Appearance-based face detection with artificial neural networks

Stathopoulou, Ioanna-Ourania; Tsihrintzis, George A.

doi:10.3233/idt-2011-0100

Cited by 17 publications

(5 citation statements)

References 54 publications

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“…A great portion of more recent research has been devoted to the detection of the emotional state of humans from visual-facial data, i.e., from images or videos of their faces, e.g. [20][21][22]. Some other works have addressed visual-facial emotion detection under special circumstances, such as when the subject suffers from depression [23] or is tired [1] or the detection of mild cognitive impairment [24].…”

Section: Previous Related Workmentioning

confidence: 99%

Visual-GRoup AFFEct Recognition (V-GRAFFER): A Unified Application for Real-Time Group Concentration Estimation in E-Lectures

Triantafyllou

Tsihrintzis

2022

Electronics

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This paper presents the most recent version of V-GRAFFER, a novel system that we have been developing for Visual GRoup AFFEct Recognition research. This version includes new algorithms and features, as well as a new application extension for using and evaluating the new features. Specifically, we present novel methods to collect facial samples from other e-lecture applications. We use screen captures of lectures, which we track and connect with samples during the duration of e-educational events. We also developed and evaluated three new algorithms for drawing conclusions on group concentration states. As V-GRAFFER required such complex functionalities to be combined together, many corresponding microservices have been developed. The current version of V-GRAFFER allows drawing real-time conclusions using the input samples collected from the use of any tutoring system, which in turn leads to real-time feedback and allows adjustment of the course material.

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Section: Previous Related Workmentioning

confidence: 99%

Visual-GRoup AFFEct Recognition (V-GRAFFER): A Unified Application for Real-Time Group Concentration Estimation in E-Lectures

Triantafyllou

Tsihrintzis

2022

Electronics

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“…British science fiction writer and futurist Arthur C. Clarke's immortal statement as found in his 1973 version of Profiles of the Future that "Any sufficiently advanced technology is indistinguishable from magic" is quite applicable in this context. However, the belief in a true divinity should transcend all barriers of paradoxes and many seeming contradictions which are but inevitable results of our limited scope of thinking constrained by the limitations of our four-dimensional space and time (Taghezout & Zaraté, 2011;Stathopoulou & Tsihrintzis, 2011).…”

Section: The Universe Of Salvation Sequencementioning

confidence: 99%

The perils and promises of (post-) human salvation

Patra

2021

lingcure

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The present study seeks to analyse Peter F. Hamilton’s trilogy Salvation Sequence comprising three novels, namely: Salvation (2018), Salvation Lost (2019), and The Saints of Salvation (2020), to see how the theological concepts in a posthuman culture connect to or differ from that of our own, and what they can teach us about our own engagement with religious visions and missions. The study will attempt to bring out how even in a highly advanced and purely technologically driven society, where civilizations will have achieved an incredible command over the very laws of time and space, religious ideas like afterlife, resurrection, and immortality will continue to exert a significant influence in deciding the outcome of events. The study will also attempt to find a common ground between the highest form of ambition that a culture at its pinnacle of techno-scientific achievement might seek to materialize by conquering death and wielding maximum command over virtually every aspect of space-time and their innermost theological and spiritual longing. Also, it will be shown that unless the religious ideals find some ways to connect to the innermost needs and religious instincts of the individual, it can never persuade him/her to partake in the vision.

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“…This is a form of reasoning that deals with uncertain or ambiguous information, where the conclusions or decisions reached may not be completely accurate or certain. AI-based reasoning encompasses various techniques like machine learning [15][16][17][18][19], deep learning [20,21],…”

Section: Introductionmentioning

confidence: 99%

Artificial Intelligence and User Experience in reciprocity: Contributions and state of the art

Virvou¹

2023

IDT

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Among the primary aims of Artificial Intelligence (AI) is the enhancement of User Experience (UX) by providing deep understanding, profound empathy, tailored assistance, useful recommendations, and natural communication with human interactants while they are achieving their goals through computer use. To this end, AI is used in varying techniques to automate sophisticated functions in UX and thereby changing what UX is apprehended by the users. This is achieved through the development of intelligent interactive systems such as virtual assistants, recommender systems, and intelligent tutoring systems. The changes are well received, as technological achievements but create new challenges of trust, explainability and usability to humans, which in turn need to be amended by further advancements of AI in reciprocity. AI can be utilised to enhance the UX of a system while the quality of the UX can influence the effectiveness of AI. The state of the art in AI for UX is constantly evolving, with a growing focus on designing transparent, explainable, and fair AI systems that prioritise user control and autonomy, protect user data privacy and security, and promote diversity and inclusivity in the design process. Staying up to date with the latest advancements and best practices in this field is crucial. This paper conducts a critical analysis of published academic works and research studies related to AI and UX, exploring their interrelationship and the cause-effect cycle between the two. Ultimately, best practices for achieving a successful interrelationship of AI in UX are identified and listed based on established methods or techniques that have been proven to be effective in previous research reviewed.

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Appearance-based face detection with artificial neural networks

Cited by 17 publications

References 54 publications

Visual-GRoup AFFEct Recognition (V-GRAFFER): A Unified Application for Real-Time Group Concentration Estimation in E-Lectures

Visual-GRoup AFFEct Recognition (V-GRAFFER): A Unified Application for Real-Time Group Concentration Estimation in E-Lectures

The perils and promises of (post-) human salvation

Artificial Intelligence and User Experience in reciprocity: Contributions and state of the art

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