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Zero-shot learning (ZSL) aims at classifying examples for unseen classes (with no training examples) given some other seen classes (with training examples). Most existing approaches exploit intermedia-level information (e.g., attributes) to transfer knowledge from seen classes to unseen classes. A common practice is to first learn projections from samples to attributes on seen classes via a regression...
Code bloat is a phenomenon in Genetic Programming (GP) that increases the size of individuals during the evolutionary process. Over the years, there has been a large number of research that attempted to address this problem. In this paper, we propose a new method to control code bloat and reduce the complexity of the solutions in GP. The proposed method is called Substituting a subtree with an Approximate...
In this paper, the principal possibility of using modal logic in the tasks of self-learning of intelligent mobile robots operating in an unknown environment is considered. The methodology for creating a model of the intelligent mobile robot control system with a self-learning module is presented. The basic principles and concepts of modal logic are described. To substantiate the applicability of the...
Blind image quality assessment (BIQA) methods aim to estimate the quality of a given test image without referring to the corresponding reference (original) image. Most BIQA methods use visual sensitivity models, which take into consideration intrinsic image characteristics (e.g. contrast, luminance, and texture) to identify degradations and estimate quality. For example, texture-based BIQA methods...
Binary lifting, which is to translate a binary executable to a high-level intermediate representation, is a primary step in binary analysis. Despite its importance, there are only few existing approaches to testing the correctness of binary lifters. Furthermore, the existing approaches suffer from low test coverage, because they largely depend on random test case generation. In this paper, we present...
Object-branch coverage (OBC) is often used as a measure of the thoroughness of tests suites, augmenting or substituting source-code based structural criteria such as branch coverage and modified condition/decision coverage (MC/DC). In addition, with the increasing use of third-party components for which source-code access may be unavailable, robust object-code coverage criteria are essential to assess...
Code changes are often reviewed before they are deployed. Popular source control systems aid code review by presenting textual differences between old and new versions of the code, leaving developers with the difficult task of determining whether the differences actually produced the desired behavior. Fortunately, we can mine such information from code repositories. We propose aiding code review with...
Mutation testing is known as an effective method for evaluating test sets in terms of their error-revealing capability. When applying mutation testing, it is necessary to identify and filter out the equivalent mutants, i.e. mutants that despite their syntactical difference have the same semantic as the original program. Due to the undecidable nature of the problem of determining whether two programs...
Existing video event classification approaches suffer from limited human-labeled semantic annotations. Weak semantic annotations can be harvested from Web-knowledge without involving any human interaction. However such weak annotations are noisy, thus can not be effectively utilized without distinguishing its reliability. In this paper, we propose a novel approach to automatically maximize the utility...
The ongoing trend towards distributed development activities causes a growing need for specification activities and techniques. Each component leads to a large number of specification documents being exchanged, change managed and committed. The quality of the specifications influences the timing, costs and success of the development task. However, the quality of such specifications is often far from...
This electronic document is a “live” template and already defines the components of your paper [title, text, heads, etc.] in its style sheet. The paper considers the possibility and necessity of using in modern control and training systems with a natural language interface methods and mechanisms, characteristic for knowledge processing systems. This symbiosis assumes the introduction of specialized...
Rounding errors are introduced pervasively when using floating-point arithmetic to approximate real arithmetic. The accumulation or catastrophic cancellation of rounding errors in numerical programs may produce high inaccuracy results, which can cause serious software failures once being triggered. High inaccuracies are known hard to debug and fix manually for developers. Hence, the automated techniques...
Coreference resolution plays a significant role in natural language processing systems. It is the method of figuring out all the noun phrases that refer back to the identical real world entity. Several researches have been done in noun phrase coreference resolution by using certain machine learning techniques. Our paper proposes a machine learning approach using support vector machines (SVM) towards...
Multimedia semantic concept detection is one of the major research topics in multimedia data analysis in recent years. Disaster information management needs the assistance of multimedia data analysis to better utilize those disasterrelated information, which has been widely shared by people through the Internet. In this paper, a Feature Affinity based Multiple Correspondence Analysis and Decision...
Surveillance video parsing, which segments the video frames into several labels, e.g., face, pants, left-leg, has wide applications [41, 8]. However, pixel-wisely annotating all frames is tedious and inefficient. In this paper, we develop a Single frame Video Parsing (SVP) method which requires only one labeled frame per video in training stage. To parse one particular frame, the video segment preceding...
Zero-shot recognition aims to accurately recognize objects of unseen classes by using a shared visual-semantic mapping between the image feature space and the semantic embedding space. This mapping is learned on training data of seen classes and is expected to have transfer ability to unseen classes. In this paper, we tackle this problem by exploiting the intrinsic relationship between the semantic...
Developing reliable software at low cost is an objective for any software developer. Software errors are removed during the various review and test phases in the development lifecycle. Software is modified to eliminate these errors. Changes are implemented during the maintenance phases also. These software changes and fixes may introduce new errors and can cause defect propagation in different dependent...
The semantic description of remote sensing image is a useful and meaningful task, which can help us to get a better understanding of the scene depicted in the remote sensing images and make better use of the remote sensing images. Nature language provides good solution for describing the semantic information of remote sensing images. Nature language description of a remote sensing image is to generate...
Image and video captioning are important tasks in visual data analytics, as they concern the capability of describing visual content in natural language. They are the pillars of query answering systems, improve indexing and search and allow a natural form of human-machine interaction. Even though promising deep learning strategies are becoming popular, the heterogeneity of large image archives makes...
UML Interactions represent one of the three UML behaviors. They describe the interwork of parts of a system based on message exchange. UML Interactions can reside on any level of abstraction and they seem sufficiently elaborated for high-level specifications used for sketching the communication among parts of a system. The UML Interactions metamodel, however, reveals some deficiencies for precise...
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