Πλοήγηση ανά Θέμα "Semantics"
Αποτελέσματα 1-20 από 64
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Applying the Nominal Group Technique for Metadata Training of Domain Experts
(2013)Low metadata quality is a problem faced by most digital repositories, affecting resource discoverability and the overall quality of services and search mechanisms that are supported by these repositories. Metadata training ... -
ARCHEO: A Dataset for Sound Event Detection in Areas of Touristic Interest
(2020)In this work we introduce ARCHEO; a dataset for audio event recognition consisting of audio clips collected from areas of touristic interest. ARCHEO audio samples can be divided into two types based on the way they were ... -
Arm Gesture Recognition using a Convolutional Neural Network
(2018)In this paper we present an approach towards arm gesture recognition that uses a Convolutional Neural Network (CNN), which is trained on Discrete Fourier Transform (DFT) images that result from raw sensor readings. More ... -
A Baselined Gated Attention Recurrent Network for Request Prediction in Ridesharing
(2022)Ridesharing has received global popularity due to its convenience and cost efficiency for both drivers and passengers and its strong potential to contribute to the implementation of the UN Sustainable Development Goals. ... -
Beyond lesion detection: Towards semantic interpretation of endoscopy videos
(2017)Several computer-based medical systems have been proposed for automatic detection of abnormalities in a variety of medical imaging domains. The majority of these systems are based on binary supervised classification ... -
Coding Time Prediction in H.264/HEVC Transcoding Using Macroblock Sizes
(2019)The continuous customers' demand for higher resolution video led to the development of video coding standards that surpass the limitations of H.264/AVC. Prominent examples in this category include the High Efficiency Video ... -
Collaborative online training methods in global production flow
(2007)Large companies may reinforce their competitiveness in the world market by transferring their internally developed know how and working processes to Small and Medium sized Enterprises (SME) that are recipients of outsourcing ... -
Comparative performance analysis of vulkan implementations of computational applications
(2019)The recent introduction of the Vulkan API and the SPIR-V intermediate-level language by the Khronos Group provides a new GPU programming model in an effort to combine the advantages of its predecessors, OpenGL for 3D ... -
Context-aware medical content adaptation through semantic representation and rules evaluation
(2008)Proper coding and transmission of medical and physiological data is a crucial issue for the effective deployment and performance of telemedicine services. The paper presents a platform for performing proper medical content ... -
Context-based storage management for wearable and portable devices
(2005)In our information-rich world, managing the data we collect is becoming a significant bottleneck for users. This issue has triggered considerable research in so-called semantic file systems, relying on the attachment of ... -
Crowd Sourcing as an Improvement of N-Grams Text Document Classification Algorithm
(2020)A common task in a world of natural language processing is text classification useful for e.g.spam filters, documents sorting, science articles classification or plagiarism detection. This can still be done best and most ... -
A Deep Learning Approach to Object Affordance Segmentation
(2020)Learning to understand and infer object functionalities is an important step towards robust visual intelligence. Significant research efforts have recently focused on segmenting the object parts that enable specific types ... -
Design of novel screening environments for Mild Cognitive Impairment: Giving priority to elicited speech and language abilities
(2015)Recent cognitive decline screening batteries have highlighted the importance of language deficits related to semantic knowledge breakdown to reveal the incipient dementia. This paper proposes the introduction of novel ... -
Detecting and Locating Gastrointestinal Anomalies Using Deep Learning and Iterative Cluster Unification
(2018)This paper proposes a novel methodology for automatic detection and localization of gastrointestinal (GI) anomalies in endoscopic video frame sequences. Training is performed with weakly annotated images, using only ... -
Differential diagnosis of behavioral variant and semantic variant of frontotemporal dementia using visual rating scales
(2020)Background: Frontotemporal dementia (FTD) represents the second most frequent early onset of dementia in people younger than 65 years. The main syndromes encompassed by the term FTD are behavioral variant of Frontotemporal ... -
Discovering similar Twitter accounts using semantics
(2016)On daily basis, millions of Twitter accounts post a vast number of tweets including numerous Twitter entities (mentions, replies, hashtags, photos, URLs). Many of these entities are used in common by many accounts. The ... -
Distributed Localized Contextual Event Reasoning under Uncertainty
(2017)We focus on Internet of Things (IoT) environments where sensing and computing devices (nodes) are responsible to observe, reason, report, and react to a specific phenomenon. Each node (e.g., an unmanned vehicle or an ... -
EDUC8 pathways: executing self-evolving and personalized intra-organizational educational processes
(2020)One of the main challenges to be confronted by modern tertiary sector, so as to improve quality is the personalization of learning, which has to be combined with a minimization of the respective costs. However, personalization ... -
Effective cache management and performance limits in information-centric networks
(2013)Proliferation of content distribution traffic in the Internet is changing the requirements on the networking infrastructure to the extent that radical new architectures are envisioned, where information is addressed by ... -
Efficient big data analysis on a single machine using apache spark and self-organizing map libraries
(2017)Apache Spark is commonly used as a big data analytical platform on powerful computer clusters, as it primarily employ the main computer memory for the evaluation. Our attempt adds self-organizing map software libraries ...