o accomplish relatively complex tasks of, such as, monitoring in vivo, information collected by different nano-sensors (NSs) is usually sent via multiple-access channels to fusion centers (FCs) for further processing....
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Precise polyp segmentation is vital for the early diagnosis and prevention of colorectal cancer(CRC)in clinical ***,due to scale variation and blurry polyp boundaries,it is still a challenging task to achieve satisfac...
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Precise polyp segmentation is vital for the early diagnosis and prevention of colorectal cancer(CRC)in clinical ***,due to scale variation and blurry polyp boundaries,it is still a challenging task to achieve satisfactory segmentation performance with different scales and *** this study,we present a novel edge-aware feature aggregation network(EFA-Net)for polyp segmentation,which can fully make use of cross-level and multi-scale features to enhance the performance of polyp ***,we first present an edge-aware guidance module(EGM)to combine the low-level features with the high-level features to learn an edge-enhanced feature,which is incorporated into each decoder unit using a layer-by-layer ***,a scale-aware convolution module(SCM)is proposed to learn scale-aware features by using dilated convolutions with different ratios,in order to effectively deal with scale ***,a cross-level fusion module(CFM)is proposed to effectively integrate the cross-level features,which can exploit the local and global contextual ***,the outputs of CFMs are adaptively weighted by using the learned edge-aware feature,which are then used to produce multiple side-out segmentation *** results on five widely adopted colonoscopy datasets show that our EFA-Net outperforms state-of-the-art polyp segmentation methods in terms of generalization and *** implementation code and segmentation maps will be publicly at https://***/taozh2017/EFANet.
In this paper,we combine decision fusion methods with four metaheuristic algorithms(Particle Swarm Optimization(PSO)algorithm,Cuckoo search algorithm,modification of Cuckoo Search(CS McCulloch)algorithm and Genetic al...
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In this paper,we combine decision fusion methods with four metaheuristic algorithms(Particle Swarm Optimization(PSO)algorithm,Cuckoo search algorithm,modification of Cuckoo Search(CS McCulloch)algorithm and Genetic algorithm)in order to improve the image *** proposed technique based on fusing the data from Particle Swarm Optimization(PSO),Cuckoo search,modification of Cuckoo Search(CS McCulloch)and Genetic algorithms are obtained for improving magnetic resonance images(MRIs)*** algorithms are used to compute the accuracy of each method while the outputs are passed to fusion *** order to obtain parts of the points that determine similar membership values,we apply the different rules of incorporation for these *** proposed approach is applied to challenging applications:MRI images,gray matter/white matter of brain segmentations and original black/white images Behavior of the proposed algorithm is provided by applying to different medical *** is shown that the proposed method gives accurate results;due to the decision fusion produces the greatest improvement in classification accuracy.
Salient object detection(SOD)in RGB and depth images has attracted increasing research *** RGB-D SOD models usually adopt fusion strategies to learn a shared representation from RGB and depth modalities,while few meth...
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Salient object detection(SOD)in RGB and depth images has attracted increasing research *** RGB-D SOD models usually adopt fusion strategies to learn a shared representation from RGB and depth modalities,while few methods explicitly consider how to preserve modality-specific *** this study,we propose a novel framework,the specificity-preserving network(SPNet),which improves SOD performance by exploring both the shared information and modality-specific ***,we use two modality-specific networks and a shared learning network to generate individual and shared saliency prediction *** effectively fuse cross-modal features in the shared learning network,we propose a cross-enhanced integration module(CIM)and propagate the fused feature to the next layer to integrate cross-level ***,to capture rich complementary multi-modal information to boost SOD performance,we use a multi-modal feature aggregation(MFA)module to integrate the modalityspecific features from each individual decoder into the shared *** using skip connections between encoder and decoder layers,hierarchical features can be fully *** experiments demonstrate that our SPNet outperforms cutting-edge approaches on six popular RGB-D SOD and three camouflaged object detection *** project is publicly available at https://***/taozh2017/SPNet.
Hypergraph Neural Networks (HGNNs) are increasingly utilized to analyze complex inter-entity relationships. Traditional HGNN systems, based on a hyperedge-centric dataflow model, independently process aggregation task...
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With the recent increase in the number of Internet of things(IoT) services, an intelligent scheduling strategy is needed to manage these services. In this paper, the problem of automatic choreography of microservices ...
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With the recent increase in the number of Internet of things(IoT) services, an intelligent scheduling strategy is needed to manage these services. In this paper, the problem of automatic choreography of microservices in IoT is explored. A type of reinforcement learning(RL) algorithm called TD3 is used to generate the optimal choreography policy under the framework of a softwaredefined network. The optimal policy is gradually reached during the learning procedure to achieve the goal, despite the dynamic characteristics of the network environment. The simulation results show that compared with other methods, the TD3 algorithm converges faster after a certain number of iterations, and it performs better than other non-RL algorithms by obtaining the highest reward. The TD3 algorithm can effciently adjust the traffic transmission path and provide qualified IoT services.
Flood extraction is a critical issue in remote sensing analysis. Accurate flood extraction faces challenges such as complex scenes, image differences across modalities, and a shortage of labeled samples. Traditional s...
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This study reports the performance of an InAs/GaSb type-Ⅱ superlattices(T2SLs) detector with nBn structure for mid-wavelength infrared(MWIR) detection. An electronic band structure of M barrier is calculated using 8-...
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This study reports the performance of an InAs/GaSb type-Ⅱ superlattices(T2SLs) detector with nBn structure for mid-wavelength infrared(MWIR) detection. An electronic band structure of M barrier is calculated using 8-band k·p method, and the nBn structure is designed with the M barrier. The detector is prepared by wet etching, which is simple in manufacturing process. X-ray diffraction(XRD) and atomic force microscope(AFM) characteristics indicate that the detector material has good crystal quality and surface morphology. The saturation bias of the spectral response measurements at 77 K is 300 m V, and the device is promising to work at a temperature of 140 K. Energy gap of T2SLs versus temperature is fitted by the Varshni curve, and zero temperature bandgap Eg(0), empirical coefficients α and β are extracted. A dark current density of 3.2×10-5A/cm2and differential resistance area(RA) product of 1.0×104Ω·cm2are measured at 77 K. The dominant mechanism of dark current at different temperature ranges is analyzed. The device with a 50% cutoff wavelength of 4.68 μm exhibits a responsivity of 0.6 A/W, a topside illuminated quantum efficiency of 20% without antireflection coating(ARC), and a detectivity of 9.17×1011cm·Hz1/2/W at 77 K and 0.3 V.
Wargame, as a tool to generate sample data for analysis and model training, has vast application in fields of training, command & control, and tactical research. Traditional wargame technologies greatly rely on hu...
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作者:
Lin, GuopingHarbin Institute of Technology
Ministry of Industry and Information Technology Key Lab of Micro-Nano Optoelectronic Information System School of Science Shenzhen518055 China
Microcavity Kerr frequency comb devices have been emerging as promising compact comb sources for a wide range of applications. Considering the oxide crystalline material platform, yttria-stabilized zirconia (YSZ) has ...
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