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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Land Cover Generation from Optical Image
摘要： With growing needs of the global land cover information, high resolution datasets have been released, such as 30m-resolution GLC30 and NLCD 2011. However, these datasets cannot update in time when the ground-truth changes. In this paper, an automatic algorithm is proposed to generate land cover based on convolutional neural network (CNN) using optical image. A land cover translation framework is designed by utilizing the techniques of the fully convolutional network, and it can provide pixel-to-pixel translation of the image. The experiment is carried out on high resolution optical image sourcing from Google earth, and the results demonstrate that the proposed method is able to generate robust and reasonable prediction of the land cover. By testing at several different areas, this methods achieve the average accuracy at 70.2% for 8 types land cover comparing with NLCD 2011 datasets.
关键词： land cover,optical image,convolutional neural networks
更新于2025-09-04 15:30:14
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High-performance stretchable conductive nanocomposites: materials, processes, and device applications
摘要： Highly conductive and intrinsically stretchable electrodes are vital components of soft electronics such as stretchable transistors and circuits, sensors and actuators, light-emitting diode arrays, and energy harvesting devices. Many kinds of conducting nanomaterials with outstanding electrical and mechanical properties have been integrated with elastomers to produce stretchable conductive nanocomposites. Understanding the characteristics of these nanocomposites and assessing the feasibility of their fabrication are therefore critical for the development of high-performance stretchable conductors and electronic devices. We herein summarise the recent advances in stretchable conductors based on the percolation networks of nanoscale conductive fillers in elastomeric media. After discussing the material-, dimension-, and size-dependent properties of conductive fillers and their implications, we highlight various techniques that are used to reduce the contact resistance between the conductive filler materials. Furthermore, we categorize elastomer matrices with different stretchabilities and mechanical properties based on their polymeric chain structures. Then, we discuss the fabrication techniques of stretchable conductive nanocomposites toward their use in soft electronics. Finally, we provide representative examples of stretchable device applications and conclude the review with a brief outlook for future research.
关键词： soft electronics,conductive nanocomposites,stretchable conductors,percolation networks,elastomeric media
更新于2025-09-04 15:30:14
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[IEEE 2018 53rd International Universities Power Engineering Conference (UPEC) - Glasgow, United Kingdom (2018.9.4-2018.9.7)] 2018 53rd International Universities Power Engineering Conference (UPEC) - Load and PV Generation Forecast Based Cost Optimization for Nanogrids with PV and Battery
摘要： Power system resiliency and robustness became major concerns of the system operators and researchers after the introduction of the smart grid concept. The improvements in the battery storage systems (BSS) and the photovoltaic (PV) systems encourage power systems operators to enable the use of those systems in resiliency and robustness studies. Utilization of those systems not only contributes to the robustness of the power systems but also decrease the operational costs. There are several methods in literature to operate the grid systems with partitions of PV and BSS in the most economical way. Although these methods are straightforward and work fine, they can not guarantee the most economical result on a daily basis. In this paper, deep learning based PV generation and load forecasts are used to improve the results of optimization in terms of economic aspects in nano-grid applications. In the considered system, there are loads, PV generation units, BSS and grid connection. Bi-directional power flow is permitted between the main grid and the nano-grid system. The forecasting methodologies and used optimization algorithms will be explained in this paper.
关键词： demand-side management,smart grids,mathematical programming,recurrent neural networks,forecasting
更新于2025-09-04 15:30:14
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[IEEE 2018 25th IEEE International Conference on Image Processing (ICIP) - Athens, Greece (2018.10.7-2018.10.10)] 2018 25th IEEE International Conference on Image Processing (ICIP) - Enabling Saccade Latency Measurements with Consumer-Grade Cameras
摘要： Eye movements can be affected by a number of neurological, neuromuscular, and neurodegenerative disorders that are important to diagnose and track longitudinally. To enable unobtrusive tracking of disease progression, we tailored and evaluated a set of candidate eye-tracking algorithms to operate on video sequences obtained from an iPhone 6, for accurate and robust determination of the time between the presentation of a visual stimulus and the beginning of the eye movement toward the stimulus (saccade latency). Additionally, we proposed a model-based method to determine the onset of the eye movement and demonstrate that the associated residual normalized root-mean-squared error can be used to automatically flag saccade tracings that should not be included in further analysis. A variant of the iTracker algorithm performs most robustly and results in mean saccade latencies and associated standard deviations on iPhone recordings that are essentially the same as those obtained from simultaneous recordings using a high-end, high-speed camera. Our results suggest that accurate and robust saccade latency determination is feasible using consumer-grade cameras and therefore might enable unobtrusive tracking of neurodegenerative disease progression.
关键词： Eye tracking,saccade latency,mobile imaging,health monitoring,convolutional neural networks
更新于2025-09-04 15:30:14
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Deep learning—Using machine learning to study biological vision
摘要： Many vision science studies employ machine learning, especially the version called ‘‘deep learning.’’ Neuroscientists use machine learning to decode neural responses. Perception scientists try to understand how living organisms recognize objects. To them, deep neural networks offer benchmark accuracies for recognition of learned stimuli. Originally machine learning was inspired by the brain. Today, machine learning is used as a statistical tool to decode brain activity. Tomorrow, deep neural networks might become our best model of brain function. This brief overview of the use of machine learning in biological vision touches on its strengths, weaknesses, milestones, controversies, and current directions. Here, we hope to help vision scientists assess what role machine learning should play in their research.
关键词： object recognition,neural networks,deep learning,machine learning
更新于2025-09-04 15:30:14
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Fully convolutional networks in multimodal nonlinear microscopy images for automated detection of head and neck carcinoma: A pilot study
摘要： Background: A fully convolutional neural networks (FCN)-based automated image analysis algorithm to discriminate between head and neck cancer and non-cancerous epithelium based on nonlinear microscopic images was developed. Methods: Head and neck cancer sections were used for standard histopathology and co-registered with multimodal images from the same sections using the combination of coherent anti-Stokes Raman scattering, two-photon excited fluorescence, and second harmonic generation microscopy. The images analyzed with semantic segmentation using a FCN for four classes: cancer, normal epithelium, background, and other tissue types. Results: A total of 114 images of 12 patients were analyzed. Using a patch score aggregation, the average recognition rate and an overall recognition rate or the four classes were 88.9% and 86.7%, respectively. A total of 113 seconds were needed to process a whole-slice image in the dataset. Conclusion: Multimodal nonlinear microscopy in combination with automated image analysis using FCN seems to be a promising technique for objective differentiation between head and neck cancer and noncancerous epithelium.
关键词： digital pathology,semantic segmentation,diagnostics,second-harmonic generation,convolutional neural networks,two-photon excited fluorescence,spectral histopathology,image analysis,head and neck cancer,coherent anti-stokes Raman scattering
更新于2025-09-04 15:30:14
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Feature-based Classification of Protein Networks using Confocal Microscopy Imaging and Machine Learning
摘要： Fluorescence imaging has become a powerful tool to investigate complex subcellular structures such as cytoskeletal filaments. Advanced microscopes generate 3D imaging data at high resolution, yet tools for quantification of the complex geometrical patterns are largely missing. Here we present a computational framework to classify protein network structures. We developed a machine-learning method that combines state-of-the-art morphological quantification with protein network classification through morphologically distinct structural features enabling live imaging–based screening. We demonstrate applicability in a confocal laser scanning microscopy (CLSM) study differentiating protein networks of the FtsZ (filamentous temperature sensitive Z) family inside plant organelles (Physcomitrella patens).
关键词： FtsZ,machine learning,classification,protein networks,confocal microscopy
更新于2025-09-04 15:30:14
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[IEEE 2017 International Conference on Optical Network Design and Modeling (ONDM) - Budapest (2017.5.15-2017.5.18)] 2017 International Conference on Optical Network Design and Modeling (ONDM) - A probabilistic approach for failure localization
摘要： This work considers the problem of fault localization in transparent optical networks. The aim is to localize single-link failures by utilizing statistical machine learning techniques trained on data that describe the network state upon current and past failure incidents. In particular, a Gaussian Process (GP) classi?er is trained on historical data extracted from the examined network, with the goal of modeling and predicting the failure probability of each link therein. To limit the set of suspect links for every failure incident, the proposed approach is complemented with the utilization of a Graph-Based Correlation heuristic. The proposed approach is tested on a dataset generated for an OFDM-based optical network, demonstrating that it achieves a high localization accuracy. The proposed scheme can be used by service providers for reducing the Mean-Time-To-Repair of the failure.
关键词： Graph-Based Correlation,OFDM,Gaussian Process,transparent optical networks,fault localization
更新于2025-09-04 15:30:14
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Building two-dimensional metal–organic networks with tin
摘要： We show that Sn atoms combined with organic ligands can be used to build 2D coordination networks on Au(111) surfaces. The use of metal–organic bonding has been recognized as a powerful strategy for the generation, directly on solid surfaces, of 2D modular functional materials with potential application in catalysis, organic electronics, and magnetism. This has lead to the important progress observed in recent years in the engineering of a great variety of surface-supported 2D metal–organic networks (MONs). In this Communication, we report the first example of a surface-confined Sn-based MON. With only a few studies of surface-supported MONs based on p-block metals reported in the literature, the possibilities of building modular 2D MONs based on this group of metals remains almost unexplored to date. Tin, with formal oxidation states 2 and 4, forms a large diversity of metal–organic compounds (organotin compounds) which have a wide range of applications ranging from all sorts of biological activity to industrial catalytic processes. Organotin compounds have also attracted the attention of the condense-matter community, especially since stanene-cyanide was proposed as a candidate topological-insulator material. We thus investigated the synthesis, directly on Cu(100) and Au(111) surfaces, of Sn-based MONs using 7,7,8,8-tetracyanoquinodimethane (TCNQ) molecules as ligands.
关键词： Au(111) surfaces,TCNQ molecules,2D coordination networks,Sn-based MON,metal–organic bonding
更新于2025-09-04 15:30:14
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[Institution of Engineering and Technology 12th European Conference on Antennas and Propagation (EuCAP 2018) - London, UK (9-13 April 2018)] 12th European Conference on Antennas and Propagation (EuCAP 2018) - EM wave propagation experiment at e band and d band for 5G wireless systems: preliminary results
摘要： Preliminary results on an electromagnetic wave propagation experiment at E and D band are presented. The research activity is collaboration between Politecnico di Milano and the Huawei European Microwave Centre in Milan, which has recently installed short (325 m) terrestrial links operating at 73, 83, 148 and 156 GHz and connecting two buildings in the university main campus. Received power data are processed to identify and isolate rain events and quantify the fade induced by precipitation, AR. Moreover, AR is estimated taking advantage of ancillary data collected by a laser-based disdrometer collocated with the link transceivers. Preliminary results definitely point out the higher prediction accuracy achieved by exploiting the information on the rain drop size provided by the disdrometer.
关键词： Electromagnetic wave propagation,5G mobile networks,terrestrial links,measurement
更新于2025-09-04 15:30:14