Наукові публікації колег з інших університетів

Постійний URI для цього фонду

https://openarchive.nure.ua/handle/document/5953

Перегляд

Перегляд Наукові публікації колег з інших університетів за автором "Abu-Jassar Amer Tahseen"

Зараз показано 1 - 3 з 3
  • Зображення мініатюри
    Публікація
    AI and multimedia: a synergy of color and image innovation
    (ТОВ «Друкарня Мадрид», 2024) Abu-Jassar Amer Tahseen; Al-Jamal Ehab Zuhair
    In the digital age, artificial intelligence (AI) has become a pivotal force in enhancing multimedia technologies. This work explores the dynamic integration of AI with multimedia, focusing on advancements in color and image recognition technologies. Through the lens of recent research , we analyze how AI-driven techniques are revolutionizing the perception and interaction with multimedia content, enabling more intuitive and engaging user experiences.
  • Зображення мініатюри
    Публікація
    Artificial intelligence in multimedia: enhancing creativity and efficiency
    (ТОВ «Друкарня Мадрид», 2024) Abu-Jassar Amer Tahseen; Albattiri Anas; Ameerah Osama
    Artificial Intelligence (AI) has emerged as a transformative force in the field of multimedia, revolutionizing content creation, analysis, and delivery across various industries. Through an analysis of the current state of AI in multimedia and its future prospects, this research paper aims to provide insights into the transformative potential of AI in shaping the future of multimedia content creation and consumption.
  • Зображення мініатюри
    Публікація
    The impact of adaptive streaming algorithms on user experience in multimedia applications
    (ТОВ «Друкарня Мадрид», 2024) Abu-Jassar Amer Tahseen; Khalaf Omar Jamal Aref Hussein
    Adaptive streaming algorithms are studied for multimedia application efficiency and user experience. Adaptive streaming adjusts to network circumstances in real time to increase video quality and eliminate buffering. This research examines how adaptive streaming technologies like DASH and HLS might improve viewers' experiences. Simulated network settings let us analyze bandwidth allotment. These simulations assess responsiveness and experience. We examined starting latency, buffering rate, and video quality in numerous circumstances to evaluate performance. According to this research, adaptive streaming algorithms increase video playback quality on unstable networks, even if t heir efficiency varies under severe conditions. Due to decreased rebuffering and faster network speed adaption, DASH increases QoE.