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Agricultural robots rely on semantic segmentation for distinguishing between crops and weeds to perform selective treatments and increase yield and crop health while reducing the amount of chemicals used. Deep‐learning approaches have recently achieved both excellent classification performance and real‐time execution. However, these techniques also rely on a large amount of training data, requiring...
Discriminating value crops from weeds is an important task in precision agriculture. In this paper, we propose a novel image processing pipeline based on attribute morphology for both the segmentation and classification tasks. The commonly used approaches for vegetation segmentation often rely on thresholding techniques which reach their decisions globally. By contrast, the proposed method works with...
Morphological attribute profiles are among the most prominent spatial-spectral pixel description tools. They can be calculated efficiently from tree based representations of an image. Although mostly implemented with inclusion trees (i.e. component trees and tree of shapes), attribute profiles have been recently adapted to partitioning trees, and specifically α- and ω-trees. Partitioning trees constitute...
We propose a local region descriptor based on connected pattern spectra, and combined with normalized central moments. The descriptors are calculated for MSER regions of the image, and their performance compared against SIFT. The MSER regions were chosen because they can be efficiently selected by constructing a max-tree, a structure used to calculate both descriptors and region moments. Experiments...
User authentication based solely on user's password is the most commonly used method, but with several known issues. With the growing number of Internet users, most of whom are not familiar enough with security threats, as well as growing significance of their on-line activities, stolen passwords are becoming a major security problem. We argue that an additional, non-intrusive level of security can...
Imperfect information environments are amongst common research subjects in the field of Artificial Intelligence. A game of poker is a good example of such an environment. As the popularity of the game grew, so did the interest in implementing a functioning automatized poker player. Approaches to this problem include various Machine Learning techniques like Bayesian decision networks, various Case-based...
This paper is concerned with detection and recognition of road surface markings in video acquired from the driver's perspective. In particular, we focus on centerlines which separate the two road lanes with opposed traffic directions, since they are often the only markings in many urban and suburban roads. The proposed technique is based on detecting parabolic sections of the thresholded steerable...
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