• R-PCNN Method to Rapidly Detect Objects on THz Images in Human Body Security Checks 

      Xiao, Hong; Zhang, Rongyue; Wang, Hao; Zhu, Feng; Zhang, Cheng; Dai, Hong-Ning; Zhou, Yubin (Chapter, 2018)
      Terahertz human body security images have low resolution and a low signal-to-noise ratio. In the traditional method, image segmentation, positioning, and identification are applied to detect objects carried by humans in ...
    • Recommendation System for Immunization Coverage and Monitoring 

      Bhatti, Uzair Aslam; Huang, Mengxing; Wang, Hao; Zhang, Yu; Mehmood, Anum; Wu, Di (Journal article; Peer reviewed, 2017)
      Immunization averts an expected 2 to 3 million deaths every year from diphtheria, tetanus, pertussis (whooping cough), and measles; however, an additional 1.5 million deaths could be avoided if vaccination coverage was ...
    • Reflections on Teaching Electrical and Computer Engineering Courses at the Bachelor Level 

      Osen, Ottar; Bye, Robin Trulssen (Chapter, 2017)
      This paper reflects on a number of observations the authors have made over many years of teaching courses in electrical and computer engineering bachelor programmes. We suggest various methods and tips for improving lectures, ...
    • Regularized Urdu Speech Recognition with Semi-Supervised Deep Learning 

      Ali Humayun, Mohammad; Hameed, Ibrahim A.; Muslim Shah, Syed; Hassan Khan, Sohaib; Zafar, Irfan; Bin Ahmed, Saad; Shuja, Junaid (Journal article; Peer reviewed, 2019)
      Automatic Speech Recognition, (ASR) has achieved the best results for English, with end-to-end neural network based supervised models. These supervised models need huge amounts of labeled speech data for good generalization, ...
    • Relationship between maximal aerobic power with aerobic fitness as a function of signal-to-noise ratio 

      Beltrame, Thomas; Gois, Mariana; Hoffmann, Uwe; Koschate, Jessica; Hughson, Richard; Frade, Maria; Linares, Stephanie; Torres, Ricardo Da Silva; Catai, Aparecida (Peer reviewed; Journal article, 2020)
      Efforts to better understand cardiorespiratory health are relevant for the future development of optimized physical activity programs. We aimed to explore the impact of the signal quality on the expected associations between ...
    • Relative Motion Tracking of Vessels using Multi-Camera Handover and Aruco Markers 

      Drugli, Even; Fjørtoft, Vegard; Hagseth, Kai Julian; Sande, Ole Kristian (Bachelor thesis, 2019)
      Tauetanken hos NTNU, avdeling Ålesund, brukes i hovedsak av studenter i skipsdesign for å teste skrogmodeller, ROVer og andre vannfartøy. Ved undersøkelser av skipsdesign, brukes småskala testing med modeller for å ...
    • Release Note System 

      Randa, Markus; Ous, Lars; Lande Pedersen, Jan Anton (Bachelor thesis, 2020)
      I en bransje der det er høyt fokus på korte leveranser av programvare, er det å dokumentere disse leveransenefortsatt tungvindt manuelt-arbeid. Oppgaven gitt av Cordel beskriver et ønske om et ...
    • Relevant Feedback Based Accurate and Intelligent Retrieval on Capturing User Intention for Personalized Websites 

      Tang, Yayuan; Wang, Hao; Guo, Kehua; Xiao, Yizhe; Chi, Tao (Journal article; Peer reviewed, 2018)
      With the rapid growth of networking, cyber–physical–social systems (CPSSs) provide vast amounts of information. Aimed at the huge and complex data provided by networking, obtaining valuable information to meet precise ...
    • Remaining Useful Life Prediction for Lithium-Ion Battery: A Deep Learning Approach 

      Ren, Lei; Zhao, Li; Hong, Sheng; Zhao, Shiqiang; Wang, Hao; Zhang, Lin (Journal article; Peer reviewed, 2018)
      Accurate prediction of remaining useful life (RUL) of lithium-ion battery plays an increasingly crucial role in the intelligent battery health management systems. The advances in deep learning introduce new data-driven ...
    • Representing Scientific Literature Evolution via Temporal Knowledge Graphs 

      Rossanez, Anderson; Reis, Julio; Torres, Ricardo Da Silva (Peer reviewed; Journal article, 2020)
      Scientific publications register the current knowledge in a specific domain. As new researches are conducted, knowledge evolves, getting documented in dissertations, theses and articles. In this article, we introduce new ...
    • Research and development in agricultural robotics: A perspective of digital farming 

      R. Shamshiri, Redmond; Weltzien, Cornelia; Hameed, Ibrahim A.; J. Yule, Ian; E. Grift, Tony; Balasundram, Siva K.; Pitonakova, Lenka; Ahmad, Desa; Chowdhary, Girish (Journal article; Peer reviewed, 2018)
      Digital farming is the practice of modern technologies such as sensors, robotics, and data analysis for shifting from tedious operations to continuously automated processes. This paper reviews some of the latest achievements ...
    • Robotic Harvesting of Fruiting Vegetables: A Simulation Approach in V-REP, ROS and MATLAB 

      Shamshiri, Redmond Ramin; Hameed, Ibrahim A.; Karkee, Manoj; Weltzien, Cornelia (Chapter, 2018)
      In modern agriculture, there is a high demand to move from tedious manual harvesting to a continuously automated operation. This chapter reports on designing a simulation and control platform in V-REP, ROS, and MATLAB for ...
    • Robotic Process Automation 

      Giske Hagen, Anders (Bachelor thesis, 2021)
      Dette prosjektet startet med at jeg hadde en god ide for å strukturere e-postene vi får om kunder som ‘går ned’- mister forbindelsen. Jeg har utviklet både en nettside og programmert en robot til å lese e-posten og plassere ...
    • Robust H-Infinity Decentralized Control for Industrial Cooperative Robots. 

      Azar, Ahmad Taher; Serrano, Fernando E.; Hameed, Ibrahim A.; Kamal, Nashwa Ahmad; Vaidyanathan, Sundarapandian (Chapter, 2019)
      In this paper, a robust H-infinity controller is proposed for industrial cooperative robots in which disturbances are taken into account for an appropriate controller design. Considering the disturbance affects the system ...
    • Robust Sparse Representation and Multiclass Support Matrix Machines for the Classification of Motor Imagery EEG Signals 

      Razak, Imran; Hameed, Ibrahim A.; Xu, Guandong (Journal article; Peer reviewed, 2019)
      Background: EEG signals are extremely complex in comparison to other biomedical signals, thus require an efficient feature selection as well as classification approach. Traditional feature extraction and classification ...
    • RoeBot - The roe picking robot 

      Lilleindset, Kristian Andre; Aarseth, Per Espen; Brathaug, Yngve; Hildrestrand, Kristoffer (Bachelor thesis, 2018)
      Salmon is today a big part of the food commodities traded from aquaculture industry. However, there are several challenges with the industry today, and increasing yield and cutting costs throughout the supply chain is ...
    • Safety System for workers in freezer room 

      Daniel Erichsen; Eilev Brustugun; Shajeevan Panchardcharam (Bachelor thesis, 2020)
      Hensikten med oppgaven er å utvikle et ledende sikkerhetssystem for fryserom på fiskefartøy. Systemet skal kunne monteres i det nye fiskefartøyet Geir III, samt kunne monteres i eksisterende fiskefartøy. Sikkerhetssystemet ...
    • Scalable And User-Friendly Simulation 

      Rutle, Adrian; Wang, Hao; Bye, Robin Trulssen; Osen, Ottar (Chapter, 2015)
      Simulation is an important technique for integrating interacting models for predicting results of hypothetical scenarios. A typical application area for simulators is virtual prototyping (VP). In VP, simulators replace the ...
    • SecureIoT: Hop-Count Based Service-Oriented Efficient Security Solution for IoT 

      Kar, Pushpendu; Misra, Sudip; Mandal, Ankush Kumar; Wang, Hao (Chapter; Conference object, 2018)
      Internet of Things (IoT) is a network of physical devices which are accessible through the Internet. All the devices are assigned with an IP address and are competent enough to collect data and provide some services. The ...
    • Segmentation of Knee Joint Using 3D Convolutional Neural Networks 

      Sperre, Jørgen André (Master thesis, 2020)
      Dyp læring teknikker har hatt økende popularitet for medisin-relaterte segmenterings oppgaver de siste årene. Denne studien bruker ett 3D konvolusjonelt nevralt nettverk (CNN) kalt nnU-Net, for å automatisk semantisk ...