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Titlebook: Image and Graphics; 11th International C Yuxin Peng,Shi-Min Hu,Kun Xu Conference proceedings 2021 Springer Nature Switzerland AG 2021 artif

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21#
發(fā)表于 2025-3-25 03:20:49 | 只看該作者
Jun Wu,Huimin Wang,Xingliang Zhu,Meng Wang,Jian Yang,Wenting Luo,Lei Qu are based on specific orthographic experience rather than reflecting general developmental processes, the developmental course of metalinguistic awareness should differ as a function of the specific writing systems children are learning. Chinese characters and the English alphabetic writing system
22#
發(fā)表于 2025-3-25 10:54:40 | 只看該作者
Yanqing Yang,Jianxu Mao,Hui Zhang,Yurong Chen,Hang Zhong,Zhihong Huang,Yaonan WangShared-Book reading is one-way to expand the volume of reading of young children. In China, teaching reading is based on a long tradition of intensive reading of limited amounts of text using recitation, drill, practice, and memorization. The Shared-Book approach was adapted to accommodate the Chine
23#
發(fā)表于 2025-3-25 15:12:25 | 只看該作者
L2-CVAEGAN: Feature Aligned Generative Networks for Zero-Shot Learningaive strategy ignores the visual divergences of different classes, which will result in excessive differences between generated and real samples. In this work, random vectors sample from the real visual distribution encoded by the encoder. Therefore, the generated samples are more close to real-worl
24#
發(fā)表于 2025-3-25 17:13:07 | 只看該作者
25#
發(fā)表于 2025-3-25 21:10:43 | 只看該作者
FER-YOLO: Detection and Classification Based on Facial Expressions, facial expression recognition (FER) plays an important role in expressing human emotional information. Generally, the FER classification process includes face pre-processing (face detection, alignment, etc.), which adds extra workload. To this end, detection and classification are carried out simu
26#
發(fā)表于 2025-3-26 02:46:58 | 只看該作者
27#
發(fā)表于 2025-3-26 07:28:54 | 只看該作者
28#
發(fā)表于 2025-3-26 10:07:20 | 只看該作者
Feature Separation GAN for Cross View Gait Recognitioniew gait recognition problem. This paper proposes a view transformation model method based on feature separation generate adversarial networks. Based on the GAN model, this method separates the features of the input data as an additional discriminant basis. On the premise of building a single model,
29#
發(fā)表于 2025-3-26 13:32:39 | 只看該作者
30#
發(fā)表于 2025-3-26 18:18:40 | 只看該作者
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