A Multiple-Objects Recognition Method Based on Region Similarity Measures: Application to Roof Extraction from Orthophotoplans

In this paper, an efficient method for automatic and accurate detection of multiple objects from images using a region similarity measure is presented. This method involves the construction of two knowledge databases: The first one contains several distinctive textures of objects to be extracted. The second one is composed with textures representing background. Both databases are provided by some examples (training set) of images from which one wants to recognize objects. The proposed procedure starts by an initialization step during which the studied image is segmented into homogeneous regions. In order to separate the objects of interest from the image background, an evaluation of the similarity between the regions of the segmented image and those of the constructed knowledge databases is then performed. The proposed approach presents several advantages in terms of applicability, suitability and simplicity. Experimental results obtained from the method applied to extract building roofs from orthophotoplans prove its robustness and performance over popular methods like K Nearest Neighbours (KNN) and Support Vector Machine (SVM)

African Linguistics in Central and Eastern Europe, and in the Nordic Countries

Non peer reviewe

Green efficiency performance analysis of the logistics industry in China: based on a kind of machine learning methods

This paper aims to analyze the green efficiency performance of the logistics industry in China’s 30 provinces from 2008 to 2017. We first evaluate the green efficiency of the logistics industry through the non-directional distance function (NDDF) method. Then, we use the functional clustering method funHDDC, which is one of the popular machine learning methods, to divide 30 provinces into 4 clusters and analyze the similarities and differences in green efficiency performance patterns among different groups. Further, we explore the driving factors of dynamic changes in green efficiency through the decomposition method. The main conclusions of this paper are as follows: (1) In general, the level of green efficiency is closely related to the geographical location. From the clustering results, we can find that most of the eastern regions belong to the cluster with higher green efficiency, while most of the western regions belong to the cluster with lower green efficiency. However, the green efficiency performance in several regions with high economic levels, such as Beijing and Shanghai, is not satisfactory. (2) Based on the analysis of decomposition results, the innovation effect of China’s logistics industry is the most obvious, but the efficiency change still needs to be improved, and technical leadership should be strengthened. Based on these conclusions, we further propose some policy recommendations for the green development of the logistics industry in China

Phentermine-Associated Atrial Fibrillation: A Case Report and Literature Review

Obesity has become a major public health problem with increased prevalence and is associated with cardiovascular mortality. Phentermine is approved for short-term obesity treatment in conjunction with lifestyle modifications. Palpitations are a well-documented side effect of phentermine, but atrial fibrillation (AF) is rarely reported. We present a case of new-onset AF in a healthy woman who had been recently started on phentermine for weight loss