It is well known that direct parsing of a long Japanese compound sentence is extremely difficult. Various pre-processing methods have been proposed to segment such a sentence into shorter, simpler ones prior to parsing. The problem with the conventional methods is that some kind of segmentation patterns or heuristic preference scores must be given manually, hence no guarantee for optimality. Th...

This paper presents a segmentation algorithm for gray-level images and addresses issues related to its performance on noisy images. It formulates an image segmentation problem as a partition of an image into (arbitrarily-shaped) connected regions to minimize the sum of graylevel variations over all partitioned regions, under the constraints that (1) each partitioned region has at least a specif...

Sigma-Trees associated with residual vector quantization (RVQ) has been used for image-driven data mining to detect features and objects in a digital image with a degree of success. RVQ methods based on σ-tree structures have been designed to implement successive refinement of information for image segmentation. In such implementations, RVQ based novel methods are devised for pixel-block mining...

In this research, we explore nested or hierarchical query segmentation, where segments are defined recursively as consisting of contiguous sequences of segments or query words, as a more effective representation of a query. We design a lightweight and unsupervised nested segmentation scheme, and propose how to use the tree arising out of the nested representation of a query to improve ranking p...

LiDAR sampling or full-area coverage is deemed as favorable means to achieve timely and robust characterizations of vertically distributed forest attributes. So far, two main strategies on the use of LiDAR data in forestry are reported: area-based method (ABA) and individual tree method (ITC). Recently, a novel 3D segmentation approach has been developed for extracting single trees from LIDAR d...

Canopy Height Model (CHM) is a standard LiDAR-derived product for deriving relevant forest inventory information, among which individual tree identification is a crucial task. The watershed algorithm from markers is the typical procedure applied to CHMs for delineation of crowns. However, for low-quality CHMs or under certain canopy conditions, segmentation at individual tree level is not pract...

Deep learning, neural networks and other data-driven processing techniques are increasingly used in the analysis of LiDAR point cloud data forest environments due to benefits offered accuracy adaptability new environments. One downsides these practical applications is requirement for manually annotated necessary training networks, which can be time consuming costly attain. We develop an approac...

Multiscale Bayesian approaches have attracted increasing attention for use in image segmentation. Generally, these methods tend to offer improved segmentation accuracy with reduced computational burden. Existing Bayesian segmentation methods use simple models of context designed to encourage large uniformly classified regions. Consequently, these context models have a limited ability to capture...