Search Results - (( java application path algorithm ) OR ( based interpolation learning algorithm ))
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Smart appointment organizer for mobile application / Mohd Syafiq Adam
Published 2009“…In creating this application, NetBeans IDE 6.5and Java Micro Edition (Java ME) are used. …”
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Visdom: Smart guide robot for visually impaired people
Published 2025“…The system architecture integrates ROS 2 on a Raspberry Pi, with TCP/IP connectivity enabling remote operation. An Android mobile application, developed using Java and the java.net.Socket library, provides an intuitive and accessible user interface for seamless interaction with the robot. …”
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Visdom: Smart guide robot for visually impaired people
Published 2025“…The system architecture integrates ROS 2 on a Raspberry Pi, with TCP/IP connectivity enabling remote operation. An Android mobile application, developed using Java and the java.net.Socket library, provides an intuitive and accessible user interface for seamless interaction with the robot. …”
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Prediction of rice biomass using machine learning algorithms
Published 2022“…Unmanned aerial vehicles (UAVs) may address these issues. Machine learning algorithms (MLs) can predict rice biomass from UAV-based vegetation indices (VIs). …”
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Adaptive GRNN for the modelling of dynamic plants
Published 2002“…These adaptation strategies are formulated based on the inherent advantageous features found in GRNN, such as highly localised pattern nodes, good interpolation capability, instantaneous learning, etc.. …”
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Ensemble learning using multi-objective optimisation for arabic handwritten words
Published 2021“…Most ensemble learning approaches are based on the assumption of linear combination, which is not valid due to differences in data types. …”
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Small target detection of Unmanned Aerial Vehicles based on GDWNet in the digital economy
Published 2025“…During the feature fusion stage, DySample is employed to generate content-aware offsets through learning. This approach effectively breaks the fixed interpolation rules of traditional upsampling methods, enabling more dynamic, flexible, and semantically rich upsampling of the input feature maps, thereby improving the quality of feature integration. …”
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Kaedah Kolorimetri untuk Analisis Kuantitatif Kapsaisin Secara Pencaman Corak Menggunakan Jaringan Neural Tiruan
Published 2002“…A three layer feed-forward neural network was used and network training was performed by using back propagation algorithm. For the determination of capsaicin, a neural network with 20 hidden neurons, 0.00001% learning rate and trained over 47,738 cycles produced the best result. …”
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Inversion of 2D and 3D DC resistivity imaging data for high contrast geophysical regions using artificial neural networks / Ahmad Neyamadpour
Published 2010“…These results show that,for all the arrays (2D and 3D) except 3D pole - dipole data, resilient propagation is the most efficient algorithm for training the DC resistivity data. In the case of 3D study of pole - dipole data, the gradient descent with momentum and an adaptive learning rate algorithm is found to be the most efficient paradigm. …”
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