|
|
|
|
|
Adil Redaoui, Amina Belalia and Kamel Belloulata
Deep network-based hashing has gained significant popularity in recent years, particularly in the field of image retrieval. However, most existing methods only focus on extracting semantic information from the final layer, disregarding valuable structura...
ver más
|
|
|
|
|
|
|
|
|
Rongke Wei, Haodong Pei, Dongjie Wu, Changwen Zeng, Xin Ai and Huixian Duan
The task of 3D reconstruction of urban targets holds pivotal importance for various applications, including autonomous driving, digital twin technology, and urban planning and development. The intricate nature of urban landscapes presents substantial cha...
ver más
|
|
|
|
|
|
|
|
|
Ruoyang Li, Shuping Xiong, Yinchao Che, Lei Shi, Xinming Ma and Lei Xi
Semantic segmentation algorithms leveraging deep convolutional neural networks often encounter challenges due to their extensive parameters, high computational complexity, and slow execution. To address these issues, we introduce a semantic segmentation ...
ver más
|
|
|
|
|
|
|
|
|
Tao Peng, Kun She, Yimin Shen, Xiangliang Xu and Yue Yu
Requirement traceability links are an essential part of requirement management software and are a basic prerequisite for software artifact changes. The manual establishment of requirement traceability links is time-consuming. When faced with large projec...
ver más
|
|
|
|
|
|
|
|
|
Hyunmin Gwak, Yongho Jeong, Chanyeong Kim, Yonghak Lee, Seongmin Yang and Sunghwan Kim
The key to semi-supervised semantic segmentation is to assign the appropriate pseudo-label to the pixels of unlabeled images. Recently, various approaches to consistency-based training and the filtering of reliable pseudo-labels have shown remarkable res...
ver más
|
|
|
|