Attribute-aware Semantic Segmentation of Road Scenes for Understanding Pedestrian Orientations

Semantic segmentation is an interesting task for many deep learning researchers for scene understanding. However, recognizing details about objects' attributes can be more informative and also helpful for a better scene understanding in intelligent vehicle use cases. This paper introduces a method for simultaneous semantic segmentation and pedestrian attributes recognition. A modified dataset built on top of the Cityscapes dataset is created by adding attribute classes corresponding to pedestrian orientation attributes. The proposed method extends the SegNet model and is trained by using both the original and the attribute-enriched datasets. Based on an experiment, the proposed attribute-aware semantic segmentation approach shows the ability to slightly improve the performance on the Cityscapes dataset, which is capable of expanding its classes in this case through additional data training

Evaluation of results from the fourth and fifth IAVCEI field workshops on volcanic gases, Vulcano island, Italy and Java, Indonesia

The major purpose of field workshops on volcanic gases, organized by the IAVCEI Commission on the Chemistry of Volcanic Gases, is the collection and analysis of volcanic gas discharges with the aim to develop and improve techniques for the geochemical surveillance of active volcanoes. The fourth and fifth workshops were held at Vulcano island, Italy, in 1991 and on Java island, Indonesia, in 1994, respectively. Gas samples were collected from four gas vents by nine groups at Vulcano and from eight gas vents by eight groups on Java. The quality (e.g. scatter of the data) of most of the results, reported from these two workshops, is sufficient to permit a broad chemical classification of the discharge and meaningful thermodynamic interpretation. In most cases, the majority of the data for individual gas vents cluster closely around the median values, suggesting that the median values are the best estimates of chemical composition. There is, however, also a considerable scatter of the analytical data, and this scatter warns us to not rely too heavily on a single analytical value, in particular on a value for CH4 and CO, because analytical data for these species often show a wide scatter. This warning is particularly relevant for chemical monitoring of volcanic activity. Further improvement of the sampling and analytical techniques as well as more detailed comparison of the techniques is required to reduce such uncertainty in order to interpret the volcanic activity and hydrothermal conditions. © 2001 Elsevier Science B.V. All rights reserved