Search

This editorial introduces the Special Issue, entitled "Deep Learning Applications with Practical Measured Results in Electronics Industries", of Electronics. Topics covered in this issue include four main parts: (I) environmental information analyses and predictions, (II) unmanned aerial vehicle (UAV) and object tracking applications, (III) measurement and denoising techniques, and (IV) recommendation systems and education systems. Four papers on environmental information analyses and predictions are as follows: (1) "A Data-Driven Short-Term Forecasting Model for Offshore Wind Speed Prediction Based on Computational Intelligence" by Panapakidis et al.; (2) "Multivariate Temporal Convolutional Network: A Deep Neural Networks Approach for Multivariate Time Series Forecasting" by Wan et al.; (3) "Modeling and Analysis of Adaptive Temperature Compensation for Humidity Sensors" by Xu et al.; (4) "An Image Compression Method for Video Surveillance System in Underground Mines Based on Residual Networks and Discrete Wavelet Transform" by Zhang et al. Three papers on UAV and object tracking applications are as follows: (1) "Trajectory Planning Algorithm of UAV Based on System Positioning Accuracy Constraints" by Zhou et al.; (2) "OTL-Classifier: Towards Imaging Processing for Future Unmanned Overhead Transmission Line Maintenance" by Zhang et al.; (3) "Model Update Strategies about Object Tracking: A State of the Art Review" by Wang et al. Five papers on measurement and denoising techniques are as follows: (1) "Characterization and Correction of the Geometric Errors in Using Confocal Microscope for Extended Topography Measurement. Part I: Models, Algorithms Development and Validation" by Wang et al.; (2) "Characterization and Correction of the Geometric Errors Using a Confocal Microscope for Extended Topography Measurement, Part II: Experimental Study and Uncertainty Evaluation" by Wang et al.; (3) "Deep Transfer HSI Classification Method Based on Information Measure and Optimal Neighborhood Noise Reduction" by Lin et al.; (4) "Quality Assessment of Tire Shearography Images via Ensemble Hybrid Faster Region-Based ConvNets" by Chang et al.; (5) "High-Resolution Image Inpainting Based on Multi-Scale Neural Network" by Sun et al. Two papers on recommendation systems and education systems are as follows: (1) "Deep Learning-Enhanced Framework for Performance Evaluation of a Recommending Interface with Varied Recommendation Position and Intensity Based on Eye-Tracking Equipment Data Processing" by Sulikowski et al. and (2) "Generative Adversarial Network Based Neural Audio Caption Model for Oral Evaluation" by Zhang et al. [ABSTRACT FROM AUTHOR]

This editorial introduces the Special Issue, entitled "Deep Learning (DL) Techniques for Agronomy Applications", of Agronomy. Topics covered in this issue include three main parts: (I) DL-based image recognition techniques for agronomy applications, (II) DL-based time series data analysis techniques for agronomy applications, and (III) behavior and strategy analysis for agronomy applications. Three papers on DL-based image recognition techniques for agronomy applications are as follows: (1) "Automatic segmentation and counting of aphid nymphs on leaves using convolutional neural networks," by Chen et al.; (2) "Estimating body condition score in dairy cows from depth images using convolutional neural networks, transfer learning, and model ensembling techniques," by Alvarez et al.; and (3) "Development of a mushroom growth measurement system applying deep learning for image recognition," by Lu et al. One paper on DL-based time series data analysis techniques for agronomy applications is as follows: "LSTM neural network based forecasting model for wheat production in Pakistan," by Haider et al. One paper on behavior and strategy analysis for agronomy applications is as follows: "Research into the E-learning model of agriculture technology companies: analysis by deep learning," by Lin et al. [ABSTRACT FROM AUTHOR]

This editorial introduces the special issue, entitled "Applications of Internet of Things", of Symmetry. The topics covered in this issue fall under four main parts: (I) communication techniques and applications, (II) data science techniques and applications, (III) smart transportation, and (IV) smart homes. Four papers on sensing techniques and applications are included as follows: (1) "Reliability of improved cooperative communication over wireless sensor networks", by Chen et al.; (2) "User classification in crowdsourcing-based cooperative spectrum sensing", by Zhai and Wang; (3) "IoT's tiny steps towards 5G: Telco's perspective", by Cero et al.; and (4) "An Internet of things area coverage analyzer (ITHACA) for complex topographical scenarios", by Parada et al. One paper on data science techniques and applications is as follows: "Internet of things: a scientometric review", by Ruiz-Rosero et al. Two papers on smart transportation are as follows: (1) "An Internet of things approach for extracting featured data using an AIS database: an application based on the viewpoint of connected ships", by He et al.; and (2) "The development of key technologies in applications of vessels connected to the Internet", by Tian et al. Two papers on smart home are as follows: (1) "A novel approach based on time cluster for activity recognition of daily living in smart homes", by Liu et al.; and (2) "IoT-based image recognition system for smart home-delivered meal services", by Tseng et al. [ABSTRACT FROM AUTHOR]