Michał Karwatowski

• Assistant at AGH University of Krakow

The primary objective of this research was to enhance the quality of semantic segmentation in cytology images by incorporating super-resolution (SR) architectures. An additional contribution was the development of a novel dataset aimed at improving imaging quality in the presence of inaccurate focus. Our experimental results demonstrate that the in...

This paper presents a computer-aided cytology diagnosis system designed for animals, focusing on image quality assessment (IQA) using Convolutional Neural Networks (CNNs). The system's building blocks are tailored to seamlessly integrate IQA, ensuring reliable performance in disease classification. We extensively investigate the CNN's ability to ha...

The primary objective of this research was to enhance the quality of semantic segmentation in cytology images by incorporating super-resolution (SR) architectures. An additional contribution was the development of a novel dataset aimed at improving imaging quality in the presence of inaccurate focus. Our experimental results demonstrate that the in...

This paper shows the machine learning system which performs instance segmentation of cytological images in veterinary medicine. Eleven cell types were used directly and indirectly in the experiments, including damaged and unrecognized categories. The deep learning models employed in the system achieve a high score of average precision and recall me...

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...

Lemmatization is the process of grouping together the inflected forms of a word so they can be analysed as a single item, identified by the word's lemma, or dictionary form. In computational linguistics, lemmatisation is the algorithmic process of determining the lemma of a word based on its intended meaning. Unlike stemming, lemmatisation depends...

We present the experiment results to use the YOLOv3 neural network architecture to automatically detect tumor cells in cytological samples taken from the skin in canines. A rich dataset of 1219 smeared sample images with 28,149 objects was gathered and annotated by the vet doctor to perform the experiments. It covers three types of common round cel...

This paper presents an approach to text-based data classification when only a limited number of positive samples are provided with additional challenge that classes are not mutually exclusive. The main goal is to develop an algorithm which can address a specific case of overlapping classes. The proposed solution encompasses a set of steps to be tak...

Convolutional Neural Networks (CNNs) were created for image classification tasks. Quickly, they were applied to other domains, including Natural Language Processing (NLP). Nowadays, the solutions based on artificial intelligence appear on mobile devices and in embedded systems, which places constraints on, among others, the memory and power consump...

Internet of things (IoT) infrastructure, fast access to knowledge becomes critical. In some application domains, such as robotics, autonomous driving, predictive maintenance, and anomaly detection, the response time of the system is more critical to ensure Quality of Service than the quality of the answer. In this paper, we propose a methodology, a...

Convolutional neural networks are modern models that are very efficient in many classification tasks. They were originally created for image processing purposes. Then some trials were performed to use them in different domains like natural language processing. The artificial intelligence systems (like humanoid robots) are very often based on embedd...

This paper addresses the problem of building a specialized semantic search engine for documents collected in small or medium-sized enterprises. It presents the results of a project that brought together computer scientists and entrepreneurs for the purpose of providing a common perspective regarding the implementation in company practice of a searc...

This paper presents the analysis of the impact of a floating-point number precision reduction on the quality of text classification. The precision reduction of the vectors representing the data (e.g. TF-IDF representation in our case) allows for a decrease of computing time and memory footprint on dedicated hardware platforms. The impact of precisi...

This paper addresses the problem of building a specialized semantic search engine for documents collected in small or medium-sized enterprises. It presents the results of a project that brought together computer scientists and entrepreneurs for the purpose of providing a common perspective regarding the implementation in company practice of a searc...

Video resolutions used in variety of media are constantly rising. While manufacturers struggle to perfect their screens it also important to ensure high quality of displayed image. Overall quality can be measured using Mean Opinion Score (MOS). Video quality can be affected by miscellaneous artifacts, appearing at every stage of video creation and...

Video resolutions used in variety of media are constantly rising. While manufacturers struggle to perfect their screens it is also important to ensure high quality of displayed image. Overall quality can be measured using Mean Opinion Score (MOS). Video quality can be affected by miscellaneous artifacts, appearing at every stage of video creation a...

This paper presents an impact of the customized hardware accelerator on the overall performance of the text similarity computing system. The hardware processing module that is presented in the paper is a building block of the processing engine in the search system of related documents. The engine is used in the phase of preliminary retrieval of sim...