Maciej Wielgosz - IEEE Xplore Author Profile

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In the dynamic field of satellite imagery, the significance of super-resolution (SR) techniques, grounded on advanced deep learning methods, is paramount. A thorough understanding and remediation of the distinct challenges posed by various land cover types for image resolution enhancement form the essence of this research. This work diligently employs two unique neural networks, SRCNN and SwinIR T...Show More
Pedestrian intention prediction is crucial for autonomous driving. In particular, knowing if pedestrians are going to cross in front of the ego-vehicle is core to performing safe and comfortable maneuvers. Creating accurate and fast models that predict such intentions from sequential images is challenging. A factor contributing to this is the lack of datasets with diverse crossing and non-crossing...Show More
The main goal of this work was to implement a reliable machine learning algorithm that can classify a dog’s age given only a photograph of its face. The problem, which seems simple for humans, presents itself as very difficult for the machine learning algorithms due to differences in facial features among the dog population. As convolutional neural networks (CNNs) performed poorly in this problem,...Show More
Nowadays, recurrent neural networks (RNN) and convolutional neural networks (CNN) play a major role in a lot of natural language domains like text document categorization, part of speech tagging, chatbots, language modeling or language translation. Very often RNN networks have a few stacked layers with several megabytes of memory, the same is in case of CNN networks. In many domains like automatic...Show More
In real-world applications - to minimize the impact of failures - machinery is often monitored by various sensors. Their role comes down to acquiring data and sending it to a more powerful entity, such as an embedded computer or cloud server. There have been attempts to reduce the computational effort related to data processing in order to use edge computing for predictive maintenance. The aim of ...Show More
Demand for high availability and performance of the LHC accelerator imposes stringent constraints on safety-critical systems handled by Machine Protection and Electrical Integrity Group at CERN. Consequently, unique means and equipment were introduced to monitor and protect superconducting magnets of the LHC. This work intends to ameliorate available algorithms by using RNN (Recurrent Neural Netwo...Show More
This paper presents a set of methods for effective compression of 3D-CNN deep learning architectures with a particular focus on embedded platforms. Deep learning models are massive regarding the number of parameters, especially in video processing. Such memory consumption poses a challenge when it comes to efficient deployment to embedded devices. The authors applied a series of quantization and p...Show More
This paper presents an analysis of an impact of a precision reduction on a performance of the cosine similarity measure in a document comparison task. The precision reduction of semantic vectors allows for a substantial computing performance improvement at the expense of a negligible decline of a comparison quality. In order to take an advantage of the precision reduction in terms of a lower numbe...Show More
This paper focuses on analyzing a Spatial Pooler (SP) of Hierarchical Temporal Memory (HTM) ability for facilitating object classification in noisy video streams. In particular, we seek to determine whether employing SP as a component of the video system increases overall robustness to noise. We have implemented our own version of HTM and applied it to object recognition tasks under various testin...Show More
Field-programmable gate arrays (FPGAs) are widely used in telecommunication due their substantial computational power and flexibly designed architecture. These features become especially important for applications of low transmission latency such as those supported by Distributed Multimedia Plays (DMP) architecture. Thus FPGAs are chosen in this work as the core building block of the system. Compl...Show More
This paper presents results of the tests performed to determine high speed calculations capabilities of the SGI RASC platform. Different data transfer modes and memory management approaches were examined to choose the most effective combination of the Host and RASC memory adjustments. Obtained results of measurements revealed that Direct I/O mode together with DMA transfer provides the highest dat...Show More
Most presented implementations of the exponential function confine to the single precision format. Increasing data width to the double precision format requires a different approach. The presented novel architecture employs three independent Look-Up Tables (LUTs) together with a short Taylor expansion exp(x)≈1+x. Implementation results show that the double precision exp() function implementation a...Show More
Highly parallel architecture for local histogram equalisation is studied. Three different kinds of approaches to the parallel architecture are regarded in this paper. (1) Module-level -which focuses on processing as many data as possible within a single module. (2) 1D -Several modules conducting simultaneously histogram equalization on partially overlapping (either horizontally or vertically) fram...Show More