- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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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) - Finger Ring Phased Antenna Array for 5G IoT and Sensor Networks at 28 GHz
摘要： In this paper, a circular phased antenna array has been constructed on the finger ring for the 28 GHz 5G communication systems. The antenna array has been verified in free space and with user’s hand phantom on three fingers by the simulations. It has been found that such antenna structure is resilient towards the user effects and has a stable coverage efficiency characteristics. The coverage efficiency of 80 % with the realized gain of 5 dBi has been observed when the ring simulated with the user’s hand. The correlation between high power loss density with antenna de-tuning has also been observed.
关键词： 5G,Wearable Antennas,Sensor Networks,28 GHz,Phased Array,IoT,Finger Ring Antenna,User effects,Antennas
更新于2025-09-04 15:30:14
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[IEEE 2018 IEEE Symposium on Computers and Communications (ISCC) - Natal, Brazil (2018.6.25-2018.6.28)] 2018 IEEE Symposium on Computers and Communications (ISCC) - Circuit Reallocation Strategy Aware of the Physical Layer Effects for Elastic Optical Networks
摘要： In this paper we propose a circuit reallocation strategy for elastic optical networks aware of the effects of the physical layer. The proposed strategy aims to reorganize active circuits so that new circuit requests that are pending blockage are established. The strategy was applied with the algorithms CS, KS-PC, KSP-RQoTO and MD-PC. The strategy was evaluate using the bandwidth blocking probability metric and components of the circuit blocking probability. The results were obtained using the real EON and NSFNet topologies. In terms of the probability of bandwidth blocking for the EON topology, for example, the reduction at the last load point was 81.01%, 89.2%, 80.93% and 78.27% for the CS, KS-PC, KSP-RQoTO and MD-PC algorithms, respectively. The blocking probability reduction for the NSFNet topology was 87%, 95.55%, 92.19% and 76.66%, for CS, KS-PC, KSP-RQoTO and MD-PC, also considering the last load point. The reductions in the probability of bandwidth blocking were due to the reallocations of circuits carried out by the strategy proposed in this work.
关键词： Circuit Reallocation,RMLSA,Elastic Optical Networks
更新于2025-09-04 15:30:14
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[IEEE 2018 Innovations in Intelligent Systems and Applications Conference (ASYU) - Adana, Turkey (2018.10.4-2018.10.6)] 2018 Innovations in Intelligent Systems and Applications Conference (ASYU) - Image Classification of Aerial Images Using CNN-SVM
摘要： Image classification is a very easy task for humans. Even a three years old child can classify an image instantly and without any doubt. However, teaching computers classifying images has been a working area for researchers for a long time because of the intrinsic difficulties of the task for computers. With the rise of deep learning, it has been possible to get better classification performance than before. In this work, we evaluated the performance of convolutional neural network combined with support vector machine for classifying aerial images based on presence of a vehicle.
关键词： unmanned aerial vehicle,vehicle detection,convolutional neural networks,aerial image,Support vector machines,image classification
更新于2025-09-04 15:30:14
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[IEEE 2018 IEEE 7th Global Conference on Consumer Electronics (GCCE) - Nara, Japan (2018.10.9-2018.10.12)] 2018 IEEE 7th Global Conference on Consumer Electronics (GCCE) - CNN-Based Boat Detection Model for Alert System Using Surveillance Video Camera
摘要： In Tokyo, various boats pass through the canal on the bayside. The loud sound created by these boats may cause some stress to the residents in that area. We propose a boat detection model based on convolutional neural networks (CNNs) using VGG19 that is trained using several types of boat pictures. Our proposed model aims to detect the type of boat passing through the canal using images obtained from the surveillance video camera. We ?nally achieve a practical result as F1-score of 0.70 by the proposed model.
关键词： Boat detection,Convolutional Neural Networks,Image Recognition,Boat classification,Surveillance Video Camera
更新于2025-09-04 15:30:14
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[IEEE 2018 IEEE 7th Global Conference on Consumer Electronics (GCCE) - Nara, Japan (2018.10.9-2018.10.12)] 2018 IEEE 7th Global Conference on Consumer Electronics (GCCE) - Automatic Generation of Facial Expression Using Generative Adversarial Nets
摘要： With the spread of digital cameras, smart phones, and SNS, the number facial images of people have increased. Facial expression generation from a single facial image has been widely applied to the fields of entertainment and social communication. Many approaches that apply machine learning techniques have been developed. In our previous study, we developed a makeup simulator system. However, this system is incapable of changing the impression of a cosmetic face based on changes in facial expression; in addition, another challenge is that the user cannot see the impression of makeup dynamically and objectively. Therefore, in this study, we generate static facial expression images from a natural (expressionless) image by using generative adversarial networks, which is critical to the research on dynamic facial expression change. Our experimental results demonstrate that our approach achieves the best expression image.
关键词： Generative Adversarial Nets,image,Image-to-Image Translation with Conditional Adversarial Networks,facial expression
更新于2025-09-04 15:30:14
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[IEEE 2018 Second International Conference on Advances in Electronics, Computers and Communications (ICAECC) - Bangalore (2018.2.9-2018.2.10)] 2018 Second International Conference on Advances in Electronics, Computers and Communications (ICAECC) - Determination of Absolute Heart Beat from Photoplethysmographic Signals in the Presence of Motion Artifacts
摘要： In Wireless Body Area Networks (WBANs), accurate monitoring of heart rate (HR) using Photoplethysmography (PPG) signals is always a difficult task, especially when the subjects are under radical exercises. This is due to the signals corrupted by severely strong Motion Artifacts (MA) caused by the subject’s body movements. In this work, a novel approach has been proposed consisting of signal decomposition for denoising using principal component analysis (PCA), spare signal reconstruction (SSR), peak detection and tracking and support vector machine (SVM) classifier for accurate estimation of HR, based on the wrist type PPG signals. With this approach, we are able to achieve high accuracy and also, it is strong enough to remove MA. Experiments were conducted on 12 subjects and their datasets are obtained from 2015 IEEE Signal Processing CUP, running on a threadmill with varying speeds ranging from 0 to a maximum speed of 15 km/hour. From the results, it is observed that the average absolute error of heart rate estimation is 1.66 beats per minute (BPM).
关键词： SVM classifier,PCA,HR,Wireless Body Area Networks (BAN),SSR,Accelerometer,PPG
更新于2025-09-04 15:30:14
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[IEEE 2018 IEEE International Conference on Consumer Electronics - Asia (ICCE-Asia) - JeJu, Korea (South) (2018.6.24-2018.6.26)] 2018 IEEE International Conference on Consumer Electronics - Asia (ICCE-Asia) - Accurate License Plate Recognition and Super-Resolution Using a Generative Adversarial Networks on Traffic Surveillance Video
摘要： Automatic License Plate Recognition (ALPR) is one of the most important methods of intelligent traffic surveillance applications. Some existing ALPR systems are developed for near-frontal plate images in a single lane. However, most surveillance cameras have a challenging environment: small size object, poor resolution and blurred image. We propose a new method that can be applied in the ALPR challenged environments by using super-resolution (SR) module based on Generative Adversarial Networks (GAN). We also used the state-of-the-art and real-time object detection method, You Only Look Once (YOLO), for license plate detection and character recognition. We collected a challenging dataset at low resolution and small object less than 60*60 size and evaluate our approach on it. The achieved mean accuracy of recognition of license plate is above 2% better than other methods in our dataset. Our implementation demonstrate the superiority over the state-of-the-art.
关键词： Visual Surveillance,Generative Adversarial Networks,License Plate Recognition,Super-Resolution
更新于2025-09-04 15:30:14
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[IEEE 2018 International Conference on Current Trends towards Converging Technologies (ICCTCT) - Coimbatore, India (2018.3.1-2018.3.3)] 2018 International Conference on Current Trends towards Converging Technologies (ICCTCT) - Processing Retinal Images to Discover Diseases
摘要： The retina of a human eye consists of billion of photosensitive cells (rods and cones) and alternative nerve cells that acquire and arrange visual information. The retina of a human eye is a thin tissue layer on the inside back wall of your eye. Three of the are Diabetic retinal diseases most Retinopathy, Glaucoma, and Cataract. The world is presently experiencing an epidemic of Diabetic Retinopathy (DR). Current predictions draw an estimation of doubling of the number affected from the current 170 million to an estimated 367 million by 2030. We propose a system wherein we extract blood vessels of the retina to detect eye diseases. Manually extracting the blood vessels of the human retina is a time-consuming task, and thus an automation of this process results in easy implementation of the work. This paper aims to design and consequently implement deep convolutional neural networks to identify the presence of an exudate, and thereby classify it into Diabetic Retinopathy, Glaucoma, and/or Cataract.
关键词： Computer vision,Glaucoma,Diabetic Retinopathy,Cataract,Convolutional Neural Networks,Retinal disease detection,CNN
更新于2025-09-04 15:30:14
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[IEEE 2018 IEEE International Conference on Intelligent Transportation Systems (ITSC) - Maui, HI, USA (2018.11.4-2018.11.7)] 2018 21st International Conference on Intelligent Transportation Systems (ITSC) - Real-time Stereo Reconstruction Failure Detection and Correction using Deep Learning
摘要： This paper introduces a stereo reconstruction method that besides producing accurate results in real-time, is capable to detect and conceal possible failures caused by one of the cameras. A classification of stereo camera sensor faults is initially introduced, the most common types of defects being highlighted. We next present a stereo camera failure detection method in which various additional checks are being introduced, with respect to the aforementioned error classification. Furthermore, we propose a novel error correction method based on CNNs (convolutional neural networks) that is capable of generating reliable disparity maps by using prior information provided by semantic segmentation in conjunction with the last available disparity. We highlight the efficiency of our approach by evaluating its performance in various driving scenarios and show that it produces accurate disparities on images from Kitti stereo and raw datasets while running in real-time on a regular GPU.
关键词： error correction,convolutional neural networks,stereo reconstruction,failure detection,semantic segmentation
更新于2025-09-04 15:30:14
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Wideband Dual-Polarized Multiple Beam-Forming Antenna Arrays
摘要： Wideband multi-beam antenna arrays based on three-beam Butler matrices are presented in this paper. The proposed beam-forming arrays are particularly suited to increasing the capacity of 4G long-term evolution (LTE) base stations. Although dual-polarized arrays are widely used in LTE base stations, analogue beam-forming arrays have not been realized before, due to the huge challenge of achieving wide operating bandwidth and stable array patterns. To tackle these problems, for the first time, we present a novel wideband multiple beam-forming antenna array based on Butler matrices. The described beam-forming networks produce three beams but the methods are applicable to larger networks. The essential part of the beam-forming array is a wideband three-beam Butler matrix, which comprises quadrature couplers and fixed wideband phase shifters. Wideband quadrature and phase shifters are developed using striplines, which provide the required power levels and phase differences at the outputs. To achieve the correct beamwidth and to obtain the required level of crossover between adjacent beams, beam-forming networks consisting of augmented three-beam Butler matrices using power dividers are presented to expand the number of output ports from three to five or six. Dual-polarized, three-beam antenna arrays with five and six elements covering LTE band are developed. Prototypes comprising beam-forming networks and arrays are tested according to LTE base station specification. The test results show close agreement with the simulation ones and compliance with LTE requirements. The designs presented are applicable to a wide range of wideband multi-beam arrays.
关键词： Butler matrix,quadrature couplers,dual-linear polarization,multi-beam,LTE base stations,wideband,beam-forming networks,phase shifters,Antenna arrays
更新于2025-09-04 15:30:14