An Overview of Applications of Artificial Intelligence Using Different Techniques, Algorithms, and Tools

[1]  Geoffrey E. Hinton,et al.  Deep Learning , 2015, Nature.

[2]  Yadira Quiñonez,et al.  Image recognition in UAV videos using convolutional neural networks , 2020, IET Softw..

[3]  Tilottama Goswami,et al.  Impact of Deep Learning in Image Processing and Computer Vision , 2018 .

[4]  Daniel Merkle,et al.  Dynamic Polyethism and Competition for Tasks in Threshold Reinforcement Models of Social Insects , 2004, Adapt. Behav..

[5]  Ajay K. S. Singholi,et al.  Review of Expert System and Its Application in Robotics , 2018 .

[6]  Huihuang Zhao,et al.  Multiple classifiers fusion and CNN feature extraction for handwritten digits recognition , 2020, Granular Computing.

[7]  Changshui Zhang,et al.  Fast Branch Convolutional Neural Network for Traffic Sign Recognition , 2017, IEEE Intelligent Transportation Systems Magazine.

[8]  Li Deng,et al.  Deep Learning in Natural Language Generation from Images , 2018 .

[9]  Jezreel Mejia,et al.  Algorithm Proposal to Control a Robotic Arm for Physically Disable People Using the LCD Touch Screen , 2019, Advances in Intelligent Systems and Computing.

[10]  Yadira Quiñonez,et al.  Autonomous Robot Navigation Based on Pattern Recognition Techniques and Artificial Neural Networks , 2015, IWINAC.

[11]  Yucheng Liu,et al.  Smart Healthcare in the Era of Internet-of-Things , 2019, IEEE Consumer Electronics Magazine.

[12]  Richard K. G. Do,et al.  Convolutional neural networks: an overview and application in radiology , 2018, Insights into Imaging.

[13]  Kofi Appiah,et al.  Embedded Vision Systems: A Review of the Literature , 2018, ARC.

[14]  Shamshad Ansari.  Building a Machine Learning–Based Computer Vision System , 2020 .

[15]  Sudha Natarajan,et al.  Traffic sign recognition using weighted multi‐convolutional neural network , 2018, IET Intelligent Transport Systems.

[16]  Epaminondas Kapetanios,et al.  Are Deep Learning Approaches Suitable for Natural Language Processing? , 2016, NLDB.

[17]  Raphaël Jeanson,et al.  Emergence of increased division of labor as a function of group size , 2007, Behavioral Ecology and Sociobiology.

[18]  Javier de Lope,et al.  Fusion of learning automata theory and granular inference systems: ANLAGIS. Applications to pattern recognition and machine learning , 2011 .

[19]  Wenlong Fu,et al.  A Survey of Recent Advances in Transfer Learning , 2019, 2019 IEEE 19th International Conference on Communication Technology (ICCT).

[20]  Mohammad Hassan Moradi,et al.  The attractor recurrent neural network based on fuzzy functions: An effective model for the classification of lung abnormalities , 2017, Comput. Biol. Medicine.

[21]  Thillainathan Logenthiran,et al.  A Novel Smart Energy Theft System (SETS) for IoT-Based Smart Home , 2019, IEEE Internet of Things Journal.

[22]  P. S. Sastry,et al.  Varieties of learning automata: an overview , 2002, IEEE Trans. Syst. Man Cybern. Part B.

[23]  Priti Maheshwary,et al.  Internet of Things (IoT) for building smart home system , 2017, 2017 International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC).

[24]  Qiang Li,et al.  The application of deep learning in computer vision , 2017 .

[25]  Alberto Attilio Brincat,et al.  IoT as a Service for Smart Cities and Nations , 2019, IEEE Internet of Things Magazine.

[26]  Luca Ambrogioni,et al.  Generative adversarial networks for reconstructing natural images from brain activity , 2017, NeuroImage.

[27]  Senthil Yogamani,et al.  Depth Augmented Semantic Segmentation Networks for Automated Driving , 2018 .

[28]  Hui Liang,et al.  Upper limb rehabilitation using robotic exoskeleton systems: a systematic review , 2018, International Journal of Intelligent Robotics and Applications.

[29]  Marco Picone,et al.  Wearable Computing for the Internet of Things , 2015, IT Professional.

[30]  Anil K. Jain,et al.  Statistical Pattern Recognition: A Review , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[31]  Sourya Dipta Das,et al.  Bird Species Classification using Transfer Learning with Multistage Training , 2018, ArXiv.

[32]  Paul Suetens,et al.  The Role of Medical Image Computing and Machine Learning in Healthcare , 2019, Artificial Intelligence in Medical Imaging.

[33]  Hua Xu,et al.  Predict effective drug combination by deep belief network and ontology fingerprints , 2018, J. Biomed. Informatics.

[34]  Pieter Abbeel,et al.  Learning by observation for surgical subtasks: Multilateral cutting of 3D viscoelastic and 2D Orthotropic Tissue Phantoms , 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).

[35]  Javier de Lope Asiaín,et al.  Cooperative and Competitive Behaviors in a Multi-robot System for Surveillance Tasks , 2009, EUROCAST.

[36]  Sudhir N. Dhage,et al.  Diabetes Disease Prediction Using Machine Learning on Big Data of Healthcare , 2018, 2018 Fourth International Conference on Computing Communication Control and Automation (ICCUBEA).

[37]  Chihiro Shibata,et al.  Transfer Learning Method for Very Deep CNN for Text Classification and Methods for its Evaluation , 2018, 2018 IEEE 42nd Annual Computer Software and Applications Conference (COMPSAC).

[38]  Yurong Liu,et al.  A survey of deep neural network architectures and their applications , 2017, Neurocomputing.

[39]  Ting Liu,et al.  Recent advances in convolutional neural networks , 2015, Pattern Recognit..

[40]  Larry P. Heck,et al.  Deep learning of knowledge graph embeddings for semantic parsing of Twitter dialogs , 2014, 2014 IEEE Global Conference on Signal and Information Processing (GlobalSIP).

[41]  Robert P. Gove,et al.  Division of labour and social insect colony performance in relation to task and mating number under two alternative response threshold models , 2009, Insectes Sociaux.

[42]  Brian Keith,et al.  A Review on Bayesian Networks for Sentiment Analysis , 2018, Advances in Intelligent Systems and Computing.

[43]  Gursel Alici,et al.  Review on Design and Control Aspects of Robotic Shoulder Rehabilitation Orthoses , 2017, IEEE Transactions on Human-Machine Systems.

[44]  Rahul Johari,et al.  IOT based Electrical Device Surveillance and Control System , 2019, 2019 4th International Conference on Internet of Things: Smart Innovation and Usages (IoT-SIU).

[45]  M. A. Jabbar,et al.  Machine Learning in Healthcare: A Review , 2018, 2018 Second International Conference on Electronics, Communication and Aerospace Technology (ICECA).

[46]  Maizatul Akmar Ismail,et al.  Face Recognition and Age Estimation Implications of Changes in Facial Features: A Critical Review Study , 2018, IEEE Access.

[47]  Jin He,et al.  Real-Time Multilead Convolutional Neural Network for Myocardial Infarction Detection , 2018, IEEE Journal of Biomedical and Health Informatics.

[48]  Uma Mudengudi,et al.  Image Segmentation and Geometric Feature Based Approach for Fast Video Summarization of Surveillance Videos , 2018, Communications in Computer and Information Science.

[49]  Marco Dorigo,et al.  Ant colony optimization theory: A survey , 2005, Theor. Comput. Sci..

[50]  Jian Sun,et al.  Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[51]  E. Bonabeau,et al.  Fixed response thresholds and the regulation of division of labor in insect societies , 1998 .

[52]  Musard Balliu,et al.  Securing IoT Apps , 2019, IEEE Security & Privacy.

[53]  Junhu Ruan,et al.  Agriculture IoT: Emerging Trends, Cooperation Networks, and Outlook , 2019, IEEE Wireless Communications.

[54]  Ming Dong,et al.  Generating synthetic CTs from magnetic resonance images using generative adversarial networks , 2018, Medical physics.

[55]  Javier de Lope Asiaín,et al.  Decentralized Multi-tasks Distribution in Heterogeneous Robot Teams by Means of Ant Colony Optimization and Learning Automata , 2012, HAIS.

[56]  Jimeng Sun,et al.  Using recurrent neural network models for early detection of heart failure onset , 2016, J. Am. Medical Informatics Assoc..

[57]  Mohsen Guizani,et al.  Secure Edge of Things for Smart Healthcare Surveillance Framework , 2019, IEEE Access.

[58]  Summer Allen.  New Prostheses and Orthoses Step Up their Game: Motorized Knees, Robotic Hands, and Exosuits Mark Advances in Rehabilitation Technology , 2016, IEEE Pulse.

[59]  Ankica Babic,et al.  Structural Risk Evaluation of a Deep Neural Network and a Markov Model in Extracting Medical Information from Phonocardiography , 2018, ICIMTH.

[60]  Samana Jafri,et al.  Face Recognition using Deep Neural Network with "LivenessNet" , 2020, 2020 International Conference on Inventive Computation Technologies (ICICT).

[61]  Prabhat,et al.  Comparative Analysis of Deep Convolutional Generative Adversarial Network and Conditional Generative Adversarial Network using Hand Written Digits , 2020, 2020 4th International Conference on Intelligent Computing and Control Systems (ICICCS).

[62]  Javier de Lope Asiaín,et al.  Bio-inspired Decentralized Self-coordination Algorithms for Multi-heterogeneous Specialized Tasks Distribution in Multi-Robot Systems , 2011, IWINAC.

[63]  Eric Bonabeau,et al.  Cooperative transport by ants and robots , 2000, Robotics Auton. Syst..

[64]  Martial Hebert,et al.  A behavior-based system for off-road navigation , 1994, IEEE Trans. Robotics Autom..

[65]  Gülgün Kayakutlu,et al.  Definition of artificial neural networks with comparison to other networks , 2011, WCIT.

[66]  Xingming Sun,et al.  Convolutional neural network for smooth filtering detection , 2018, IET Image Process..

[67]  Yu Tsao,et al.  S1 and S2 Heart Sound Recognition Using Deep Neural Networks , 2017, IEEE Trans. Biomed. Eng..

[68]  Mohammad S. Obaidat,et al.  Quality of Service Optimization in an IoT-Driven Intelligent Transportation System , 2019, IEEE Wireless Communications.

[69]  Ronaldo C. Prati,et al.  Advancing IoT-Based Smart Irrigation , 2019, IEEE Internet of Things Magazine.

[70]  Sunil Kumar Khatri,et al.  Future of Wearable Devices Using IoT Synergy in AI , 2019, 2019 3rd International conference on Electronics, Communication and Aerospace Technology (ICECA).

[71]  Vijay Vasudevan,et al.  Learning Transferable Architectures for Scalable Image Recognition , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[72]  Elnaz Jahani Heravi,et al.  Guide to Convolutional Neural Networks , 2017 .

[73]  Mark Sandler,et al.  MobileNetV2: Inverted Residuals and Linear Bottlenecks , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[74]  Retno Larasati,et al.  Handwritten digits recognition using ensemble neural networks and ensemble decision tree , 2017, 2017 International Conference on Smart Cities, Automation & Intelligent Computing Systems (ICON-SONICS).

[75]  Silvio Savarese,et al.  Discovering Groups of People in Images , 2014, ECCV.

[76]  Fanliang Bu,et al.  Generation of person-specific 3D model based on single photograph , 2016, 2016 2nd IEEE International Conference on Computer and Communications (ICCC).

[77]  J. Deneubourg,et al.  Emergent polyethism as a consequence of increased colony size in insect societies. , 2002, Journal of theoretical biology.

[78]  Jie Yang,et al.  Mining Chinese social media UGC: a big-data framework for analyzing Douban movie reviews , 2016, Journal of Big Data.

[79]  R. Pfeifer,et al.  Self-Organization, Embodiment, and Biologically Inspired Robotics , 2007, Science.

[80]  Xiangjian He,et al.  Deep Learning Techniques for Medical Image Segmentation: Achievements and Challenges , 2019, Journal of Digital Imaging.

[81]  Qiang Yang,et al.  A Survey on Transfer Learning , 2010, IEEE Transactions on Knowledge and Data Engineering.

[82]  Christian Blum,et al.  Ant colony optimization: Introduction and recent trends , 2005 .

[83]  Rika Sustika,et al.  On comparison of deep learning architectures for distant speech recognition , 2017, 2017 2nd International conferences on Information Technology, Information Systems and Electrical Engineering (ICITISEE).

[84]  Kgas Waidyasekara,et al.  Application of Robotic Technology for the Advancement of Construction Industry in Sri Lanka: A Review , 2020 .

[85]  U. M. Chaskar,et al.  GUI Based Pick and Place Robotic Arm for Multipurpose Industrial Applications , 2018, 2018 Second International Conference on Intelligent Computing and Control Systems (ICICCS).

[86]  Chetana Prakash,et al.  Internet of Things (IoT): A vision, architectural elements, and security issues , 2017, 2017 International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC).

[87]  Javier de Lope Asiaín,et al.  Stochastic Learning Automata for Self-coordination in Heterogeneous Multi-Tasks Selection in Multi-Robot Systems , 2011, MICAI.

[88]  Yadira Quiñonez,et al.  Simulation and path planning for quadcopter obstacle avoidance in indoor environments using the ROS framework , 2017 .

[89]  Lucia Lo Bello,et al.  Industrial robotics in factory automation: From the early stage to the Internet of Things , 2017, IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society.

[90]  Li Fei-Fei,et al.  Progressive Neural Architecture Search , 2017, ECCV.

[91]  Chao Zeng,et al.  Bio-inspired robotic impedance adaptation for human-robot collaborative tasks , 2020, Science China Information Sciences.

[92]  Sunil Karamchandani,et al.  Performance Evaluation of Machine Learning and Deep Learning Techniques for Sentiment Analysis , 2018 .

[93]  Xiuzhen Cheng,et al.  NormaChain: A Blockchain-Based Normalized Autonomous Transaction Settlement System for IoT-Based E-Commerce , 2019, IEEE Internet of Things Journal.

[94]  Howie Choset,et al.  Continuum Robots for Medical Applications: A Survey , 2015, IEEE Transactions on Robotics.

[95]  Javier de Lope Asiaín,et al.  Response threshold models and stochastic learning automata for self-coordination of heterogeneous multi-task distribution in multi-robot systems , 2013, Robotics Auton. Syst..

[96]  John Soldatos,et al.  VITAL-OS: An Open Source IoT Operating System for Smart Cities , 2018, IEEE Communications Standards Magazine.

[97]  G. Robinson.  Regulation of division of labor in insect societies. , 1992, Annual review of entomology.

[98]  Milagra Weiss,et al.  Intracolonial genetic diversity in honeybee (Apis mellifera) colonies increases pollen foraging efficiency , 2011, Behavioral Ecology and Sociobiology.

[99]  Shang-Liang Chen,et al.  Orthogonal least squares learning algorithm for radial basis function networks , 1991, IEEE Trans. Neural Networks.

[100]  Ryo Miyajima.  Deep Learning Triggers a New Era in Industrial Robotics , 2017, IEEE MultiMedia.

[101]  Cristina Grisot.  Application to Natural Language Processing and Machine Translation , 2018 .

[102]  Ke Li,et al.  A New Framework of Intelligent Public Transportation System Based on the Internet of Things , 2019, IEEE Access.

[103]  D. Maravall,et al.  Application of Self-Organizing Techniques for the Distribution of Heterogeneous Multi-Tasks in Multi-Robot Systems , 2012, 2012 IEEE Ninth Electronics, Robotics and Automotive Mechanics Conference.

[104]  Xi Zhang,et al.  Research on the Application of IoT in E-Commerce , 2017, 22017 IEEE International Conference on Computational Science and Engineering (CSE) and IEEE International Conference on Embedded and Ubiquitous Computing (EUC).

[105]  Shamshad Ansari.  Industrial Application: Real-Time Defect Detection in Industrial Manufacturing , 2020 .

[106]  Bo Chen,et al.  MnasNet: Platform-Aware Neural Architecture Search for Mobile , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[107]  Yadira Quiñonez,et al.  Using Convolutional Neural Networks to Recognition of Dolphin Images , 2018, Advances in Intelligent Systems and Computing.

[108]  Javier de Lope,et al.  Self-organizing techniques to improve the decentralized multi-task distribution in multi-robot systems , 2015, Neurocomputing.

[109]  Maja J. Matarić,et al.  From Local Interactions to Collective Intelligence , 1995 .

[110]  Sergey Ioffe,et al.  Rethinking the Inception Architecture for Computer Vision , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[111]  Hung T. Nguyen,et al.  Deep learning framework for detection of hypoglycemic episodes in children with type 1 diabetes , 2016, 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).