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Start Over Topic classification Publication Type Electronic Resources Publisher mdpi - multidisciplinary digital publishing institute
6 results

1. Visual and Camera Sensors.

Author

Park, Kang Ryoung, Kim, Euntai, Lee, Sangyoun, and Park, Kang Ryoung

Subjects
Information technology industries, 3D point clouds, BIM, CNN, DLT, DeblurGAN, DoF-dependent, Hough-space, OCD4M, PnP, VSLAM-photogrammetric algorithm, accuracy analysis, artificial intelligence, automatic online calibration, autonomous landing, blur image restoration, camera calibration, camera networks, classification, close range photogrammetry, computer vision, computer-aided diagnosis, convolutional auto-encoders, convolutional filter, convolutional neural network, covariance, deep-learning-based motion deblurring and marker detection, distortion partition, drone, ensemble learning, facial expression recognition system, flying object detection, image processing, in vivo endoscopy, lens distortion, local image patch, low-cost device, machine learning, multi-scale featured local binary pattern, multi-sensor fusion, multimodal human recognition, network slimming, open-pit mine slope monitoring, optimum deployment, pathological site classification, plank recognition, point pair feature, portable mobile mapping system, pruning model, robotic grasping, robustness, self-assembly device, semi-direct SLAM, side-rear-view monitoring system, three-dimensional reconstruction, uncertainty, unmanned aerial vehicle, unsharp masking, vision measurement, visual-inertial, weighted DLT
Abstract

Summary: This book includes 13 papers published in Special Issue ("Visual and Camera Sensors") of the journal Sensors. The goal of this Special Issue was to invite high-quality, state-of-the-art research papers dealing with challenging issues in visual and camera sensors.

2. Semantic Web Technology and Recommender Systems.

Author

Kotis, Konstantinos, Kotis, Konstantinos, and Spiliotopoulos, Dimitris

Subjects
Information technology industries, Context-Aware Recommender System, Kendall Correlation Coefficient, OWL/RDF, ParlTech, Pearson Correlation Coefficient, RDF, SBVR, Spearman Correlation Coefficient, Twitter, Wikification, associative mining, big data analytics, blockchain, classification, clustering, cold start, cryptocurrency, cultural informatics, cultural space, cultural spaces, data catalog, dataset recommender, decision support, digital parliament, digital transformation, disruptive technologies, domain knowledge graph, fact type, informal document to SBVR, interactive information retrieval, job matching, journey planning, keyword search, knowledge graphs, knowledge-driven processes, legal tech, linked data, machine learning, migrants, mobility, named entity disambiguation, natural language, natural language query, neural networks, ontologies, ontology, operational rules, parliamentary administrators, parliamentary hype cycle, personalization, preferences, process mining, reasoning, recommendation, recommendation system, recommendation systems, recommender systems, refugees, resource efficiency, semantic trajectories, semantic web, sentiment analysis, social data, social media analysis, social media analytics, spatial datasets, technology framework, terrorism, text annotation, trending topics, user experience, user influence, user modeling, word sense disambiguation
Abstract

Summary: In this book (Volume I), 13 papers have been published on different topics of the wide research areas of Semantic Web and Recommender systems. These papers have been carefully selected based on the peer review of several respectful reviewers organized by MDPI's BDCC journal. This issue has attracted well-known international research teams, who we would like to thank for their work.

3. Hyperspectral Imaging and Applications.

Author

Chang, Chein-I, Chang, Chein-I, Song, Meiping, Wu, Chao-Cheng, and Zhang, Junping

Subjects
History of engineering & technology, Technology: general issues, 90° yaw imaging, AHS, AVIRIS, Africa, Dunhuang site, Gram-Schmidt orthogonalization, HyMap, KSVD, Otsu's method, SVM, adaptive window, agroforestry, airborne laser scanning, algebraic multigrid methods, anomaly detection, band expansion process (BEP), band grouping, band selection, band selection (BS), band subset selection (BSS), biodiversity, class imbalance, classification, composite kernel, constrained energy minimization, constrained energy minimization (CEM), correlation band expansion process (CBEP), data fusion, data integration, data unmixing, data-guided constraints, deep belief networks, deep learning, deep pipelined background statistics, endmember extraction, ensemble learning, evenness, fire severity, graph, hashing ensemble, hierarchical feature, high-level synthesis, hyperspectral, hyperspectral classification, hyperspectral compression, hyperspectral detection, hyperspectral image, hyperspectral image (HSI), hyperspectral image classification, hyperspectral imagery, hyperspectral images (HSIs), hyperspectral imaging, hyperspectral pansharpening, hyperspectral unmixing, image enhancement, image fusion, imaging spectroscopy, in situ measurements, intrinsic image decomposition, irradiance-based method, iterative CEM (ICEM), iterative algorithm, label propagation, linearly constrained minimum variance (LCMV), local abundance, local summation RX detector (LS-RXD), lossy compression, machine learning, mineral mapping, minimum noise fraction, multiscale spatial information, multiscale union regions adaptive sparse representation (MURASR), nonlinear band expansion (NBE), nonnegative matrix factorization, nuclear norm, on-board compression, optical spectral region, orthogonal projections, panchromatic, panchromatic image, parallel processing, peatland, progressive sample processing (PSP), prototype space, raw material, real-time processing, recursive anomaly detection, reflectance-based method, remote sensing, rolling guidance filtering (RGF), rotation forest, semi-supervised learning, semi-supervised local discriminant analysis, sequential LCMV-BSS (SQ LCMV-BSS), sliding window, sparse coding, sparse unmixing, sparseness, spectral mixture analysis, spectral variability, spectral-spatial classification, sprout detection, structure tensor, successive LCMV-BSS (SC LCMV-BSS), superpixel, target detection, terrestrial hyperspectral imaging, texture feature enhancement, thermal infrared spectral region, tree species, tree-based ensemble, vegetation type, vicarious calibration, vineyard, water stress, weighted fusion, weighted least squares filter
Abstract

Summary: Due to advent of sensor technology, hyperspectral imaging has become an emerging technology in remote sensing. Many problems, which cannot be resolved by multispectral imaging, can now be solved by hyperspectral imaging. The aim of this Special Issue "Hyperspectral Imaging and Applications" is to publish new ideas and technologies to facilitate the utility of hyperspectral imaging in data exploitation and to further explore its potential in different applications. This Special Issue has accepted and published 25 papers in various areas, which can be organized into 7 categories with the number of papers published in every category included in its open parenthesis. 1. Data Unmixing (2 papers)2. Spectral variability (2 papers)3. Target Detection (3 papers)4. Hyperspectral Image Classification (6 papers)5. Band Selection (2 papers)6. Data Fusion (2 papers)7. Applications (8 papers) Under every category each paper is briefly summarized by a short description so that readers can quickly grab its content to find what they are interested in.

4. Bioinformatics Applications Based On Machine Learning.

Author

Chamoso, Pablo, Chamoso, Pablo, González-Briones, Alfonso, Mohamad, Mohd, and Rodriguez, Sara

Subjects
Technology: general issues, Affective Computing, Arabidopsis thaliana, Artificial Neural Networks, CTX-M, Decision table, Harmony Search, Machine Learning, PART, Particle Swarm Optimization, Weka, bi-directional LSTM, bioinformatics, biological functions detection, classification, clinical data, clinical implications, cluster, computer vision, convolutional neural network, data mining, deep learning, derivative-free optimization, detection, diabetes, dynamic models, ear detection, epidemiology, evolutionary computation, evolutionary computing, feature selection, forecast, fuel cell, gene clustering, genetic programming, glycolysis, gradient boosting, hybrid systems, hydrogen energy, image recognition, informative genes, intelligent systems, machine learning, metabolism, metagenomics, metrics, mitochondrial protein, parameter estimation, personality assessment, plasmodium falciparum, power management, real-life patients, regression, swarm intelligence, transposable elements, video analysis, yeast
Abstract

Summary: The great advances in information technology (IT) have implications for many sectors, such as bioinformatics, and has considerably increased their possibilities. This book presents a collection of 11 original research papers, all of them related to the application of IT-related techniques within the bioinformatics sector: from new applications created from the adaptation and application of existing techniques to the creation of new methodologies to solve existing problems.

5. Sustainability Analysis and Environmental Decision-Making Using Simulation, Optimization, and Computational Analytics.

Author

Yeomans, Julian Scott, Kozlova, Mariia, and Yeomans, Julian Scott

Subjects
Mathematics & science, Research & information: general, C-vine copula, CO2 emissions, DEA, Germany, Iowa food-energy-water nexus, LASSO, Monte Carlo simulation, South Texas, biofuel policy, biomass gasification, boron, business aviation, classification, computer modeling, computer simulation, desalination, dynamic programming, eco-efficiency, ecological indicators, ecological relationship, electric motor, electricity production, energy modeling, energy system design, environmental footprint, factorial analysis, feature selection, feed-in tariff, financial market, forecasting, fuzzy, generation profile, input-output analysis, interval, investing, investment profitability analysis, joint dependencies, machine learning, model reduction, modelling, n/a, nitrogen export, nonpoint source pollution, operational flexibility, optimal allocation, optimal path, parameter estimation, point source pollution, pollutant loadings, quantile regression, reduction, regression, renewable energy, renewable energy support, reverse osmosis, seawater, simulation, simulation decomposition, sourcing, specific power, streamflow forecasting, sustainability, system modeling, the pay-off method, turboprop, unlisted companies, urban solid waste system, water quality, water resource management, water resources, watershed management, weather modeling
Abstract

Summary: Effective environmental decision-making is often challenging and complex, where final solutions frequently possess inherently subjective political and socio-economic components. Consequently, complex sustainability applications in the "real world" frequently employ computational decision-making approaches to construct solutions to problems containing numerous quantitative dimensions and considerable sources of uncertainty. This volume includes a number of such applied computational analytics papers that either create new decision-making methods or provide innovative implementations of existing methods for addressing a wide spectrum of sustainability applications, broadly defined. The disparate contributions all emphasize novel approaches of computational analytics as applied to environmental decision-making and sustainability analysis - be this on the side of optimization, simulation, modelling, computational solution procedures, visual analytics, and/or information technologies.

6. Smart Sensor Technologies for IoT.

Author

Brida, Peter, Brida, Peter, Kertesz, Attila, Krejcar, Ondrej, and Selamat, Ali

Subjects
Technology: general issues, 5G, ACR, Bluetooth, DRONET, Fast Reroute, GNSS-RTK positioning, H.264/AVC, H.265/HEVC, IMU, Internet of Things, Internet of Things (IoT), IoT, IoT system, MANET, Multicast Repair (M-REP), QoE, ReRoute, Velostat, WSN, Wi-Fi, Wi-Fi sensing, bit repair (B-REP), classification, clustering, convolutional neural network, data classification, dead reckoning, depth-based routing, detection, electromagnetic scanning, energy-efficient, failure repair, few-shot learning, fingerprinting, free space optics, human activity recognition, indoor tracking, internet of things (IoT), localization, location-independent, magnetometer, measurement, meta learning, metric learning, mm-wave radars, mobile localization, multilayered network model, multiwavelength laser, n/a, optical code division multiple access (OCDMA), optical sensors, particle filter, point cloud, position detection, positioning, pressure sensor, quality of service differentiation, smart sensor, smart sensors, subjective assessment, traffic, underwater wireless sensor network, vehicle, vibration sensing, wireless optical networks, wireless technology
Abstract

Summary: The recent development in wireless networks and devices has led to novel services that will utilize wireless communication on a new level. Much effort and resources have been dedicated to establishing new communication networks that will support machine-to-machine communication and the Internet of Things (IoT). In these systems, various smart and sensory devices are deployed and connected, enabling large amounts of data to be streamed. Smart services represent new trends in mobile services, i.e., a completely new spectrum of context-aware, personalized, and intelligent services and applications. A variety of existing services utilize information about the position of the user or mobile device. The position of mobile devices is often achieved using the Global Navigation Satellite System (GNSS) chips that are integrated into all modern mobile devices (smartphones). However, GNSS is not always a reliable source of position estimates due to multipath propagation and signal blockage. Moreover, integrating GNSS chips into all devices might have a negative impact on the battery life of future IoT applications. Therefore, alternative solutions to position estimation should be investigated and implemented in IoT applications. This Special Issue, "Smart Sensor Technologies for IoT" aims to report on some of the recent research efforts on this increasingly important topic. The twelve accepted papers in this issue cover various aspects of Smart Sensor Technologies for IoT.