- 标题
- 摘要
- 关键词
- 实验方案
- 产品
过滤筛选
- 2015
- Bessel Function
- Coupling Coefficient
- Fusion temperature and Elongation speed
- Physics
- UIN Suska Riau
- University of Riau
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[American Society of Agricultural and Biological Engineers 2017 Spokane, Washington July 16 - July 19, 2017 - ()] 2017 Spokane, Washington July 16 - July 19, 2017 - Design and modeling of grain impact sensor utilizing two crossed polyvinylidene fluoride films
摘要： In order to reduce the unavoidable grain losses during harvesting, the combine harvester’s operational parameters should be adjusted accordingly. So, it is important to develop a real-time sensor which can monitor the grain losses. A grain impact sensor utilizing crossed piezoelectric polyvinylidene fluoride (PVDF) films as sensitive material is described. This sensor is composed of two crossed layers of sensor unit arrays, a damping layer and a support plate. The two layers are insulated from each other but can detect the impact simultaneously. The sensor unit arrays of those two layers are perpendicular and the sensor units in each layer are independent and parallel. Each sensor unit has its independent signal processing circuit, which is composed of charge amplifier, band-pass filter, envelope detector and voltage comparator. Two signals from two layers presented a two-dimensional impact position information through multi-sensor fusion technology. The sensor can obtain the spatial distribution of grain loss accurately to reduce the error-recognition ratio. Moreover, the grain impact sensor was simulated by finite element method to obtain the best number and size of the sensor units for higher sensitivity, detection speed, stress transfer efficiency, deformation transfer efficiency.
关键词： double layers,grain impact sensor,multi-sensor fusion,grain loss detecting,PVDF film
更新于2025-09-23 15:22:29
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Deep Belief Network for Spectral–Spatial Classification of Hyperspectral Remote Sensor Data
摘要： With the development of high-resolution optical sensors, the classification of ground objects combined with multivariate optical sensors is a hot topic at present. Deep learning methods, such as convolutional neural networks, are applied to feature extraction and classification. In this work, a novel deep belief network (DBN) hyperspectral image classification method based on multivariate optical sensors and stacked by restricted Boltzmann machines is proposed. We introduced the DBN framework to classify spatial hyperspectral sensor data on the basis of DBN. Then, the improved method (combination of spectral and spatial information) was verified. After unsupervised pretraining and supervised fine-tuning, the DBN model could successfully learn features. Additionally, we added a logistic regression layer that could classify the hyperspectral images. Moreover, the proposed training method, which fuses spectral and spatial information, was tested over the Indian Pines and Pavia University datasets. The advantages of this method over traditional methods are as follows: (1) the network has deep structure and the ability of feature extraction is stronger than traditional classifiers; (2) experimental results indicate that our method outperforms traditional classification and other deep learning approaches.
关键词： classification,feature extraction,multi-sensor fusion,remote sensors,deep learning,hyperspectral image
更新于2025-09-23 15:22:29
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[IEEE 2018 IEEE International Conference on Imaging Systems and Techniques (IST) - Krakow, Poland (2018.10.16-2018.10.18)] 2018 IEEE International Conference on Imaging Systems and Techniques (IST) - Colour Constancy for Image of Non-Uniformly Lit Scenes
摘要： This paper presents a colour constancy algorithm for images of scenes lit by non-uniform light sources. The proposed method determines number of colour regions within the image using a histogram-based algorithm. It then applies the K-means++ algorithm on the input image, dividing the image into its segments. The proposed algorithm computes the normalized average absolute difference (NAAD) for each segment’s coefficients and uses it as a measure to determine if the segment’s coefficients have sufficient colour variations. The initial colour constancy adjustment factors for each segment with sufficient colour variation is calculated based on the principle that the average values of colour components of the image are achromatic. The colour constancy adjustment weighting factors (CCAWF) for each pixel of image are determined by fusing the CCAWFs of the segments’ with sufficient colour variations, weighted by their normalized Euclidian distance of the pixel from the center of the segments. Experimental results were generated using both indoor and outdoor benchmark images from the scene illuminated by single or multiple illuminants. Results show that the proposed method outperforms the state of the art techniques subjectively and objectively.
关键词： multi-illuminants,fusion,k-means segmentation,colour constancy
更新于2025-09-23 15:22:29
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[IEEE 2018 IEEE International Conference on Imaging Systems and Techniques (IST) - Krakow (2018.10.16-2018.10.18)] 2018 IEEE International Conference on Imaging Systems and Techniques (IST) - A Cortical Based Diagnosis System for MCI Based on sMRI Features Fusion
摘要： Alzheimer’s disease (AD) is one of the most neurodegenerative disorders that target central nervous system with statistical results of more than 5 million sufferers among the Americans. According to the literature, discovering the disease in its early stage is considered as one of the main obstacles that face the scientists. The difficulty of this diagnostic task relied on a number of reasons including the variability of the disease’s effect among its patients. This paper aims to study mild cognitive impairment (MCI), the type of impairment that found to increase the factor of achieving to AD. According to this study a cortical regions based computer-aided diagnosis (CAD) system can be presented that in turn serve the early diagnosis of AD. This goal is achieved by visualizing the personalized diagnosis of the MCI in each of the cortical regions separately. For this purpose, the proposed CAD system goes into four main stages: 1-preprocessing and cortex extraction, 2-cortex reconstruction and shape-based feature extraction, 3-feature fusing, and 4-local/regional diagnosis followed by global diagnosis step. Evaluating the proposed system shows promising results with a maximum performance of 86.30%, 88.33%, and 84.88% for accuracy, specificity, and sensitivity, respectively.
关键词： cortical regions,MCI,AD,feature fusion,sMRI
更新于2025-09-23 15:22:29
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[IEEE OCEANS 2018 MTS/IEEE Charleston - Charleston, SC, USA (2018.10.22-2018.10.25)] OCEANS 2018 MTS/IEEE Charleston - Improvement of the video camera system mounted on a balloon for supporting the visual census of river dolphins
摘要： In order to increase the surfacing dolphin’s detection probability by the balloon camera system similar to that of a human observer, improvements were made in the camera system on the balloon [1]. Followed by test on ground, fusion census of both acoustic and visual census with the improved camera system on the balloon was conducted at the same experiment site as 2016 for three days from 6 to 8 February, 2018. The performance of the improved balloon camera system for supporting the fusion census was well demonstrated, even though the balloon census could be conducted only when the wind direction was aligned with the boat cruise direction. The improved system could cover previous system drawbacks and could also capture the individual dolphin’s features such as migration behavior of the dolphin with a calf, measurement of body length of the small calf, etc.
关键词： Visual census,Ganges river dolphin,Acoustic census,River dolphin,Fusion census,Balloon
更新于2025-09-23 15:22:29
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An interprojection sensor fusion approach to estimate blocked projection signal in synchronized moving grid-based CBCT system
摘要： Purpose: A preobject grid can reduce and correct scatter in cone beam computed tomography (CBCT). However, half of the signal in each projection is blocked by the grid. A synchronized moving grid (SMOG) has been proposed to acquire two complimentary projections at each gantry position and merge them into one complete projection. That approach, however, suffers from increased scanning time and the technical difficulty of accurately merging the two projections per gantry angle. Herein, the authors present a new SMOG approach which acquires a single projection per gantry angle, with complimentary grid patterns for any two adjacent projections, and use an interprojection sensor fusion (IPSF) technique to estimate the blocked signal in each projection. The method may have the additional benefit of reduced imaging dose due to the grid blocking half of the incident radiation. Methods: The IPSF considers multiple paired observations from two adjacent gantry angles as approximations of the blocked signal and uses a weighted least square regression of these observations to finally determine the blocked signal. The method was first tested with a simulated SMOG on a head phantom. The signal to noise ratio (SNR), which represents the difference of the recovered CBCT image to the original image without the SMOG, was used to evaluate the ability of the IPSF in recovering the missing signal. The IPSF approach was then tested using a Catphan phantom on a prototype SMOG assembly installed in a bench top CBCT system. Results: In the simulated SMOG experiment, the SNRs were increased from 15.1 and 12.7 dB to 35.6 and 28.9 dB comparing with a conventional interpolation method (inpainting method) for a projection and the reconstructed 3D image, respectively, suggesting that IPSF successfully recovered most of blocked signal. In the prototype SMOG experiment, the authors have successfully reconstructed a CBCT image using the IPSF-SMOG approach. The detailed geometric features in the Catphan phantom were mostly recovered according to visual evaluation. The scatter related artifacts, such as cupping artifacts, were almost completely removed. Conclusions: The IPSF-SMOG is promising in reducing scatter artifacts and improving image quality while reducing radiation dose.
关键词： moving grids,scatter correction,interpolation,sensor fusion,geometric model,SMOG,dose reduction,CBCT
更新于2025-09-23 15:22:29
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Single-image low-light enhancement via generating and fusing multiple sources
摘要： Imperfect lightness conditions usually lower the visual quality of an image by bringing in unclear image details and poor image contrast. Traditional low-light enhancement models based on one single input are often limited in avoiding the effect of over-enhancement or under-enhancement. Models based on fusing multiple input sources usually perform well in relieving this issue, as they can harmonize the complementary visual appearances of a same scene provided by different sources. Nevertheless, these models still have difficulty in dealing with the situation that only one input is at hand, which usually happens in many practical situations. In this paper, we propose a low-light enhancement model that artificially enriches input sources and then seamlessly fuses them. Specifically, with an input image, we first generate multiple enhanced images based on a lightness-aware camera response model. These images are then fused at mid-level based on a patch-based image decomposition model. To validate our model, we conduct qualitative and quantitative comparisons with several state-of-the-art single-source and multi-source models on a collection of real-world images. Experimental results show that our model better improves the image quality in terms of visual naturalness and aesthetics.
关键词： Fusion,Image enhancement,Low-light image
更新于2025-09-23 15:21:21
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Feature-Level Fusion of Landsat 8 Data and SAR Texture Images for Urban Land Cover Classification
摘要： Each of the urban land cover types has unique thermal pattern. Therefore, thermal remote sensing can be used over urban areas for indicating temperature differences and comparing the relationships between urban surface temperatures and land cover types. On the other hand, synthetic-aperture radar (SAR) sensors are playing an increasingly important role in land cover classi?cation due to their ability to operate day and night through cloud cover, and capturing the structure and dielectric properties of the earth surface materials. In this research, a feature-level fusion of SAR image and all bands (optical and thermal) of Landsat 8 data is proposed in order to modify the accuracy of urban land cover classi?cation. In the proposed object-based image analysis algorithm, segmented regions of both Landsat 8 and SAR images are utilized for performing knowledge-based classi?cation based on the land surface temperatures, spectral relationships between thermal and optical bands, and SAR texture features measured in the gray-level co-occurrence matrix space. The evaluated results showed the improvements of about 2.48 and 0.06 for overall accuracy and kappa after performing feature-level fusion on Landsat 8 and SAR data.
关键词： Thermal remote sensing,SAR data,Object-based image analysis,Textural features,Feature-level fusion
更新于2025-09-23 15:21:21
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Impact of asymmetries on fuel performance in inertial confinement fusion
摘要： Low-mode asymmetries prevent effective compression, con?nement, and heating of the fuel in inertial con?nement fusion (ICF) implosions, and their control is essential to achieving ignition. Ion temperatures (Tion) in ICF experiments are inferred from the broadening of primary neutron spectra. Directional motion (?ow) of the fuel at burn also impacts broadening and will lead to arti?cially in?ated “Tion” values. Flow due to low-mode asymmetries is expected to give rise to line-of-sight variations in measured Tion. We report on intentionally asymmetrically driven experiments at the OMEGA laser facility designed to test the ability to accurately predict and measure line-of-sight differences in apparent Tion due to low-mode asymmetry-seeded ?ows. Contrasted to CHIMERA and xRAGE simulations, the measurements demonstrate how all asymmetry seeds have to be considered to fully capture the ?ow ?eld in an implosion. In particular, ?ow induced by the stalk that holds the target is found to interfere with the seeded asymmetry. A substantial stalk-seeded asymmetry in the areal density of the implosion is also observed.
关键词： CHIMERA,xRAGE simulations,OMEGA laser facility,inertial con?nement fusion,ion temperatures,low-mode asymmetries
更新于2025-09-23 15:21:21
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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) - A Non Local Multifocus Image Fusion Scheme for Dynamic Scenes
摘要： In order to overcome the limited depth of field of usual photographic devices, a common approach is multi-focus image fusion (MFIF). From a stack of images acquired with different focus settings, these methods aim at fusing the content of the images of the stack to produce a final image that is sharp everywhere. Such methods can be very efficient, but when a global geometrical alignment of images is out-of-reach, or when some objects are moving, the final image shows ghosts or other artefacts. In this paper, we propose a generic method to overcome these limitations. We first select a reference image, and then, for each image of the stack, reconstruct an image that shares the geometry of the reference and the sharpness content of the image at hand. The reconstruction is achieved thanks to a specially crafted modification of the PatchMatch algorithm, adapted to blurred images, and to a dedicated postprocessing for correcting reconstruction errors. Then, from the new image stack, MFIF is performed to produce a sharp result. We show the efficiency of the result on a database of challenging cases of hand-held shots containing moving objects.
关键词： focus stacking,computational photography,PatchMatch,non-local methods,Multifocus image fusion
更新于2025-09-23 15:21:21