Road extraction from aerial images has been a hot research topic in the field of remote sensing image analysis. In this letter, a semantic segmentation neural network which combines the strengths of residual learning and U-Net is proposed for road area extraction. The network is built with residual units and has similar architecture to that of U-Net. The benefits of this model is two-fold: firs...

Deep learning (DL) based semantic segmentation methods have been providing state-of-the-art performance in the last few years. More specifically, these techniques have been successfully applied to medical image classification, segmentation, and detection tasks. One deep learning technique, U-Net, has become one of the most popular for these applications. In this paper, we propose a Recurrent Co...

The unsupervised detection of hierarchical structures is a major topic in unsupervised learning and one of the key questions in data analysis and representation. We propose a novel algorithm for the problem of learning decision trees for data clustering and related problems. In contrast to many other methods based on successive tree growing and pruning, we propose an ,aL”G.,P 4Lnrt;nn C.-e hM ,...

There are various varieties of Rice and lentils. Price fabrication adulteration have been some the issues faced by consumers, farmers wholesale retailers. Traditional methods for Identification these similar types grains their quality analysis crude inaccurate. Methods were tried to implemented earlier but due financial inability low efficiency, they weren’t successful. To overcome this problem...

Background: The purposes of this study were to develop a problem-based learning program for nursing student’s education and to evaluate the program after its implementation. Methods: An intervention study carried out on 27 third year undergraduate nursing students in the nursing and midwifery faculty of Kashan University of Medical Sciences. Problem-based learning method was used for one group...