Håkan Grahn

Håkan Grahn
Blekinge Institute of Technology | BTH · Dept. of Computer Science

PhD

About

135
Publications
40,703
Reads
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1,437
Citations
Citations since 2016
37 Research Items
700 Citations
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2016201720182019202020212022050100150
2016201720182019202020212022050100150

Publications

Publications (135)
Article
Full-text available
The availability of large amounts of data in combination with Big Data analytics has transformed many application domains. In this paper, we provide insights into how the area has developed in the last decade. First, we identify seven major application areas and six groups of important enabling technologies for Big Data applications and systems. Th...
Article
Full-text available
Data has become an integral part of our society in the past years, arriving faster and in larger quantities than before. Traditional clustering algorithms rely on the availability of entire datasets to model them correctly and efficiently. Such requirements are not possible in the data stream clustering scenario, where data arrives and needs to be...
Article
Full-text available
Chromatic aberration is an error that occurs in color images due to the fact that camera lenses refract the light of different wavelengths in different angles. The common approach today to correct the error is to use a lookup table for each camera-lens combination, e.g., as in Adobe PhotoShop Lightroom or DxO Optics Pro. In this paper, we propose a...
Article
Full-text available
Recently machine learning researchers are designing algorithms that can run in embedded and mobile devices, which introduces additional constraints compared to traditional algorithm design approaches. One of these constraints is energy consumption, which directly translates to battery capacity for these devices. Streaming algorithms, such as the Ve...
Article
Full-text available
In this study, we propose a higher order mining approach that can be used for the analysis of real-world datasets. The approach can be used to monitor and identify the deviating operational behaviour of the studied phenomenon in the absence of prior knowledge about the data. The proposed approach consists of several different data analysis techniqu...
Article
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This paper introduces a new image-based handwritten historical digit dataset named Arkiv Digital Sweden (ARDIS). The images in ARDIS dataset are extracted from 15,000 Swedish church records which were written by different priests with various handwriting styles in the nineteenth and twentieth centuries. The constructed dataset consists of three sin...
Chapter
This paper compares three different word image representations as base for label free sample selection for word spotting in historical handwritten documents. These representations are a temporal pyramid representation based on pixel counts, a graph based representation, and a pyramidal histogram of characters (PHOC) representation predicted by a PH...
Article
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Energy consumption has been widely studied in the computer architecture field for decades. While the adoption of energy as a metric in machine learning is emerging, the majority of research is still primarily focused on obtaining high levels of accuracy without any computational constraint. We believe that one of the reasons for this lack of intere...
Chapter
Full-text available
Involving humans in the learning process of a machine learning algorithm can have many advantages ranging from establishing trust into a particular model to added personalization capabilities to reducing labeling efforts. While these approaches are commonly summarized under the term interactive machine learning (iML), no unambiguous definition of i...
Chapter
In this study we apply clustering techniques for analyzing and understanding households’ electricity consumption data. The knowledge extracted by this analysis is used to create a model of normal electricity consumption behavior for each particular household. Initially, the household’s electricity consumption data are partitioned into a number of c...
Chapter
Machine learning algorithms are responsible for a significant amount of computations. These computations are increasing with the advancements in different machine learning fields. For example, fields such as deep learning require algorithms to run during weeks consuming vast amounts of energy. While there is a trend in optimizing machine learning a...
Article
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In this paper, a new approach is proposed to enhance the handwriting image by using learning-based windowing contrast enhancement and Gaussian Mixture Model (GMM). A fixed size window moves over the handwriting image and two quantitative methods which are discrete entropy (DE) and edge-based contrast measure (EBCM) are used to estimate the quality...
Article
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The growth of Internet video and over-the-top transmission techniques has enabled online video service providers to deliver high quality video content to viewers. To maintain and improve the quality of experience, video providers need to detect unexpected issues that can highly affect the viewers' experience. This requires analyzing massive amounts...
Preprint
Machine learning software accounts for a significant amount of energy consumed in data centers. These algorithms are usually optimized towards predictive performance, i.e. accuracy, and scalability. This is the case of data stream mining algorithms. Although these algorithms are adaptive to the incoming data, they have fixed parameters from the beg...
Conference Paper
Full-text available
We propose a cluster analysis approach for organizing , visualizing and understanding households' electricity consumption data. We initially partition the consumption data into a number of clusters with similar daily electricity consumption profiles. The centroids of each cluster can be seen as representative signatures of a household's electricity...
Preprint
Full-text available
Graphics processing units (GPUs) in embedded mobile platforms are reaching performance levels where they may be useful for computer vision applications. We compare two generations of embedded GPUs for mobile devices when running a state-of-the-art feature detection algorithm, i.e., Harris-Hessian/FREAK. We compare architectural differences, executi...
Article
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In the context of historical document analysis, image binarization is a first important step, which separates foreground from background, despite common image degradations, such as faded ink, stains, or bleed-through. Fast binarization has great significance when analyzing vast archives of document images, since even small inefficiencies can quickl...
Conference Paper
This paper proposes a preprocessing stage to augment the bank of features that one can retrieve from binary images to help increase the accuracy of pattern recognition algorithms. To this end, by applying successive dilations to a given shape, we can capture a new dimension of its vital characteristics which we term hereafter: the shape growth patt...
Chapter
Full-text available
In telecommunication business, a major investment goes into the infrastructure and its maintenance, while business revenues are proportional to how big, good, and well-balanced the customer base is. We present a data-driven analytic strategy based on combinatorial optimization and analysis of the historical mobility designed to quantify the desirab...
Article
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The aim of this study is to improve the monitoring and controlling of heating systems located at customer buildings through the use of a decision support system. To achieve this, the proposed system applies a two-step classifier to detect manual changes of the temperature of the heating system. We apply data from the Swedish company NODA, active in...
Chapter
Data mining algorithms are usually designed to optimize a trade-off between predictive accuracy and computational efficiency. This paper introduces energy consumption and energy efficiency as important factors to consider during data mining algorithm analysis and evaluation. We conducted an experiment to illustrate how energy consumption and accura...
Conference Paper
Full-text available
GPUs in embedded platforms are reaching performance levels comparable to desktop hardware, thus it becomes interesting to apply Computer Vision techniques. We propose, implement, and evaluate a novel feature detector and descriptor combination, i.e., we combine the Harris-Hessian detector with the FREAK binary descriptor. The implementation is done...
Conference Paper
Full-text available
Readability of document images is one core issue when analysing historical documents. One way to improve the readability of those document images is image binarization. By separating the written text from its background, documents degraded by, e.g., stains or faded ink become better readable. Due to the large quantity of available historical docume...
Article
Thread-level speculation can be used to take advantage of multicore architectures for JavaScript in web applications. We extend previous studies with these main contributions; we implement thread-level speculation in the state-of-the art just-in-time-enabled JavaScript engine V8 and make the measurements in the Chromium web browser both from Google...
Conference Paper
Full-text available
Data mining algorithms are usually designed to optimize a trade-off between predictive accuracy and computational efficiency. This paper introduces energy consumption and energy efficiency as important factors to consider during data mining algorithm analysis and evaluation. We extended the CRISP (Cross Industry Standard Process for Data Mining) fr...
Article
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JPEG encoding is a common technique to compress images. However, since JPEG is a lossy compression certain artifacts may occur in the compressed image. These artifacts typically occur in high frequency or detailed areas of the image. This paper proposes an algorithm based on the SSIM metric to improve the experienced quality in JPEG encoded images....
Article
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JavaScript is a sequential programming language that has a large potential for parallel execution in Web applications. Thread-level speculation can take advantage of this, but it has a large memory overhead. In this article, we evaluate the effects of adjusting various parameters for thread-level speculation. Our results clearly show that thread-le...
Conference Paper
Full-text available
Thread-Level Speculation has been used to take advantage of multicore processors in virtual execution environments for the sequential JavaScript scripting language. While the results are promising the memory overhead is high. Here we propose to reduce the memory usage by limiting the checkpoint depth based on an in-depth study of the memory and exe...
Article
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JavaScript is a sequential programming language, and Thread-Level Speculation has been proposed to dynamically extract parallelism in order to take advantage of parallel hardware. In previous work, we have showed significant speed-ups with a simple on/off speculation heuristic. In this paper, we propose and evaluate three heuristics for dynamically...
Conference Paper
Full-text available
Thread-Level Speculation can be used to take advantage of multicore architectures for web applications. We have implemented Thread-Level Speculation in the state-of-the-art JavaScript engine V8 instead of using an interpreted JavaScript engine. We evaluate the implementation with the Chromium web browser on 15 popular web applications for 2, 4, and...
Conference Paper
Full-text available
We present the first implementation of Thread-Level Spec-ulation in combination with Just-in-time compilation. The implementation is done in Google's V8, a well-known JavaScript engine, and evaluated on 15 popular web application execut-ing on 2, 4, and 8 core computers. Our results show an aver-age speedup of 2.9 on 4 cores, without any JavaScript...
Conference Paper
Real-time video streaming suffer from bandwidth limitation that are unable to handle the high amount of video data. To reduce the amount of data to be streamed, we propose an adaptive technique to crop the important part of the video frames, and drop the part that are outside the important part; this part is called the Region of Interest (ROI). The...
Article
JavaScript lets developers provide client-side interactivity in Web applications, but because it is sequential, it can't take advantage of multicore processors. Thread-level speculation (TLS) addresses this issue by enabling the speculation of JavaScript function calls and thus exploits the parallel performance potential multicore processors provid...
Article
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In real time video streaming, the frames must meet their timing constraints, typically specified as their deadlines. Wireless networks may suffer from bandwidth limitations. To reduce the data transmission over the wireless networks, we propose an adaption technique in the server side by extracting a part of the video frames that considered as a Re...
Conference Paper
Streaming real time video over wireless networks cannot guarantee that all the frames could meet their deadlines. Wireless networks may suffer from bandwidth limitations. To reduce the streaming data over wireless networks, we propose a technique to identify, and extract the Region Of Interest (ROI), and drop the non-ROI from the frames that are be...
Conference Paper
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Railway traffic disturbances occur and train dispatchers make re-scheduling deci-sions in order to reduce the delays. In order to support the dispatchers, good re-scheduling strategies are required that could reduce the delays. We propose and evaluate re-scheduling strategies based on: (i) earliest start time, (ii) earliest track release time, (iii...
Article
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The fundamental structure of a software system is referred to as the software architecture. Researchers have identified that the quality attributes of a software system, e.g., performance and maintainability, often are restricted by the architecture. Therefore, it is important to evaluate the quality properties of a system already during architec-t...
Article
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Testing is an important activity in all software development projects and organizations. Therefore, it is important that all parts of the organization have the same view on testing and testability of software components and systems. In this paper we study the view on testability by software engineers, software testers, and managers, using a questio...
Article
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Rankings of different research bodies are of particular interest for academia and bibliometrics is used to measure the quality of these research bodies. Different factors affecting this quality have been proposed. In this paper, we have demonstrated a new approach based on fuzzy models and taken into account different proposed factors to access the...
Article
Full-text available
A software architecture is one of the first steps towards a software system. The design of the architecture is impor-tant in order to create a good foundation for the system. The design process is performed by evaluating architec-ture alternatives against each other. A desirable property of a good evaluation method is high efficiency at low cost. I...
Article
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Collaboration between industry and academia supports improvement and innovation in industry and helps to ensure industrial relevance in academic research. This article presents an exploratory study of factors for successful collaboration between industry and academia. A survey designed for data collection was first conducted in Sweden and then repl...
Conference Paper
Full-text available
Railways are an important part of the infrastructure in most countries. As the railway networks become more and more saturated, even small traffic disturbances can propagate and have severe consequences. Therefore, ef-ficient re-scheduling support for the traffic managers is needed. In this paper, the train real-time re-scheduling problem is studie...
Article
Real-time video streaming over wireless channel has become an important issue due to the limited bandwidth that is unable to handle the flow of information of the video frames. The characteristics of wireless networks in terms of the available bandwidth, frame delay, and frame losses cannot be known in advance. As the effect of that, the user may n...
Conference Paper
Full-text available
JavaScript has gone from being a mechanism for providing dynamic web pages to an important component of many web applications. Currently one of the most popular type of web applications is so-called social networks, e.g., Facebook, Twitter, and MySpace. However, the workload and execution behavior of JavaScript in this context have not been fully e...
Conference Paper
Full-text available
Machine learning algorithms are frequently applied in data mining applications. Many of the tasks in this domain concern high-dimensional data. Consequently, these tasks are often complex and computationally expensive. This paper presents a GPU-based parallel implementation of the Random Forests algorithm. In contrast to previous work, the proposed...
Conference Paper
Full-text available
Web Applications have become increasingly popular as they allow developers to use an uniform platform for user interactions. The dynamic programming language JavaScript used in most Web Applications has performance penalties, that have been addressed by traditional optimization techniques. We have found that while the performance gain of such techn...
Conference Paper
Full-text available
JavaScript is a dynamically typed, object-based scripting language with runtime evaluation. It has emerged as an important language for client-side computation of web applications. Previous studies indicate some differences in execution behavior between established benchmarks and real-world web applications. Our study extends previous studies by s...