12 citations · 26 across the 11 of their papers we have counts for
12 papers
Using simulation to calibrate real data acquisition in veterinary medicine
Krystian Strzałka, Szymon Mazurek, Maciej Wielgosz +12
This paper explores the innovative use of simulation environments to enhance data acquisition and diagnostics in veterinary medicine, focusing specifically on gait analysis in dogs…
Using super-resolution for enhancing visual perception and segmentation performance in veterinary cytology
Jakub Caputa, Maciej Wielgosz, Daria Łukasik +11
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 co…
J-Parallelio -- automatic parallelization framework for Java virtual machine code
Krzysztof Stuglik, Piotr Listkiewicz, Mateusz Kulczyk +1
Manual translation of the algorithms from sequential version to its parallel counterpart is time consuming and can be done only with the specific knowledge of hardware accelerator…
Context based lemmatizer for Polish language
Michal Karwatowski, Marcin Pietron
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 com…
When deep learning models on GPU can be accelerated by taking advantage of unstructured sparsity
Marcin Pietroń, Dominik Żurek
This paper is focused on the improvement the efficiency of the sparse convolutional neural networks (CNNs) layers on graphic processing units (GPU). The Nvidia deep neural network…
Retrain or not retrain? -- efficient pruning methods of deep CNN networks
Marcin Pietron, Maciej Wielgosz
Convolutional neural networks (CNN) play a major role in image processing tasks like image classification, object detection, semantic segmentation. Very often CNN networks have fro…
Ensemble approach for natural language question answering problem
Anna Aniol, Marcin Pietron
Machine comprehension, answering a question depending on a given context paragraph is a typical task of Natural Language Understanding. It requires to model complex dependencies ex…
Method for Hybrid Precision Convolutional Neural Network Representation
Mo'taz Al-Hami, Marcin Pietron, Rishi Kumar +3
This invention addresses fixed-point representations of convolutional neural networks (CNN) in integrated circuits. When quantizing a CNN for a practical implementation there is a…
Convolutional neural network compression for natural language processing
Krzysztof Wróbel, Marcin Pietroń, Maciej Wielgosz +2
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 w…
Using Spatial Pooler of Hierarchical Temporal Memory to classify noisy videos with predefined complexity
Maciej Wielgosz, Marcin Pietroń
This paper examines the performance of a Spatial Pooler (SP) of a Hierarchical Temporal Memory (HTM) in the task of noisy object recognition. To address this challenge, a dedicated…
OpenCL-accelerated object classification in video streams using Spatial Pooler of Hierarchical Temporal Memory
Maciej Wielgosz, Marcin Pietroń
We present a method to classify objects in video streams using a brain-inspired Hierarchical Temporal Memory (HTM) algorithm. Object classification is a challenging task where huma…
Formal analysis of HTM Spatial Pooler performance under predefined operation conditions
M. Pietron, M. Wielgosz, K. Wiatr
This paper introduces mathematical formalism for Spatial (SP) of Hierarchical Temporal Memory (HTM) with a spacial consideration for its hardware implementation. Performance of HTM…