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In nowadays, as the development of digital photographic technology, video files grow rapidly, there is a great demand for automatic video semantic analysis in many scenes, such as video semantic understanding, content-based analysis, video retrieval. Shot boundary detection is a key basic technology and first step for video analysis. However, recent methods are time consuming and performs bad in the...
Dependency-based software change impact analysis is the domain concerned with estimating the sets of artifacts impacted by a change to a related artifact. Research has shown that analysing the various class dependency types independently will never completely reveal the impact sets. Therefore, dependency types are combined to improve the precision of estimated when compared to impact sets. Software...
Currently, open source projects receive various kinds of issues daily, because of the extreme openness of Issue Tracking System (ITS) in GitHub. ITS is a labor-intensive and time-consuming task of issue categorization for project managers. However, a contributor is only required a short textual abstract to report an issue in GitHub. Thus, most traditional classification approaches based on detailed...
Person re-identification is an important task in video surveillance systems. It can be formally defined as establishing the correspondence between images of a person taken from different cameras at different times. In this paper, we present a two stream convolutional neural network where each stream is a Siamese network. This architecture can learn spatial and temporal information separately. We also...
Semantic similarity of texts is one of the important areas of Natural Language Processing, and there are several approaches to measure similarity: statistical, WordNet based, and hybrid. For all of these approaches, a lexical knowledge is used such as corpus or semantic network. WordNet is one of the most preferred and mature lexical knowledge base. In this study, we have focused on measuring semantic...
We report on the results of the first visual search and rating study (N60) evaluating human gaze when assessing the realism of image composites. The effects of object identity knowledge and mismatched feature type on observers' gaze and subjective realism scores are studied. Gaze metrics used include: fixation count, fixation duration, time and duration of first fixation on target object, as well...
Blockchain is a decentralized, trustless protocol that combines transparency, immutability, and consensus properties to enable secure, pseudo-anonymous transactions. Smart contracts are built atop a blockchain to support on-chain storage and enable Decentralized Apps (DApps) to interact with the blockchain programatically. Programmable blockchains have generated interest in the healthcare domain as...
Video scene detection, the task of temporally dividing a video into its semantic sections, is an important process for effective analysis of heterogeneous video content. With the increased amount of video available for consumption, video scene detection becomes more and more important by providing means for effective video summarization, search and retrieval, browsing, and video understanding. We...
A wide range of text-based artifacts contribute to software projects (e.g., source code, test cases, use cases, project requirements, interaction diagrams, etc.). Traceability Link Recovery (TLR) is the software task in which relevant documents in these various sets are linked to one another, uncovering information about the project that is not available when considering only the documents themselves...
We present a scene parsing method that utilizes global context information based on both the parametric and nonparametric models. Compared to previous methods that only exploit the local relationship between objects, we train a context network based on scene similarities to generate feature representations for global contexts. In addition, these learned features are utilized to generate global and...
The usage of the service selection approaches across different dynamic service provisioning environments has increased the challenges associated with an effective method that can be used to select a relevant service. The use of service selection approach should depend on certain factors. In order to address this challenge, the literature analysis is conducted on various service selection approaches...
In this paper, we introduce our multi-document summarization system for Turkish news. The aim of the summarization system is to build a single document for multi document news that have been collected previously. The news were collected from several Turkish news sources via Real Simple Syndication (RSS). They were separated into clusters according to their topics. We utilized cosine similarity metric...
Paraphrase Detection is the task of examining if two sentences convey the same meaning or not. Here, in this paper, we have chosen a sentence embedding by unsupervised RAE vectors for capturing syntactic as well as semantic information. The RAEs learn features from the nodes of the parse tree and chunk information along with unsupervised word embedding. These learnt features are used for measuring...
Automatic recommendations based on skill matching techniques can prove to be an important component of an online recruitment platform, being able to lower the costs for employers, ease the process for candidates and increase the hiring quality overall. This is important nowadays, when online recruitment plays a major role in the hiring process. The main challenges in this area consist in providing...
Event detection in unconstrained videos is conceived as a content-based video retrieval with two modalities: textual and visual. Given a text describing a novel event, the goal is to rank related videos accordingly. This task is zero-exemplar, no video examples are given to the novel event. Related works train a bank of concept detectors on external data sources. These detectors predict confidence...
In this work we study the task of image annotation, of which the goal is to describe an image using a few tags. Instead of predicting the full list of tags, here we target for providing a short list of tags under a limited number (e.g., 3), to cover as much information as possible of the image. The tags in such a short list should be representative and diverse. It means they are required to be not...
Recently, there has been a lot of interest in automatically generating descriptions for an image. Most existing language-model based approaches for this task learn to generate an image description word by word in its original word order. However, for humans, it is more natural to locate the objects and their relationships first, and then elaborate on each object, describing notable attributes. We...
In industrial power generation plants, subsystem monitoring and analytics play a vital role in quantifying the knowledge about different factors that impact their overall performance. Multi-dimensional performance metrics, e.g. thermal efficiency, in-service time, mean-time-to-failure etc., are calculated that may have different data constraints, modelling techniques, and execution frameworks. Automating...
Recent years have witnessed a resurgence of interest in video summarization. However, one of the main obstacles to the research on video summarization is the user subjectivity — users have various preferences over the summaries. The subjectiveness causes at least two problems. First, no single video summarizer fits all users unless it interacts with and adapts to the individual users. Second,...
Person re-identification (ReID) is an important task in video surveillance and has various applications. It is non-trivial due to complex background clutters, varying illumination conditions, and uncontrollable camera settings. Moreover, the person body misalignment caused by detectors or pose variations is sometimes too severe for feature matching across images. In this study, we propose a novel...
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