Neural Radiance Fields: Past, Present, and Future

The various aspects like modeling and interpreting 3D environments and surroundings have enticed humans to progress their research in 3D Computer Vision, Computer Graphics, and Machine Learning. An attempt made by Mildenhall et al in their paper about NeRFs (Neural Radiance Fields) led to a boom in Computer Graphics, Robotics, Computer Vision, and the possible scope of High-Resolution Low Storage Augmented Reality and Virtual Reality-based 3D models have gained traction from res with more than 1000 preprints related to NeRFs published. This paper serves as a bridge for people starting to study these fields by building on the basics of Mathematics, Geometry, Computer Vision, and Computer Graphics to the difficulties encountered in Implicit Representations at the intersection of all these disciplines. This survey provides the history of rendering, Implicit Learning, and NeRFs, the progression of research on NeRFs, and the potential applications and implications of NeRFs in today's world. In doing so, this survey categorizes all the NeRF-related research in terms of the datasets used, objective functions, applications solved, and evaluation criteria for these applications.Comment: 413 pages, 9 figures, 277 citation

The social role of AI advisers

Artificial Intelligence (AI) profoundly affects how people communicate, work, and perceive the world. While autonomous AI systems are the focal point in societal and academic discussions, advisory AI systems, which influence human decisions but don't undertake independent actions, often remain unexplored. Examples range from automated purchase recommendations to medical diagnoses. This dissertation seeks to understand what advisory AI systems truly are. Are they capable of autonomous, human-like action? Or can they be reduced to inert tools? And what happens when advisory AI systems are closely linked with human perception, especially through Augmented Reality and sensory augmentation? Does their ontological status change? This dissertation concludes that, regardless of their implementation, advisory AI systems occupy an ontological status between tools and humans. They are more than just tools but less than humans.Künstliche Intelligenz (KI) beeinflusst massiv, wie Menschen kommunizieren, arbeiten und die Welt wahrnehmen. Während autonome KI-Systeme gesellschaftlich und akademisch im Fokus stehen, bleiben beratende KI-Systeme, die menschliche Entscheidungen beeinflussen, aber keine eigenständige Handlung übernehmen, oft unerforscht. Beispiele reichen von automatisierten Kaufempfehlungen bis hin zu medizinischen Diagnosen. Die vorliegende Dissertation untersucht, was beratenden KI-Systeme wirklich sind. Sind sie zu eigenständiger, menschenähnlicher Handlung fähig? Oder lassen sie sich auf handlungsunfähige Werkzeuge reduzieren? Und was passiert, wenn beratende KI Systeme eng mit der menschlichen Wahrnehmung gekoppelt werden, insbesondere durch Augmented Reality und sensorische Augmentation? Verändert sich ihr ontologischer Status? Die vorliegende Dissertation schlussfolgert, dass unabhängig von Ihrer Implementation beratende KI-Systeme einen ontologischen Status zwischen Werkzeugen und Menschen einnehmen. Sie sind also mehr als nur Werkzeuge, aber weniger als Menschen. Louis Longin ist wissenschaftlicher Mitarbeiter am Lehrstuhl für Philosophie des Geistes an der Ludwig-Maximilians-Universität München, wo er 2023 mit der vorliegenden Dissertation promoviert wurde. Seinem Interesse gilt der wachsende Einfluss der Künstlichen Intelligenz auf den menschlichen Nutzer, besonders in den Bereichen der sozialen Interaktion, Ethik und sensorischen Augmentation

Response surface methods applied to submarine concept exploration

CIVINS (Civilian Institutions) Thesis documentIt is estimated that 70 to 85 percent of a naval ship's life-cycle cost is determined during the concept exploration phase which places an importance in the methodology used by the designer to select the concept design. But trade-off studies are guided primarily by past experience, rules-of-thumb, and designer preference. This approach is ad hoc, not efficient and may not lead to an optimum concept design. Even worse, once the designer has a 'good' concept design, he has no process or methodology to determine whether a better concept design is possible or not. A methodology is required to search the design space for an optimal solution based on the specified preferences from the customer. But the difficulty is the design space, which is non-linear, discontinuous, and bounded by a variety of constraints, goals, and thresholds. Then the design process itself is difficult to optimize because of the coupling among decomposed engineering disciplines and sub-system interactions. These attributes prevent application of mature optimization techniques including Lagrange multipliers, steepest ascent methods, linear programming, non-linear programming, and dynamic programming. To further improve submarine concept exploration, this thesis examines a statistical technique called Response Surface Methods (RSM). The purpose of RSM is to lead to an understanding of the relationship between the input (factors) and Output (response) variables, often to further the optimization of the underlying process. The RSM approach allows the designers to find a local optimal and examine how the design factors affect the response in the region around the generated optimal point.http://archive.org/details/responsesurfacem1094510921CIVIN

Aerospace medicine and biology: A continuing bibliography with indexes (supplement 375)

This bibliography lists 212 reports, articles, and other documents recently introduced into the NASA Scientific and Technical Information System database. Subject coverage includes the following: aerospace medicine and physiology, life support systems and man/system technology, protective clothing, exobiology and extraterrestrial life, planetary biology, and flight crew behavior and performance

The use of Eye Tracking Technology in Maritime High-Speed Craft Navigation

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