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Creating a Python-based Automated System for Recognizing Emotions from Facial Expressions.
Zima, Samuel ; Malik, Aamir Saeed (oponent) ; Hussain, Yasir (vedoucí práce)
This thesis examines facial expression recognition (FER) using deep learning by focusing on its application in devices with limited memory and computational resources. It begins by researching emotions and facial expressions from psychological, biological, and sociological perspectives. The core of this thesis involves the design and implementation of an automated FER system using the FER-2013 dataset. This system uses a customized SqueezeNet architecture enhanced with a simple bypass, dropout layers and batch normalization layers. This system achieves an accuracy of 66.37 % on the FER-2013 dataset. For comparative analysis, this model was compared with a customized VGG16 architecture which achieved an accuracy of 65.09 %. This thesis provides valuable insights into the development of smaller, more efficient machine learning models for FER which are usable in a wide range of devices, including low-performance CPUs and embedded devices.
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Game Development for Assessment of Human Memory, Attention and Reflexes
Petrovskyi, Denys ; Hussain, Yasir (oponent) ; Malik, Aamir Saeed (vedoucí práce)
This thesis details the development of an Android application designed to simultaneously assess memory, attention and reflexes. The main goal was to create an interactive platform that not only engages users in cognitive tasks, but also allows them to track their performance over time through statistical analysis and progress graphs. Using the Flutter framework, the application offers a user-friendly and clear design, integrated with Firebase for efficient user data management and authentication. The project involved the development of a series of cognitive modules integrated into a single game that dynamically adjusts to the user's results, ensuring accurate assessments and user engagement. The user interface was designed to be intuitive, ensuring ease of use and accessibility. User test results show that the application successfully measures cognitive abilities and provides users with valuable feedback, thereby supporting continuous cognitive improvement. This work demonstrates the potential of gamified cognitive assessments in mobile applications, contributing to the fields of educational technology and cognitive psychology.
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Cognitive Game Battery: Assessing and Identifying Deficits in Memory, Attention, Problem-Solving, and Decision-Making Skills
Češka, Ondřej ; Malik, Aamir Saeed (oponent) ; Hussain, Yasir (vedoucí práce)
The goal of this work is the non-invasive assessment of selected cognitive domains (attention, memory, decision-making) using a new mobile application developed for this purpose. Assessment of cognitive deficits is important for the prevention of neurocognitive disorders. Existing assessment tasks were analyzed and based on them a cognitive game battery consisting of 3 mobile games was successfully designed and implemented. The application is made for the Android platform and was developed in the Unity engine. A system for collecting and storing game data and their subsequent evaluation with the help of cloud availability was created and evaluated using data collection and findings of existing studies. The presented application brings a different perspective to the assessment of cognitive deficits, compares the user's achieved score with other players, and provides them with detailed feedback.
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Game Development for Assessment of a Person’s Reasoning, Auditory & Visual skills
Pejchar, Štěpán ; Hussain, Yasir (oponent) ; Malik, Aamir Saeed (vedoucí práce)
The goal of the thesis is to implement games that assess cognitive functions of the users playing them, specifically audio-visual cognitive functions and reasoning cognitive functions. The nature of the thesis is a pilot study of a bigger project. The first part of the thesis is the theoretical research. It explains what these cognitive functions are, how they work, and how we can assess them. The second part of the thesis talks about the actual game. It explains the game design and the implementation. The game was implemented in Unity using C\# and a Firebase database. This part also talks about how the game assesses and presents the assessment of the cognitive functions to the users. The last part of the thesis deals with the testing of the game. The game was tested on fifteen users. Their answers are presented and evaluated in the final part.
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