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Titlebook: Urban Intelligence and Applications; Second International Xiaohui Yuan,Mohamed Elhoseny,Jianfang Shi Conference proceedings 2020 Springer N

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Multi-scale Graph Convolutional Neural Network for Object Recognition from Point Cloud Dataion in recent years. In this paper, we propose a new approach to improve the critical robotic capability, semantic understanding of the environment (i.e., 3D object recognition). The convolutional neural network (CNN) method has a very good recognition result in the 2D image domain, but it has certa
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Label Distribution Learning-Based Semantic Retrieval Model on Knowledge Graph knowledge in reason and retrieve useful knowledge to recommend for users in a big data environment, this paper proposes a label distribution learning-based semantic retrieval model on the knowledge graph. The model firstly constructs the knowledge graph based on the topic map model. And then it clu
发表于 2025-3-25 17:55:59 | 显示全部楼层
An Improved Local Binary Descriptor Based Polar Gridding for Rotation Change proposes a fast and rotation-robust local binary descriptor using polar location, called rotation-invariant local difference binary descriptor (RLDB). RLDB computes binary test of average intensity and gradient in radial and tangent directions of grid cells partitioned by multiple log-polar grids.
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A Task-Aware Network for Multi-task Learningk learning. Fine-tuning a pre-trained network for another task could change the network in a way that degrades the performance on its original task. In this paper, we proposed a novel deep network for learning multiple tasks based on extendable Dynamic Convolutional Blocks. Using the dynamic residua
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Data Mining Technology in Detection and Identification of Bad Data in Power System “residual flooding” or “residual pollution” phenomena, which is the ideal state. The bad data can be detected and identified before the estimation, and the bad data detection and identification method based on association rule mining studied in this paper can solve these problems to a certain exten
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Recommendation Based on Attention Degree and Entropyn establish user profiles through the user’s behavior and other information, and automatically recommend the items that best match the user’s preferences, thus effectively reducing the information overload problem. Although scholars from all over the world have proposed many solutions to the persona
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Model-Based Intelligent Non-linear Signal Recognition for Gearbox Condition Monitoring is proposed. The method is to study and monitor the working state of the gearbox by studying the original vibration signal of the gearbox, and establish a corresponding experimental model by using the normal gear and the fault gear, respectively. Firstly, the vibration signal of the gearbox is prep
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