This paper proposes a pixel-based texture classifier that integrates multiple texture feature extraction methods in order to identify the regions of an input image that belong to a given set of texture patterns. Exper...
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Many robotics tasks require autonomous exploration by teams of robots. In difficult or large environments, communication drop-out complicates this task. Several approaches exist that aim to keep the team connected, bu...
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ISBN:
(纸本)9780980740424
Many robotics tasks require autonomous exploration by teams of robots. In difficult or large environments, communication drop-out complicates this task. Several approaches exist that aim to keep the team connected, but even so there is an inherent limit to the range that can be explored. In this paper we describe and examine Role-Based Exploration, an approach that uses mobile relays to ferry information back and forth within the team, and compare it to methods that do not. There are significant advantages in the use of such relays, such as improved coordination and responsiveness, and adaptability to unexpected communication dropout. The approaches are implemented and validated on a team of real robots.
Deep neural networks virtually dominate the domain of most modern vision systems, providing high performance at a cost of increased computational complexity. Since for those systems it is often required to operate bot...
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In this paper the research on optimisation of visual object tracking using a Siamese neural network for embedded vision systems is presented. It was assumed that the solution shall operate in real-time, preferably for...
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Quantum Neural Networks (QNNs) are an emerging technology that can be used in many applications including computervision. In this paper, we presented a traffic sign classification system implemented using a hybrid qu...
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In this paper we present a vision based hardware-software control system enabling the autonomous landing of a multirotor unmanned aerial vehicle (UAV). It allows for the detection of a marked landing pa...
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Glaucoma is one of the major reasons for visual impairment all across the globe. The recent advancements in machine learning techniques have greatly facilitated ophthalmologists in the early diagnosis of ocular diseas...
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This paper presents a new, efficient technique for supervised texture segmentation based on a set of specifically designed filters and a multi-level pixel-based classifier. Filter design is carried out by means of a n...
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This paper presents a new, efficient technique for supervised texture segmentation based on a set of specifically designed filters and a multi-level pixel-based classifier. Filter design is carried out by means of a neural network, which is trained to maximize the filters' discrimination power among the texture classes under consideration. Texture features obtained with these filters are then processed by a classification scheme that utilizes multiple evaluation window sizes following a top-down approach, which iteratively refines the resulting segmentation. The proposed technique is compared to previous supervised texture segmenters by using both synthetic compositions and real outdoor textured images.
Most existing approaches to autonomous driving fall into one of two categories: modular pipelines, that build an extensive model of the environment, and imitation learning approaches, that map images directly to contr...
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A supervised pixel-based classifier for identifying the presence of a given set of texture patterns of interest in a complex textured image is described. The proposed technique integrates the outcome of multiple textu...
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A supervised pixel-based classifier for identifying the presence of a given set of texture patterns of interest in a complex textured image is described. The proposed technique integrates the outcome of multiple texture feature extraction methods belonging to different families. In this way, it yields lower classification rates than previous texture classifiers based on specific families of texture methods. Experimental results with real outdoor images are presented.
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