Software variability engineering benefits from Machine Learning (ML) to learn e.g., variability-aware performance models, explore variants of interest and minimize their energy impact. As the number of applications of combining variability with ML ...

Feature modeling is a process for identifying the common and variable parts of a software product line and recording them in a tree-structured feature model. However, feature models can be difficult for mainstream developers to specify and maintain ...

Low-light image processing is a common issue in industry, media and other practical application fields. Enhancing image brightness or contrast directly may bring accompanying noise and color cast. The proposed method is a feature based deep F-Retinex-...

Software errors are a major nuisance in software development and can lead not only to reputation damages, but also to considerable financial losses for companies. Therefore, numerous techniques for predicting software defects, largely based on machine ...

Software Product Lines (SPLs) are Software Engineering methodologies that manage the development and evolution of families of product variants. They aim at handling the commonality and variability of these products. SPLs reduce the development cost, ...

As a key data-integration step, entity matching (EM) identifies tuples referring to the same real-world entities in disparate data sources. In many cases, the EM quality can be improved by repairing incorrect values in the data; at the same time, it is ...

Video Shot Detection plays a vital role in the analysis of the contents in Video. The algorithms and methodologies learnt from Video Shot Detection has a wide range of applications starting from Video Browsing, Content-based Video Retrieval and Storage, ...

Online digital collectible card games have seen a massive rise in popularity recently, none more so than Hearthstone: Heroes of Warcraft. While the game is mainly player vs. player focused, a need for competent game playing AI has arisen as well. This ...

This paper summarized the basic process of software vulnerability prediction using feature-based machine learning for the first time. In addition to sorting out the related types and basis of vulnerability features definition, the advantages and ...

Fast changing hardware and software technologies in addition to larger and more specialized customer bases demand software tailored to meet very diverse requirements. Software development approaches that aim at capturing this diversity on a single ...

Enterprise Resource Planning (ERP) system vendors need to customize their products according to the domain-specific requirements of their customers. Systematic reuse of features and related ERP product customizations would improve software quality and ...

As the number of mobile apps increases rapidly, many users may install dozens of, or even hundreds of, apps on a single smartphone. However, many apps on the same phone may contain similar or even the same feature, resulting in feature redundancy. For ...

The study of the evolution of highly configurable systems requires a thorough understanding of thee core ingredients of such systems: (1) the underlying variability model; (2) the assets that together implement the configurable features; and (3) the ...

This research seeks to develop neural network techniques to effectively recognize actions in videos. The proposed study will lead to a deeper understanding of how neural network algorithms can help AI systems to understand motions. It will also realize ...

Personal and participatory environmental sensing, especially of air quality, is a topic of increasing importance. However, as the employed sensors are often cheap, they are prone to erroneous readings, e.g. due to sensor aging or low selectivity. ...

The Base Variability Resolution (BVR) is a modern language to build software product lines (SPL). The language incorporates advanced concepts for feature modeling, reuse and realization of components in SPL. The BVR bundle implements and supports the ...

Classification of HEp-2 cell images is seeing an increasing interest in the last years. Research on this subject is being further stimulated by contests in important pattern recognition conferences (ICPR-2012, ICIP-2013 and ICPR-2014). Several feature ...

Mining features and opinion words is essential for fine-grained opinion analysis of customer reviews. It is observed that semantic dependencies naturally exist between features and opinion words, even among features or opinion words themselves. In this ...

The diversity of requirements elicited from different customers leads to the development of many variants. Furthermore, compliance with safety standards as mandated for safety-critical systems requires high test efforts for each variant. Model-based ...

In content-based image retrieval (CBIR), images are usually represented by local invariant features or global features. Although great success has been witnessed, there still exists some non-trivial problems with those features. In this paper, we ...