بدائل البحث:
complement system » component system (توسيع البحث), complex system (توسيع البحث)
method algorithm » network algorithm (توسيع البحث), means algorithm (توسيع البحث), mean algorithm (توسيع البحث)
system algorithm » custom algorithm (توسيع البحث), sssgm algorithm (توسيع البحث), systematic algorithm (توسيع البحث)
coding algorithm » cosine algorithm (توسيع البحث), modeling algorithm (توسيع البحث), finding algorithm (توسيع البحث)
level coding » level according (توسيع البحث), level modeling (توسيع البحث), level using (توسيع البحث)
element » elements (توسيع البحث)
complement system » component system (توسيع البحث), complex system (توسيع البحث)
method algorithm » network algorithm (توسيع البحث), means algorithm (توسيع البحث), mean algorithm (توسيع البحث)
system algorithm » custom algorithm (توسيع البحث), sssgm algorithm (توسيع البحث), systematic algorithm (توسيع البحث)
coding algorithm » cosine algorithm (توسيع البحث), modeling algorithm (توسيع البحث), finding algorithm (توسيع البحث)
level coding » level according (توسيع البحث), level modeling (توسيع البحث), level using (توسيع البحث)
element » elements (توسيع البحث)
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501
Results of ablation experiment.
منشور في 2025"…On the KITTI dataset, our algorithm achieved 3D average detection accuracy (AP3D) of 81.15%, 62.02%, and 58.68% across three difficulty levels. …"
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502
Transformer Encoder network structure.
منشور في 2025"…On the KITTI dataset, our algorithm achieved 3D average detection accuracy (AP3D) of 81.15%, 62.02%, and 58.68% across three difficulty levels. …"
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503
Line chart of frame rate.
منشور في 2025"…On the KITTI dataset, our algorithm achieved 3D average detection accuracy (AP3D) of 81.15%, 62.02%, and 58.68% across three difficulty levels. …"
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504
The total loss and three-component loss.
منشور في 2025"…On the KITTI dataset, our algorithm achieved 3D average detection accuracy (AP3D) of 81.15%, 62.02%, and 58.68% across three difficulty levels. …"
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505
Improved upsampling module based on Transformer.
منشور في 2025"…On the KITTI dataset, our algorithm achieved 3D average detection accuracy (AP3D) of 81.15%, 62.02%, and 58.68% across three difficulty levels. …"
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506
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507
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508
Title: Hydro-Aerial Urban Mobility System (HAUMS): Integrated Tubular Network for Clean Transport, Urban Cooling, and Water Recovery / Título: Sistema Hidro-Aéreo de Movilidad Urba...
منشور في 2025"…<p dir="ltr">Hydraulic Tubular Urban Transport System for Sustainable CitiesPart of the Integrated Network For Planetary Sustainability Initiative / Parte de la Iniciativa Red Integrada para la Sostenibilidad Planetaria.This proposal presents an innovative concept for sustainable urban transport: a hydraulic tubular network operating above existing streets, powered by a combination of water and air propulsion with solar energy assistance.The system is built around twin semi-enclosed tubes forming a figure-eight shape:The lower section carries a steady, low-turbulence flow of water that supports the capsules’ motion.The upper section channels controlled air streams that complement the hydraulic flow and increase efficiency.Passenger capsules, light and aerodynamic, travel inside these tubes. …"
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509
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510
LSTM model’s equations.
منشور في 2025"…The findings indicate that the LSTM model, when integrated with the watershed-internal KG and LLM, can effectively incorporate critical elements influencing water level changes, the accuracy of the LLM-KG-LSTM model is enhanced by 3% compared to the standard LSTM model, and the LSTM series outperforms both RNN and GRU models, Our method will guide future research from the perspective of focusing on forecasting algorithms to the perspective of focusing on the relationship between multi-dimensional disaster data and algorithm parallelism.…"
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511
Parameter’s interpretation.
منشور في 2025"…The findings indicate that the LSTM model, when integrated with the watershed-internal KG and LLM, can effectively incorporate critical elements influencing water level changes, the accuracy of the LLM-KG-LSTM model is enhanced by 3% compared to the standard LSTM model, and the LSTM series outperforms both RNN and GRU models, Our method will guide future research from the perspective of focusing on forecasting algorithms to the perspective of focusing on the relationship between multi-dimensional disaster data and algorithm parallelism.…"
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512
The models’ training parameters.
منشور في 2025"…The findings indicate that the LSTM model, when integrated with the watershed-internal KG and LLM, can effectively incorporate critical elements influencing water level changes, the accuracy of the LLM-KG-LSTM model is enhanced by 3% compared to the standard LSTM model, and the LSTM series outperforms both RNN and GRU models, Our method will guide future research from the perspective of focusing on forecasting algorithms to the perspective of focusing on the relationship between multi-dimensional disaster data and algorithm parallelism.…"
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513
Association point and relationship.
منشور في 2025"…The findings indicate that the LSTM model, when integrated with the watershed-internal KG and LLM, can effectively incorporate critical elements influencing water level changes, the accuracy of the LLM-KG-LSTM model is enhanced by 3% compared to the standard LSTM model, and the LSTM series outperforms both RNN and GRU models, Our method will guide future research from the perspective of focusing on forecasting algorithms to the perspective of focusing on the relationship between multi-dimensional disaster data and algorithm parallelism.…"
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514
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515
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516
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517
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518
Overall framework design.
منشور في 2025"…Our approach uses cross-project code clone detection to establish the ground truth for software reuse, identifying code clones across popular GitHub projects as indicators of potential reuse candidates. …"
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519
Gamma distribution of reuse.
منشور في 2025"…Our approach uses cross-project code clone detection to establish the ground truth for software reuse, identifying code clones across popular GitHub projects as indicators of potential reuse candidates. …"
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520
Top 5 correlated features based on reuse.
منشور في 2025"…Our approach uses cross-project code clone detection to establish the ground truth for software reuse, identifying code clones across popular GitHub projects as indicators of potential reuse candidates. …"