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Automatization of object detection with AI
(Faculty of Engineering and Natural Science, 2024) Ulykbek A.
This study performs a comprehensive analysis of the YOLO (You Only Look Once) object detection method, painstakingly evaluating its performance on a wide range of image formats. The investigation’s main focus is on critical metrics that are carefully examined across set of different images, including processing time, frames per second (FPS), and important metrics related to object detection. By means of this rigorous examination, the research reveals noteworthy variations in the algorithm’s effectiveness, illuminating its intrinsic merits and demerits under various circumstances and situations.These results provide a vital source of information for practitioners and researchers working in the field of real-time object recognition applications. They enable them to make informed decisions and create optimization plans specifically for YOLO-based systems. This study provides stakeholders with the tools and considerations needed to efficiently negotiate the complexity of real-world deployments by providing a detailed understanding of the algorithm’s performance peculiarities, thereby promoting improvements and innovation in the field of computer vision.
Road traffic sign recognition using computer vision
(Faculty of Engineering and Natural Science, 2024) Alsiyeu U.
Road traffic accidents are a major public problem in Kazakhstan, with driver inattention and ignorance of traffic signs among the leading causes. Current driver assistance systems integrated in map apps may be inaccurate and irrelevant, especially in rural areas and on highways. The solution proposed by the research includes a computer vision algorithm for accurate and robust detection and recognition of road traffic signs in real time which will be integrated into a mobile application with a notification system. The algorithm will use deep learning neural networks to detect and recognize traffic signs in real time. The algorithm will be trained on a dataset, which will be collected manually and augmented using machine learning techniques. The proposed system has the potential to improve road safety in Kazakhstan by helping drivers to be more aware of traffic signs and to reduce driver inattention.
“Using 3D modeling to develop the creative abilities of learners”
(Faculty of Engineering and Natural Science, 2024) Shugay T.
This paper examines new possibilities for using 3D modeling technologies and explores the development of spatial thinking, imagination and creativity of learners through 3D modeling. The research material was the work of various authors in the field of creativity and creativity development, as well as materials from researchers in the field of three-dimensional modeling. Their use made it possible to study the ideas and outline the prospects for the development of the creative abilities and interests of students. The experimental group was trained using the free 3D modeling program Blender and further experiments and surveys were conducted. The results and analysis of the experiment provide valuable insights into the effectiveness of 3D modeling in creative abilities among learners.
Enhancing Fake News Classification Through DL Models: Encoder-Decoder Architecture with BLSTM for Improved Accuracy
(Faculty of Engineering and Natural Science, 2024) Sumeyra B.P.
In today’s world, the subject of fake news is crucial. It discusses how social media and traditional media spread false stories or misinformation. This effort aims to use deep learning models to increase the accuracy of fake news classification. We investigate the utilization of bidirectional long short-term memory (BLSTM) networks and attention processes in conjunction with encoder-decoder design to boost accuracy
Development of a mobile application to establish e-communication with parents
(Faculty of Engineering and Natural Science, 2013) Suleyman A.
Coming together is a beginning, staying together is progress and working together is success. Successful teachers communicate with the parents. Collaboration between parents and teacher is absolutely crucial to a student success. Create an open path of communication so parents present a united front, there is a lower chance that your student will fall through the cracks. ; Most parents make great plans for their children making sure they attend a good grammar and high school. They prepare for years for the child’s adulthood by planning for college or special training. No one would for a minute, who loved their child, would neglect seeing the child attend school and getting a good secular education. The purpose in this project is establish easy communication between school and parents using fast and low cost SMS messaging system, because it has a major advantage in communicating with parents. That helps to increase student success with communication between school and parents. This project is an android based application for communicate with parents using SMS (Short Message Service). Capable to send and receive SMS between — school and parents including text- content students’ grade marks, attendance, announcements and congratulations. As fast as phone call but cheaper also it doesn't matter if the parent is busy or not. This application can send grade marks to the parents, also if parents want to know grades marks, application response "info" text from the parents as student's grade marks. Of course this is first step of the communication with parents. If that way fails teacher needs to move communication to next step. As Groves described "If phone calls fail to produce any significant improvement in a student's behavior, you'll want to move on to the next step: scheduling a face-to-face parent conference. Mobile communication, with its quick-messaging capabilities and computerlike information processing, can empower them to work together. Ideally, the physical presence of parents at the school would boost education in many ways, but parents are normally away from schools. Mobile devices, however, have been popular for reducing the distance between people.