This paper proposes a method that combines a hardware description language and Random Forests theory, to develop a motion recognition embedded system. To validate this system, the Ninapro database DB2 was used as trai...
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This paper presents a novel approach to estimate and compensate for the misalignment between the Inertial Measurement Unit (IMU) and Doppler Velocity Log (DVL) sensors. Estimating the location and attitude of an ROV u...
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The process for producing intelligence is traditionally represented by a series of steps forming a cycle. Collection is one of these stages and is characterized by the application of a set of disciplines to obtain inf...
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We analyze wholesale datasets from Indonesian Automobile Industry Data for electric cars in Indonesia using statistical analysis to predict the electric cars used in the future. We apply a linear regression approach t...
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Co-presence is the index that indicates the degree to which the observer believes he/she is not alone and secluded. The representation of avatars in virtual environments (VE) having an effect on co-presence was report...
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In recent years, 3DCG-related industries have grown rapidly and the demand for 3DCG content has increased. However, 3DCG production requires special skills and a lot of time. In particular, the creation of background ...
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Recently, energy storage devices (ESDs) have been introduced to railway vehicles to operate even in an emergency case, such as a power outage. However, there have been no proposals for simultaneous design methods of p...
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In this study, we propose a method for enabling humans to initialize a neural network before training. This is a novel way of involving humans in neural network training. So far, neural networks learn very well from s...
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ISBN:
(数字)9798350388077
ISBN:
(纸本)9798350388084
In this study, we propose a method for enabling humans to initialize a neural network before training. This is a novel way of involving humans in neural network training. So far, neural networks learn very well from structured data. However, human knowledge, common sense, and experiences are not necessarily easy to express as structured data. This limits the ability of neural networks to learn from humans. This study attempts to fill the gap and enhance the learning ability of neural networks. This paper explains the structure of the neural network that supports this objective and the results of the initial experiments in transferring human knowledge to neural networks.
A long period grating (LPG) operating in the visible wavelength range functionalised with sensitive dyes is reported. Two different sensing mechanisms transmission based, using intensity ratio;and refractive index cha...
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A dielectric Mie-resonant nanoantenna is capable of controlling the directionality of the emission from nearby quantum emitters through the excitation of multiple degenerate Mie resonances. A crystalline silicon nanos...
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