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Dagger is a modeling and visualization framework that addresses the challenge of representing knowledge and information for decision-makers, enabling them to better comprehend the operational context of network security data. It allows users to answer critical questions such as “Given that I care about mission X, is there any reason I should be worried about what is going on in cyberspace?” or “If...
Bag of visual words (BoVW) remains a very competitive representation in the domain of scene classification. In this framework, extracting SIFT descriptors on a dense grid of pixels has shown to lead to a better performance. However, due to the nature of SIFT as an edge-based descriptor, computing SIFT on homogeneous regions might result in non-stable region descriptors. The suggested solution in the...
Visual information is a valuable asset in any perception scheme designed for an intelligent transportation system. In this regard, the camera-based recognition of locations provides a higher situational awareness of the environment, which is very useful for varied localization solutions typically needed in long-term autonomous navigation, such as loop closure detection and visual odometry or SLAM...
Profiling tools are indispensable for performance optimization of parallel codes. They allow users to understand where a code spends its time, and to focus optimization efforts on the most time consuming regions. However, two sources of complexity make them difficult to use on large-scale parallel applications. First, the code complexity of parallel applications is increasingly, and identifying the...
Managing scientific software stacks has traditionally been a manual task that required a sizeable team with knowledge about the specifics of building each application. Keeping the software stack up to date also caused a significant overhead for system administrators as well as support teams. Furthermore, a flat module view and the manual creation of modules by different members of the teams can end...
An effective change in Human Computer Interaction requires to account of how communication practices are transformed in different contexts, how users sense the interaction with a machine, and an efficient machine sensitivity in interpreting users' communicative signals, and activities. To this aims, the present paper investigates on whether and how positive and negative visual scenes may alter listeners'...
Most of recommender systems build their predictions by analysing the preferences of users. However, there are many situations, such as in intelligent tutoring systems, where recommendations of pedagogical resources should rather be based on their memory. So as to infer in real time and with low involvement what has been memorized by users, we highlight in the paper the link between gaze features and...
Assessment of image similarity is ubiquitous and essential task to a wide range multimedia applications. In this paper we propose a similarity method which aims at providing an image classification scheme using multi-instances based representation of an image. In other words, the similarity measure is defined to be used within two sample sets where each set, which can be defined in an arbitrary metric...
In recent decades, experts have presented a range of teaching methods and techniques which should increase the learning effectiveness. Naturally, no learning process is universal and reliable at the same time, and suitable for everyone and in every situation. Concept mapping is a method based on findings in cognitive psychology. We investigated how the learning process and effectiveness can be influenced...
A major component of a generic image retrieval pipeline is producing concise and effective descriptors for each image. Previous works have shown impressive results in image retrieval when using descriptors from the black-box output of the fully-connected stage of pretrained Convolutional Neural Networks (ConvNets). However, previous work on descriptors pooled from the deep feature maps from late convolutional...
In this paper, we study a pattern-context-aware scheme for stereo pattern analysis.Depth and texture are chosen as two primary factors for the pattern-context- aware computing.We organize these patterns as a context to analyze.A knowledge-based inference system is built with human experience to model the correlation of the context and processing. The process for the pattern analysis could recognize...
The slit-scan technique is applied as a means to create artistic static and dynamic representations of motion in videos by arranging small slits of each video frame next to each other. This technique produces compact representations evenfor long timespansof recorded video material. We adapt this approach for the comparison of eye tracking data from multiple participants watching video. We adjust the...
In the context of visual object search and localization, saliency maps provide an efficient way to find object candidates in images. Unlike most approaches, we propose a way to learn saliency maps directly on a robot, by exploring the environment, discovering salient objects using geometric cues, and learning their visual aspects. More importantly, we provide an autonomous exploration strategy able...
Computer technology offers huge potential for assisting People with Disabilities (PwD), whether in daily activities, rehabilitation, or educational processes. However, we observed in literature that High Assistive Technologies (HATs) must be customized for each PwD, since a technology that works for one does not always work for another. In this scenario, the Participatory Design (PD) approach proves...
In this work, we grant robot agents the capacity to sense and react to their human supervisor's changing trust state, as a means to maintain the efficiency of their collaboration. We propose the novel formulation of Trust-Aware Conservative Control (TACtiC), in which the agent alters its behaviors momentarily whenever the human loses trust. This trust-seeking robot framework builds upon an online...
The development of reliable and robust visual recognition systems is a main challenge towards the deployment of autonomous robotic agents in unconstrained environments. Learning to recognize objects requires image representations that are discriminative to relevant information while being invariant to nuisances, such as scaling, rotations, light and background changes, and so forth. Deep Convolutional...
This paper investigates the development of a classification of features inherent in the design and development of Location Based Experiences (LBEs) with a special focus on games for teaching and learning. The paper aims to identify and associate learning features, such as feedback, activities, outcomes and assessment with location-driven mechanics, such as location-based activities, entities, conditions...
Previous empirical studies have analyzed emotional responses to form and color, across a variety of contexts and across cultures. Recently Amare and Manning proposed a systematic model that identifies a spectrum of emotional quality (agitation-amusement-focus) generally parallel to the familiar color spectrum (red-yellow-blue) and a spectrum of form (contrast-variety-pattern). For example, both the...
The inclusion of people with disabilities in regular schools needs to be effective. Therefore, appropriated teaching methods, materials and capacitated teachers are indispensable factors. By using learning objects, it is necessary to ensure that they were built considering the needs of people with disabilities, which means the possibility of using accessibility resources. In this work, only visual...
Engineers and scientists need to be skilled in writing, speaking, and using visuals. This paper explores how instruction in communication can draw upon principles common across modes of communication. I first survey guidelines for the design of scholarly posters and categorize the types of advice they provide. Second, I use the categories of advice to develop a framework which highlights principles...
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