scispace - formally typeset
Search or ask a question
Author

Timo Hämäläinen

Other affiliations: Dalian Medical University, Nokia, Dublin Institute of Technology  ...read more
Bio: Timo Hämäläinen is an academic researcher from University of Jyväskylä. The author has contributed to research in topics: Quality of service & Encoder. The author has an hindex of 38, co-authored 560 publications receiving 7648 citations. Previous affiliations of Timo Hämäläinen include Dalian Medical University & Nokia.


Papers
More filters
Proceedings ArticleDOI
07 May 2001
TL;DR: A new video encoder proposal, H.26L, is compared against H.263 and H.264 and the trade-off possibilities between the complexity and compression performance within H.262 are presented.
Abstract: A new video encoder proposal, H.26L, is compared against H.263 and H.263+. In the comparison, both computational complexity and compression performance are analyzed. Moreover, the trade-off possibilities between the complexity and compression performance within H.26L are presented. Experimental comparisons with H.263 and H.263+ show that H.26L reduces the output bit rate about 30% with the same quality. The computation time increases about three times compared to H.263 and leads into the encoding speed of 3-6 fps for QCIF sequences on a 400 MHz Pentium III processor. Realtime operation can be achieved by applying additional, algorithmic and platform-specific optimizations.

29 citations

Journal ArticleDOI
TL;DR: A novel Deep Learning stack for detecting Advanced Persistent threat (APT) attacks based on a theoretical approach where an APT is observed as a multi-vector multi-stage attack with a continuous strategic campaign is presented.
Abstract: We present a novel Deep Learning (DL) stack for detecting Advanced Persistent threat (APT) attacks. This model is based on a theoretical approach where an APT is observed as a multi-vector multi-stage attack with a continuous strategic campaign. To capture these attacks, the entire network flow and particularly raw data must be used as an input for the detection process. By combining different types of tailored DL-methods, it is possible to capture certain types of anomalies and behaviour. Our method essentially breaks down a bigger problem into smaller tasks, tries to solve these sequentially and finally returns a conclusive result. This concept paper outlines, for example, the problems and possible solutions for the tasks. Additionally, we describe how we will be developing, implementing and testing the method in the near future.

27 citations

Proceedings ArticleDOI
01 Oct 2015
TL;DR: Key parallelization strategies of the Kvazaar HEVC intra encoder for multicore processors are introduced and its rate-distortion-complexity characteristics are superior to other public implementations in all-intra (AI) coding.
Abstract: This paper introduces key parallelization strategies of our Kvazaar HEVC intra encoder for multicore processors. The schemes implemented in Kvazaar are 1) tiles; 2) Wavefront Parallel Processing (WPP); and 3) picture-level parallel processing. Kvazaar is the only practical open-source HEVC encoder that supports all these schemes. In addition, its rate-distortion-complexity characteristics are superior to other public implementations in all-intra (AI) coding. Our experiments with high-quality encoder presets show that a C implementation of Kvazaar is 19% faster than the corresponding implementation of x265 for the same coding efficiency with 8 threads and 38% faster with 16 threads. With the high-speed presets, Kvazaar improves coding efficiency by 4.5% while being twice as fast as x265. The high-speed preset of Kvazaar obtains almost the same coding efficiency as the high-quality preset of f265 while being 24 times faster when 16 threads are used.

27 citations

Journal ArticleDOI
TL;DR: A configurable motion estimation architecture for a wide range of fast block-matching algorithms (BMAs) based on a new BMA framework that can be adjusted to support the desired set of BMAs and is very tolerant of different BMA-specific search strategies and search patterns.
Abstract: This paper introduces a configurable motion estimation architecture for a wide range of fast block-matching algorithms (BMAs). Contemporary motion estimation architectures are either too rigid for multiple BMAs or the flexibility in them is implemented at the cost of reduced performance. The proposed architecture overcomes both of these limitations. The configurability of the proposed architecture is based on a new BMA framework that can be adjusted to support the desired set of BMAs. The chosen framework configuration is implemented by an intelligent control logic which is integrated to an efficient parallel memory system and distortion computation unit. The flexibility of the framework is demonstrated by mapping five different BMAs (BBGDS, DS, CDS, HEXBS, and TSS) to the architecture. The total execution time of the mapped BMAs is shown to be almost directly proportional to the number of tested checking points in the search area, so the architecture is very tolerant of different BMA-specific search strategies and search patterns. In addition, a run-time switching between supported BMAs can be done without performance compromises. With a 0.13-mum CMOS technology, the proposed architecture configured for HEXBS, BBGDS, and TSS requires only 14.2 kgates and 2.5 KB of memory at 200 MHz operating frequency. A performance comparison to the reference programmable architectures reveals that only the proposed implementation is able to process real-time (30 fps) fixed block-size motion estimation (1 reference frame) at full HDTV resolution (1920 times1080).

27 citations

Proceedings ArticleDOI
10 Dec 2002
TL;DR: These models for the 3G/4G service pricing including QoS are introduced and the importance of pricing versus the acceptance of services will be a very delicate and important matter that must be dealt very gently.
Abstract: Pricing of the future multimedia services in the 3G/4G networks will play a key role from operator's point of view to achieve the maximum revenue and maximizing ROY. On the other hand pricing of the various new services is a very important issue to subscribers and especially the pricing versus the acceptance of services will be a very delicate and important matter that must be dealt very gently. This paper introduces models for the 3G/4G service pricing including QoS.

27 citations


Cited by
More filters
Journal ArticleDOI

[...]

08 Dec 2001-BMJ
TL;DR: There is, I think, something ethereal about i —the square root of minus one, which seems an odd beast at that time—an intruder hovering on the edge of reality.
Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

33,785 citations

Journal ArticleDOI
TL;DR: Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis.
Abstract: Machine Learning is the study of methods for programming computers to learn. Computers are applied to a wide range of tasks, and for most of these it is relatively easy for programmers to design and implement the necessary software. However, there are many tasks for which this is difficult or impossible. These can be divided into four general categories. First, there are problems for which there exist no human experts. For example, in modern automated manufacturing facilities, there is a need to predict machine failures before they occur by analyzing sensor readings. Because the machines are new, there are no human experts who can be interviewed by a programmer to provide the knowledge necessary to build a computer system. A machine learning system can study recorded data and subsequent machine failures and learn prediction rules. Second, there are problems where human experts exist, but where they are unable to explain their expertise. This is the case in many perceptual tasks, such as speech recognition, hand-writing recognition, and natural language understanding. Virtually all humans exhibit expert-level abilities on these tasks, but none of them can describe the detailed steps that they follow as they perform them. Fortunately, humans can provide machines with examples of the inputs and correct outputs for these tasks, so machine learning algorithms can learn to map the inputs to the outputs. Third, there are problems where phenomena are changing rapidly. In finance, for example, people would like to predict the future behavior of the stock market, of consumer purchases, or of exchange rates. These behaviors change frequently, so that even if a programmer could construct a good predictive computer program, it would need to be rewritten frequently. A learning program can relieve the programmer of this burden by constantly modifying and tuning a set of learned prediction rules. Fourth, there are applications that need to be customized for each computer user separately. Consider, for example, a program to filter unwanted electronic mail messages. Different users will need different filters. It is unreasonable to expect each user to program his or her own rules, and it is infeasible to provide every user with a software engineer to keep the rules up-to-date. A machine learning system can learn which mail messages the user rejects and maintain the filtering rules automatically. Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis. Statistics focuses on understanding the phenomena that have generated the data, often with the goal of testing different hypotheses about those phenomena. Data mining seeks to find patterns in the data that are understandable by people. Psychological studies of human learning aspire to understand the mechanisms underlying the various learning behaviors exhibited by people (concept learning, skill acquisition, strategy change, etc.).

13,246 citations

Journal ArticleDOI
01 Nov 2007
TL;DR: Comprehensive performance comparisons including accuracy, precision, complexity, scalability, robustness, and cost are presented.
Abstract: Wireless indoor positioning systems have become very popular in recent years. These systems have been successfully used in many applications such as asset tracking and inventory management. This paper provides an overview of the existing wireless indoor positioning solutions and attempts to classify different techniques and systems. Three typical location estimation schemes of triangulation, scene analysis, and proximity are analyzed. We also discuss location fingerprinting in detail since it is used in most current system or solutions. We then examine a set of properties by which location systems are evaluated, and apply this evaluation method to survey a number of existing systems. Comprehensive performance comparisons including accuracy, precision, complexity, scalability, robustness, and cost are presented.

4,123 citations

01 Jan 2006

3,012 citations

01 Jan 1990
TL;DR: An overview of the self-organizing map algorithm, on which the papers in this issue are based, is presented in this article, where the authors present an overview of their work.
Abstract: An overview of the self-organizing map algorithm, on which the papers in this issue are based, is presented in this article.

2,933 citations