Automated detection and classification of brain abnormalities, such as tumors, is essential for understanding and tracking patient progress. In this study, advanced machine learning methods were applied to enhance the...
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The term 'Vehicle Ad hoc Network' (VANET) refers to a system in which a collection of non-stationary or stationary vehicles share a wireless connection. Until recently, VANETs were primarily used to improve th...
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Machine learning can effectively accelerate the runtime of a computer-generated ***,the angular spectrum method and single fast Fresnel transform-based machine learning acceleration algorithms are still limited in the...
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Machine learning can effectively accelerate the runtime of a computer-generated ***,the angular spectrum method and single fast Fresnel transform-based machine learning acceleration algorithms are still limited in the field-of-view angle of *** this paper,we propose an efficient method for the fast generation of large field-of-view holograms combining stochastic gradient descent(SGD),neural networks,and double-sampling Fresnel diffraction(DSFD).Compared with the traditional Gerchberg-Saxton(GS)algorithm,the DSFD-SGD algorithm has better reconstruction *** neural network can be automatically trained in an unsupervised manner with a training set of target images without labels,and its combination with the DSFD can improve the optimization speed *** proposed DSFD-Net method can generate 2000-resolution holograms in 0.05 *** feasibility of the proposed method is demonstrated with simulations and experiments.
Deep learning algorithms often require high-quality datasets, but public datasets can be less effective for specific applications like visual robotic arm grasping. Generating private datasets traditionally involves ti...
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Considering a battery as the energy source for steady average current and an ultracapacitor as the dynamic energy buffer, this paper proposes a novel control strategy based on average current demand. The methodology a...
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This paper presents the design and simulation of a plasmonic refractive index (RI) sensor and a temperature sensor. The suggested design comprises a MIM waveguide integrated with a grill-shaped rectangular cavity. Sim...
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ISBN:
(数字)9798331511371
ISBN:
(纸本)9798331511388
This paper presents the design and simulation of a plasmonic refractive index (RI) sensor and a temperature sensor. The suggested design comprises a MIM waveguide integrated with a grill-shaped rectangular cavity. Simulations were performed for two configurations: one with a solitary cavity and another with two cavities. The RI sensitivity was determined to be 1681.42 nm/RIU. In addition, temperature sensitivity was evaluated by employing two dielectric materials, namely ethanol and polydimethylsiloxane, which exhibited temperature sensitivities of 0.475 nm/°C and 0.67 nm/°C, respectively. The plasmonic sensor being suggested exhibits promising capabilities for utilization in nanosensing and industrial environments.
Urban traffic congestion necessitates innovative monitoring and control solutions. This study leverages UAV footage and deep learning techniques to classify and analyze traffic density levels autonomously. By employin...
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Artificial intelligence (AI) is expected to significantly enhance radio resource management (RRM) in sixth-generation (6G) networks. However, the lack of explainability in complex deep learning (DL) models poses a cha...
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We present a new fluctuation-dissipation relation that shows how quantum noise transforms under engineered nonlinear dissipation found in many important nonlinear optical devices and validate the theory with experimen...
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Rapid electronic device development requires more complicated and densely packed PCB designs. These systems need properly placed and connected electrical components for best performance and reliability. Complexity and...
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