Automatic extraction of tailing ponds from Very High-Resolution (VHR) remotely sensed images is vital for mineral resource management. This study proposes a Pseudo-Siamese Visual Geometry Group Encoder-Decoder network (PSVED) to achieve high accuracy VHR images. First, handcrafted feature (HCF) are calculated based on the index calculation algorithm, highlighting ponds’ signals. Second, conside...

Semantic role labeling, the computational identification and labeling of arguments in text, has become a leading task in computational linguistics today. Although the issues for this task have been studied for decades, the availability of large resources and the development of statistical machine learning methods have heightened the amount of effort in this field. This special issue presents se...

Semantic role labeling, the computational identification and labeling of arguments in text, has become a leading task in computational linguistics today. Although the issues for this task have been studied for decades, the availability of large resources and the development of statistical machine learning methods have heightened the amount of effort in this field. This special issue presents se...

This paper shows that semantic role labeling is a consequence of accurate verbal predicate labeling. In doing so, the paper presents a novel type of semantic feature for verbal predicate labeling using a new corpus. The corpus contains verbal predicates, serving as verb senses, that have semantic roles associated with each argument. Although much work has been done using feature vectors with ma...

In this study, we try to apply SVMs to the semantic role labeling task, which is one of the multiclass problems. As a result, we propose a two-phase semantic role labeling model which consists of the identification phase and the classification phase. We first identify semantic arguments, and then assign semantic roles to the identified semantic arguments. By taking the two-phase approach, we ca...

In this article we report work on Chinese semantic role labeling, taking advantage of two recently completed corpora, the Chinese PropBank, a semantically annotated corpus of Chinese verbs, and the Chinese Nombank, a companion corpus that annotates the predicate–argument structure of nominalized predicates. Because the semantic role labels are assigned to the constituents in a parse tree, we fi...

37 sites for the checking of farmers’ aid applications under the Common Agricultural Policy (CAP), covering an area of over 10,000 km, were imaged with very high resolution (VHR) images (Ikonos, QuickBird, Eros) in the framework of an operational testing programme. Determining the performance of VHR imagery orthorectification, and geometric quality assessment of the results in relation to the d...

When ordering very high resolution (VHR) imagery of IKONOS or QuickBird a cloud coverage up to 20 % within the scenes has to be accepted. This indicates the high impact of atmospheric conditions to VHR imagery. Beside clouds the images are influenced by haze oftentimes. This haze could be removed using new atmospheric correction algorithms, which were not available for VHR data so far. Furtherm...

XARA is a rule-based PropBank labeler for Alpino XML files, written in Java. I used XARA in my research on semantic role labeling in a Dutch corpus to bootstrap a dependency treebank with semantic roles. Rules in XARA are based on XPath expressions, which makes it a versatile tool that is applicable to other treebanks as well. In addition to automatic role annotation, XARA is able to extract tr...

Scene segmentation and semantic labeling of Synthetic Aperture Radar (SAR) images is one of the key problems in interpreting SAR data. In this paper, a new approach for semantic labeling of SAR imagery is proposed based on hierarchical Markov aspect model (HMAM) with weak supervision. The motivation for this work is to incorporate the multiscale spatial relation between adjacent image patches i...