

作者： Dvoynikova, Anastasia Verkholyak, Oxana Karpov, Alexey St.Petersburg Russia

The sentiment analysis of text is one of the important tasks in the field of natural language processing. It is used in different areas. Despite the variety of existing methods, the systems of sentiment analysis of Russian-language texts give low accuracy compared to English-language ones. The article discusses basic methods for identifying emotions in text data and methods of text vectorization. The existing achievements in the field of computer sentiment analysis are analyzed. At the moment, there are many unsolved problems in the field of automatic sentiment analysis. Copyright © 2019 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 international (CC BY 4.0).

关键词： machine learning

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