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When modeling tasks are performed, it is important that the different modeling team members share a common vocabulary. This implies not only agreement on the terminology itself but especially on the meaning of the terms used. To this end it comes in handy to have graphical tools for sharing and analyzing the knowledge dispersed throughout different sources. In this paper we present RCMTool, a tool...
Providing appropriate tool-supported guidance to students is an essential aspect of technology-supported inquiry-based STEM education, in order to facilitate them in engaging in diverse inquiry tasks. However, analyzing educational designs and evaluating the level of tool-supported guidance provided towards reflective remedying actions is not a trivial task, especially for novice STEM teachers. In...
Learning now occurs in various manners in social networks, utilizing practice communities and learning networks. In this context, students are interested in exploring learning activities of other students without having to read through large quantities of textual content. Students tend to be interested in finding information concerning their majors, contents of their subjects and their co-learners...
People are accustomed to seeing certain objects in specific and recurring contexts in daily life. Many research results have indicated that consistent scene could result in better object recognition. Research has also shown that contextual regularities and image quality can help us to form rapid judgments of particular objects and summon our attention when the objects appear to be incongruent with...
In this paper, we tackle the FINE-GRAINED VISUAL RECOGNITION problem by proposing a deep multi-context framework. We employ deep Convolutional Neural Networks to model features of objects in images. Global context and local context are both taken into consideration, and are jointly modeled in a unified multi-context deep learning framework. To cleanse the relatively dirty data for training, a regional...
The ability to obtain a compact description of an object and to keep the significant information can be crucial for many applications such as indexing, clustering and classification. Formal concept analysis (FCA) provides an algorithm to perform such dimension reduction. However, the requirements of FCA limit its performance. In order to relax FCA requirements, this paper presents an extension of...
Infographic is a type of information visualization that uses graphic design to enhance human ability to identify patterns and trends. It is popularly used to support spread of information. Yet, there are few studies that investigate how infographics affect learning and how individual factors, such as learning styles and enjoyment of the information affect infographics perception. In this sense, this...
The trend Gamification occurred several years ago in the context of digital teaching and training aka e-learning. Looking closer at the development of game-based learning and gamification in computer science, it has to be admitted, that game-based learning seems to have ended in an impasse point where the instructionally smooth integration of learning and gaming has not really been realizable, yet...
In robotic navigation, biologically inspired localization models have often exhibited interesting features and proven to be competitive with other solutions in terms of adaptability and performance. In general, place recognition systems rely on global or local visual descriptors; or both. In this paper, we propose a model of context-based place cells combining these two information. Global visual...
Semantic context is an important and useful cue for scene parsing in complicated natural images with a substantial amount of variations in objects and the environment. This paper proposes Spatially Constrained Location Prior (SCLP) for effective modelling of global and local semantic context in the scene in terms of inter-class spatial relationships. Unlike existing studies focusing on either relative...
Smart and wearable devices are trendy electronic objects that have become increasingly popular in recent years. Those devices are, by definition, tightly connected with the user's personal activities. Authentication is therefore a critical feature for both identifying users and personalizing the services on the device. In particular, the emergence of smartglasses changed the way we thought a wearable...
We present a context-aware hybrid classification system for the problem of fine-grained product class recognition in computer vision. Recently, retail product recognition has become an interesting computer vision research topic. We focus on the classification of products on shelves in a store. This is a very challenging classification problem because many product classes are visually similar in terms...
In the field of Marketing Augmented Reality (AR) has the capability to induct necessary innovation which can drive marketing in a user centric dimension which provides exploratory AR experience which is driven by user orientation due to context awareness. Context aware branding and customer preference marketing will present users to view marketing content at their own convenience and driven by utility.
In this paper, we aim at synthesizing a texture from a high-resolution patch and a low-resolution image. To do so, we solve a nonconvex optimization problem that involves a statistical prior and a Fourier spectrum constraint. The numerical analysis shows that the proposed approach achieves better results (in terms of visual quality) than state-of-the-art methods tailored to super-resolution or texture...
Captions are a central component in image posts that communicate the background story behind photos. Captions can enhance the engagement with audiences and are therefore critical to campaigns or advertisement. Previous studies in image captioning either rely solely on image content or summarize multiple web documents related to image's location; both neglect users' activities. We propose business-aware...
Existing joint models of deep Convolutional Neural Networks (CNNs) and Conditional Random Fields (CRFs) face two problems for object segmentation: 1) CNNs can hardly extract high level features; 2) fully connected layers of CNNs are lack of capability of dealing with structured multi-level features. To address these problems, we utilize a Structured Random Forests based border ownership detection...
Existing approaches for egocentric activity recognition mainly rely on a single modality (e.g., detecting interacting objects) to infer the activity category. However, due to the inconsistency between camera angle and subject's visual field, important objects may be partially occluded or missing in the video frames. Moreover, where the objects are and how we interact with the objects are usually ignored...
Students learn and process information in different ways according to their learning styles. There are many learning styles and teachers are usually unable to deliver learning material that matches every possible combination. In this context, several tools, called Adaptive Hypermedia Systems (AHS), have been developed to automatically adapt and recommend learning material according to the students'...
Sustainable energy is no longer a technological challenge, as many of its aspects have now been analyzed and solved. However, this is not true when looking for sustainable systems that are technologically compatible with the characteristics of the historical city. The research first investigated a specific case study: the historical center of Ascoli Piceno in the Marche Region. The analysis began...
Visualization and processing of geographic information is an important part for a Spatial Data Infrastructure (SDI). Choose the software system to accomplish this task is laborious and complex. To assist SDI implementers to define which systems should be used, this article analyzes some of the currently available systems and used by a variety of existing SDI in order to provide information for decision...
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