الصفحة 2
الصفحة 2
Automotive Lighting and Human Vision
Visual perception is the most important of the human senses. Lack of visual perception is one of the main causes of accidents. The safety of vehicle traffic depends on how well automotive lighting supports the visual perception of the driver. This book explains the fundamentals of visual perception, like e.g. physiology of eye and brain, as well as those of automotive lighting technology, like e.g. design of headlamps and signal lights. It is an interdiciplinary approach to a fastly evolving field of science and technology, answering questions like "How does information enter our brain when driving a car?" and "What are the benefits and dangers of LED signal lighting?"
Artificial intelligence in the design process : The impact on creativity and team collaboration
Discusses how to include artificial intelligence (AI) systems in the early stages of the design process. Today designers need new tools capable of supporting them in dealing with the increasing project's complexity and empowering their performances and capabilities. AI systems appear to be powerful means to enhance designers' creativity. This assumption was tested in a workshop where sixteen participants collaborated with three AI systems throughout the creative phases of research, sketching, and color selection. Results show that designers can access a broader level of variance and inspiration while reducing the risk of fossilization by triggering lateral thinking through AI-generated data. Therefore, AI could significantly impact the creative phases of the design process if applied consciously. Being AI systems intelligent agents, the book treats the Human-AI collaboration as a collaboration between human agents, proposing a set of guidelines helpful to achieving an efficient partnership with the machine.
Applied Parallel Computing ; 6th International Conference, PARA 2002, Espoo, Finland, June 15-18, 2002. Proceeding
These proceedings contain the papers presented at PARA 2002, the Sixth In-ternational Conference on Applied Parallel Computing. PARA 2002 was held inEspoo, Finland, June 15–18, 2002, and hosted by CSC, the Finnish informationtechnology center for science. The general theme of the conference was advancedscientific computing.The conference demonstrated the ability of advanced scientific computing tosolve real-world problems, and highlighted methods, instruments, and trends infuture scientific computing. The conference began with a one-day tutorial sessionon Grid programming.The conference focused on an application-oriented, multi-disciplinary, andmulti-scale approach. A wide variety of scientific computing applications wereintroduced, from semiconductor processing and behavior of the human body tooceanic and atmospheric phenomena.
Ambient intelligence for scientific discovery : Foundations, theories, and systems
Many difficult scientific discovery tasks can only be solved in interactive ways, by combining intelligent computing techniques with intuitive and adaptive user interfaces. It is inevitable to use human intelligence in scientific discovery systems: human eyes can capture complex patterns and relationships, along with detecting the exceptional cases in a data set; the human brain can easily manipulate perceptions to make decisions. Ambient intelligence is about this kind of ubiquitous and autonomous human interaction with information. Scientific discovery is a process of creative perception and communication, dealing with questions like: how do we significantly reduce information while maintaining meaning, or how do we extract patterns from massive data and growing data resources. Originating from the SIGCHI Workshop on Ambient Intelligence for Scientific Discovery, this state-of-the-art survey is organized in three parts: new paradigms in scientific discovery, ambient cognition, and ambient intelligence systems. Many chapters share common features such as interaction, vision, language, and biomedicine.
3D Segmentation for medical images (OsteoVision) = التقطيع ثلاثي الأبعاد للصور الطبية
With the increasing integration of AI across various sectors, artificial intelligence (AI) is already playing a significant role in the healthcare industry, and its use is expected to grow further. AI systems used in image processing and computer vision algorithms have shown a significant ability to perform many operations such as segmentation, classification, and detection. This project presents the application of computer vision algorithms in the field of medical imaging for diagnostic, therapeutic, and interventional purposes. This thesis explores the use of several computer vision algorithms to address different pathologies, specifically brain tumors (glioma) (see Appendix A) and knee osteoarthritis (OA), as well as tracking the progression of knee osteoarthritis using the Kellgren and Lawrence (KL) grading system, a common method for classifying the severity of OA into five grades. To achieve the desired impact, the project employs various techniques, including 3D segmentation for brain tumors, 2D segmentation for knee joints, and multinomial classification for determining the severity of knee OA injuries. The primary aims of the project are to enhance diagnostic accuracy, assist in creating treatment plans, provide an assistive tool for healthcare providers to make more informed decisions, leverage AI's capabilities to detect abnormalities that might escape the human eye, and streamline workflow. To facilitate these goals, the project incorporates a user-friendly UI, a website, and a Flutter-based mobile application, enabling healthcare providers to efficiently integrate these tools into their practice and improve patient care.
