Student IT/EE Workshop 2024

Session

Session C (Poster)

18 Apr 2024, 11:15

SK 04 / SK 05 (Warsaw University of Technology)

Conveners

Session C (Poster)

• Michał Śmiałek

11. Automated Liver Cancer Diagnosis: A Convolutional Neural Network Approach on CT Imaging

Justyna Budzyńska, Maria Kujawa

In recent years, deep neural networks (DNNs) have shown remarkable potential in medical image analysis, particularly in the field of computed tomography (CT) imaging. The use of DNNs to analyze medical images, especially in the context of detecting cancer, is becoming a promising area of research. In this study a novel approach to detect liver cancer using deep neural networks (DNNs) based on...

16. Comparative analysis of frontend layer design and implementation methods (Analiza porównawcza metod projektowania i implementacji warstwy frontend)

Mr Adrian Mostowski, Bartłomiej Kopyść, Mr Kacper Kuczewski

Abstract:

In software development, clean code and clean architecture are crucial aspects that
ensure separation between business logic, application logic, and framework-related
code. However, in the dynamic world of web development, these approaches are not
commonly utilized due to the lack of standardization among frontend frameworks and
libraries. This often leads to complications in...

33. Comparing UNET architectures in blood vessel segmentation task

Bartłomiej Anczok (Warsaw University Of Technology)

Advancements in UNet architectures have been pivotal in medical image segmentation, particularly for blood vessel segmentation, which is crucial for medical diagnosis and treatment. This article presents a comprehensive comparative study of various UNet models, examining their effectiveness in blood vessel identification within medical imaging. We explore the evolution of these models from the...

23. Comparison of the NLU and NLG transformers in the context of classifying fake news

Aleksandra Koźbiel, Olgierd Usidus

This research presents a comparative analysis of
Natural Language Understanding (NLU) and Natural Language
Generation (NLG) models for the task of fake news detection. A
concise literature review was conducted to understand the state-
of-the-art techniques in the field. The study focused on comparing
the performance of two language models, BERT (Bidirectional
Encoder Representations from...

20. Convolutional Neural Network for Diabetic Retinopathy Detection

Adrian Krzemiński, Hubert Kunikowski, Szymon Maliszewski

This scientific article describes a project focused on creating a convolutional neural network designed to assist physicians in diagnosing diabetic retinopathy based on Optical Coherence Tomography (OCT) images. The project involves an in-depth analysis of existing research on the classification of this disease using fundus images. Leveraging a diverse dataset of OCT images, encompassing both...

29. Detection of cancerous changes in microscopic specimens from the colon

Agnieszka Salwa, Dawid Szczawiński, Hubert Skibiński

Contemporary medical diagnostics increasingly utilise advanced information technologies to analyse microscopic specimens, crucial in detecting and diagnosing cancerous changes. In our work, we focused on the analysis of microscopic specimens from the colon, which is extremely important in detecting early stages of cancer. We used Python to process and analyse these images, offering extensive...

18. Energy trading optimization: A Comparative Analysis of Reinforcement Learning Techniques

KIatarzyna Prus

This paper embarks on a comparative study of three diverse reinforcement learning techniques applied to forecasting and optimizing energy trading in day-ahead markets for medium-sized prosumers. Given renewable energy sources' inherent volatility and unpredictability, this study leverages these diverse approaches, each known for its unique advantages in navigating complex optimisation...

28. Examination the combination of A2C Learning with Behavioral Cloning on a bot for the Blood Bowl board game

Mr Eryk Sędkowski, Wojciech Zieliński

This paper aims to improve existing solutions of machine-learned bots for the Blood Bowl game. Blood Bowl is a stochastic, fully-observable, turn-based, two-player board game. Players, referred to as coaches, lead an 11-player team, where each individual has statistics and abilities. A wide grid-based board, various moves, possible interruption of the game sequence, and randomness create a...

9. Learning a foreign language through voice conversation with AI chat

Dominik Biedrzycki (Politechnika Warszawska)

In this comprehensive exploration, the author delves
into a visionary initiative aimed at fundamentally transforming
language learning through the implementation of a groundbreaking Conversational AI system. The research underscores the
pivotal role of innovative features, particularly the successful
integration and testing of TextToSpeech and real-time translations, which have emerged as...

14. Picture Captioning

Mr Piotr Szczepański, Mr Karol Zieliński, Mr Albert Ziółkiewicz

The research focused on classic image captioning based on a coder-decoder structure, where the coder encodes the image features. At the same time, the decoder produces a caption – a phrase describing the image content. We investigated the decoder part by testing multiple convolutional-neural-network-based backbones – feature extractors. This investigation aimed to find the optimal encoder,...

7. Solutions of Maxwell equations for defining improvements of parallel computing with CUDA library

Maciej Konieczny

Maxwell equations are fundamental laws of physics for understanding electromagnetic fields. Their usage is essential in applications related to propagation of electromagnetic waves. To provide a numerical implementation of these equations, a Finite-Difference Time-Domain method can be used. It is crucial to optimize such complex calculations in order to provide convenient, time-saving tools....

25. Study of various applications of the A* algorithm in the context of overhead line routing.

Maciej Bukalski

The paper presents research on the usefulness of the A algorithm in the context of setting a route for an overhead power line. The algorithm was implemented in Python using the pyautocad library. The final result of the program is the marked route in a dwg file. The research examined how different ways of implementing the A algorithm and different heuristics affects its performance. The...

3. Text2SQL with „small” Large Language Models

Damian Janczarek

This article conducts a comprehensive comparison of Mistral7B and SQLCoder 2.0, two „small” large language models, in the context of the Text2SQL task using the „Spider” dataset. Despite its modest scale, Mistral7B achieves a notable 33% accuracy without any query-answer examples in the prompt, showcasing promising prospects for compact large language models in the Text2SQL domain. The...

4. The concept of a system for high-scale computing based on microservice architecture

Antoni Malinowski, Arkadiusz Kasprzak

This study introduces a microservice-based architecture designed to compute a large amount of data, offering scalable and modular system components. Main system concepts are illustrated through the example of credit risk management in a fictional banking system. The architecture's design principles emphasize scalability, domain separation, and technological agnosticism, aiming to ensure...