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This short empirical paper investigates how well topic modeling and database meta-data characteristics can classify web and other proof-of-concept (PoC) exploits for publicly disclosed software vulnerabilities. By using a dataset comprised of over 36 thousand PoC exploits, near a 0.9 accuracy rate is obtained in the empirical experiment. Text mining and topic modeling are a significant boost factor...
Depth map estimation forms an integral part of many applications such as 2D-to-3D creation. There exists various methods in literature for depth map estimation using different cues and structure. Usually, depth information is decoded from these cues at the edges and matting is applied to spread it over neighboring regions. Defocus is one such cue due to its natural existence and does not require any...
We consider the problem of signal segmentation in the setup of supervised learning. The supervision lies here in the existence of labelled change points in a historical database of similar signals. Typical segmentation techniques rely on a penalized least square procedure where the smoothing parameter is fixed arbitrarily. We introduce the alpin (Adaptive Linear Penalty INference) algorithm to tune...
In the past decades, massive attention has been paid toward no-reference or blind image sharpness assessment (BISA) and many algorithms have achieved good performance. This paper provides an evaluation of 12 state-of-the-art BISA methods based on Gaussian blurring images collected from four simulation databases (LIVE, CSIQ, TID2008 and TID2013). The prediction performance is estimated with two metrics...
This paper revisits visual saliency prediction by evaluating the recent advancements in this field such as crowd-sourced mouse tracking-based databases and contextual annotations. We pursue a critical and quantitative approach towards some of the new challenges including the quality of mouse tracking versus eye tracking for model training and evaluation. We extend quantitative evaluation of models...
The GOES-R Flight Project has developed an Image Navigation and Registration (INR) Performance Assessment Tool Set (IPATS) for measuring Advanced Baseline Imager (ABI) and Geostationary Lightning Mapper (GLM) INR performance metrics in the post-launch period for performance evaluation and long term monitoring. IPATS utilizes a modular algorithmic design to allow user selection of data processing sequences...
First-person videos (FPVs) in daily living help us to memorize our life experience and information systems to process daily activities. Summarizing FPVs into key frames that represent the entire data would allow us to remember our memory in the past and computers to efficiently process the data. However, most video summarization approaches only use visual information, even though our daily activities...
Reliable management of modern cloud computing infrastructures is unrealizable without monitoring and analysis of a huge number of system indicators (metrics) as time series data stored in big databases. Efficient storage and processing of collected historical data from all "objects" of those infrastructures are technology challenges for this Big Data application. We propose a data compression...
Internet is popular for people at all ages. A computer is used to access the Internet but a user needs to authenticate himself to the system in order to gain access. The problem of a typical authentication technique is to memorize a password. Lots of junior high school students in Pakthongchaiprachaniramit School cannot remember their own password and this work is proposed to solve the problem by...
Face recognition methods utilizing Sparse Representation based Classification (SRC) and Collaborative Representation based Classification (CRC) have recently attracted a great deal of attention due to inherent simplicity and efficiency. In this paper, we introduce the Large Margin Nearest Neighbor (LMNN), which learns a Mahalanobis distance metric that is applied, to SRC and CRC as the locality constraint...
In this paper, we present a new benchmark (Menpo benchmark) for facial landmark localisation and summarise the results of the recent competition, so-called Menpo Challenge, run in conjunction to CVPR 2017. The Menpo benchmark, contrary to the previous benchmarks such as 300-W and 300-VW, contains facial images both in (nearly) frontal, as well as in profile pose (annotated with a different markup...
Automated affective computing in the wild is a challenging task in the field of computer vision. This paper presents three neural network-based methods proposed for the task of facial affect estimation submitted to the First Affect-in-the-Wild challenge. These methods are based on Inception-ResNet modules redesigned specifically for the task of facial affect estimation. These methods are: Shallow...
Free view point video (FVV), which offers immersive experience to users with multiple views, is one of the new trends in advanced visual media. These new viewpoints are traditionally synthesized via depth image-based rendering(DIBR) and geometric distortions are therefore observed. Mid-level contours descriptors are capable of evaluating such edges incoherence among the synthesized images which common...
Model-based software development promises improvements in terms of quality and cost by raising the abstraction level of the development from code to models, but also requires mature techniques and tools. Although Eclipse Modelling Framework (EMF) introduces a default persistence mechanism for models, namely XMI, its usage is often limited as model size increases. To overcome this limitation, during...
The relation between fetal heart rate and the value of umbilical cord artery pH is not something new for the scientific community. However, the problem has not been investigated sufficiently. One reason for that is the lack of open databases with a large number of recordings. Such a database is used here, recently publicly available, with cardiotocographic data recorded approximately two hours before...
Software installed on a computer does have security vulnerabilities to which an attacker can have access and do harm to the computer. It is known to be a good practice to install updates or upgrade versions of the software regularly to improve features, stability, and security, but often those updates and upgrades are ignored or delayed for several reasons. In addition, the new releases may come with...
Code portability is a desirable non-functional requirement. The most established metric evaluating it consists of counting the number of instructions that use platform specific APIs. Generally, instructions using APIs are preceded or followed by related code that e.g. prepares some input for a call or analyses the return value. This paper proposes a taint analysis approach to identify code portions...
With the growth of Infrastructure as a Service (IaaS) in cloud computing, and the Internet of Things (IoT), network monitoring of the global infrastructure will continue to expand, as cybersecurity will become of primary importance. Current network monitoring approaches, particularly those that are agent-based, are proprietary, costly, and may not scale. This paper proposes a lightweight, scalable...
Distribution of intangible information goods is experiencing tremendous growth in recent years, which has facilitated a blossoming of information goods economics. As big data develops, there are more and more information goods markets for data trading. In the current of data pricing policies in data trading, there are many metrics to measure the value of data goods, such as the data generation date,...
Memcached is a widely used in-memory caching solution in large-scale searching scenarios. The most pivotal performance metric in Memcached is latency, which is affected by various factors including the workload pattern, the service rate, the unbalanced load distribution and the cache miss ratio. To quantitate the impact of each factor on latency, we establish a theoretical model for the Memcached...
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