|
|
|
Zeyang Zhang, Zhongcai Pei, Zhiyong Tang and Fei Gu
Traditional video object segmentation often has low detection speed and inaccurate results due to the jitter caused by the pan-and-tilt or hand-held devices. Deep neural network (DNN) has been widely adopted to address these problems; however, it relies ...
ver más
|
|
|
|
|
|
Feng Zhu, Jieyu Zhao and Zhengyi Cai
At present, the unsupervised visual representation learning of the point cloud model is mainly based on generative methods, but the generative methods pay too much attention to the details of each point, thus ignoring the learning of semantic information...
ver más
|
|
|
|
|
|
Mohammad Daradkeh
The heterogeneity and diversity of users and external knowledge resources is a hallmark of open innovation communities (OICs). Although user segmentation in heterogeneous OICs is a prominent and recurring issue, it has received limited attention in open ...
ver más
|
|
|
|
|
|
Iurii Katser, Viacheslav Kozitsin, Victor Lobachev and Ivan Maksimov
Offline changepoint detection (CPD) algorithms are used for signal segmentation in an optimal way. Generally, these algorithms are based on the assumption that signal?s changed statistical properties are known, and the appropriate models (metrics, cost f...
ver más
|
|
|
|
|
|
Feiyang Chen, Ying Jiang, Xiangrui Zeng, Jing Zhang, Xin Gao and Min Xu
Salient segmentation is a critical step in biomedical image analysis, aiming to cut out regions that are most interesting to humans. Recently, supervised methods have achieved promising results in biomedical areas, but they depend on annotated training d...
ver más
|
|
|