Titlebook: Computer-Aided Design and Computer Graphics; 18th International C Shi-Min Hu,Yiyu Cai,Paul Rosin Conference proceedings 2024 The Editor(s)

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書目名稱Computer-Aided Design and Computer Graphics影響因子(影響力)




書目名稱Computer-Aided Design and Computer Graphics影響因子(影響力)學科排名




書目名稱Computer-Aided Design and Computer Graphics網(wǎng)絡公開度




書目名稱Computer-Aided Design and Computer Graphics網(wǎng)絡公開度學科排名




書目名稱Computer-Aided Design and Computer Graphics被引頻次




書目名稱Computer-Aided Design and Computer Graphics被引頻次學科排名




書目名稱Computer-Aided Design and Computer Graphics年度引用




書目名稱Computer-Aided Design and Computer Graphics年度引用學科排名




書目名稱Computer-Aided Design and Computer Graphics讀者反饋




書目名稱Computer-Aided Design and Computer Graphics讀者反饋學科排名

宏偉

表臉

,FFANet: Dual Attention-Based Flow Field Aware Network for?3D Grid Classification and?Segmentation,te the great success in various scenarios, the existing approaches fail to effectively utilize the velocity information in the flow field, resulting in the actual requirements of post-processing tasks being difficult to meet by the extracted features. To fully integrate structural information in the

開始發(fā)作

,A Lightweight Model for?Feature Points Recognition of?Tool Path Based on?Deep Learning,r method encodes CL points as matrices and stores them as text files. We have developed a neural network with an Encoder-Decoder architecture, named EDFP-Net, which takes the encoding matrices as input, extracts deeper features using the Encoder, and recognizes feature points using the Decoder. Our

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聯(lián)想記憶

聯(lián)想記憶

Influence of the Printing Direction on the Surface Appearance in Multi-material Fused Filament Fabrsurface appearance is largely a matter of trial and error unless the employed materials are very similar and very translucent, so we can think of them as blending together. When the multiple materials are fused into one filament in a diamond hotend extruder but do not blend, the resulting surface ap

樹木心

StrongOC-SORT: Make Observation-Centric SORT More Robust,ositions and disturbed tracks. Despite great progress made by current trackers, their performance still needs improvement due to their inability to adapt their components to these challenges. In this work, we propose a new method, StrongOC-SORT, which exploits the observation-centric nature and four

Morbid

,Semi-direct Sparse Odometry with?Robust and?Accurate Pose Estimation for?Dynamic Scenes, with moving objects. This paper addresses the problem by proposing a semi-direct sparse visual odometry (SDSO) method designed for dynamic scenes. With the aid of the pixel-level semantic information, the system can not only eliminate dynamic points but also construct more accurate photometric erro

Suggestions

,Parallel Dense Vision Transformer and?Augmentation Network for?Occluded Person Re-identification,s across different devices. Some existing methods mainly focus on developing effective data augmentation and representation learning techniques to improve the performance of person ReID systems. However, existing data augmentation strategies can not make full use of the information in the training d