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| http://dx.doi.org/10.1007/s41347-020-00184-1 | DOI Listing |
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Reconsidering learnable fine-grained text prompts for few-shot anomaly detection in visual-language models.
Neural Netw
February 2025
Key Laboratory of Computing Power Network and Information Security, Ministry of Education, Shandong Computer Science Center (National Supercomputer Center in Jinan), Qilu University of Technology (Shandong Academy of Sciences), Jinan, 250353, China; Shandong Provincial Key Laboratory of Computing Power Internet and Service Computing, Shandong Fundamental Research Center for Computer Science, Jinan, 250014, China. Electronic address:
Few-Shot Anomaly Detection (FSAD) in industrial images aims to identify abnormalities using only a few normal images, which is crucial for industrial scenarios where sample training is limited. The recent advances in large-scale pre-trained visual-language models have brought significant improvements to the FSAD, which typically requires hundreds of text prompts to be manually crafted through prompt engineering. However, manually designed text prompts cannot accurately match the informative features of different categories across diverse images, and the domain gap between train and test datasets can severely impact the generalization capability of text prompts.
View Article and Find Full Text PDFReconsidering the Effectiveness of Fear Appeals: An Experimental Study of Interactive Fear Messaging to Promote Positive Actions on Climate Change.
J Health Commun
June 2024
School of Journalism and Communication, Tsinghua University, Beijing, China.
Masspersonal communication has emerged as a compelling alternative persuasive approach in response to the widespread use of social media. It is crucial to comprehend how observing online interpersonal interactions regarding the fear appeal of climate change can foster pro-environmental behaviors among users. This study examines the effects of vicarious message interactivity in promoting actions against climate change and the underlying mechanisms behind this effect.
View Article and Find Full Text PDFThe fine line between automation and augmentation in website usability evaluation.
Sci Rep
May 2024
Department of Computer Science, University of Bari Aldo Moro, Via E. Orabona 4, 70125, Bari, Italy.
Artificial Intelligence (AI) systems are becoming widespread in all aspects of society, bringing benefits to the whole economy. There is a growing understanding of the potential benefits and risks of this type of technology. While the benefits are more efficient decision processes and industrial productivity, the risks may include a potential progressive disengagement of human beings in crucial aspects of decision-making.
View Article and Find Full Text PDF'My doctor self and my human self': A qualitative study of physicians' presentation of self on social media.
Med Educ
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Department of Emergency Medicine, University of Michigan, Ann Arbor, Michigan, USA.
Introduction: When using social media, physicians are encouraged and trained to maintain separate professional and personal identities. However, this separation is difficult and even undesirable, as the blurring of personal and professional online presence can influence patient trust. Thus, it is necessary to develop policies and educational resources that are more responsive to the blurring of personal and professional boundaries on social media.
View Article and Find Full Text PDFMethodological Frameworks and Dimensions to Be Considered in Digital Health Technology Assessment: Scoping Review and Thematic Analysis.
J Med Internet Res
April 2024
Agency for Health Quality and Assessment of Catalonia, Barcelona, Spain.
Background: Digital health technologies (dHTs) offer a unique opportunity to address some of the major challenges facing health care systems worldwide. However, the implementation of dHTs raises some concerns, such as the limited understanding of their real impact on health systems and people's well-being or the potential risks derived from their use. In this context, health technology assessment (HTA) is 1 of the main tools that health systems can use to appraise evidence and determine the value of a given dHT.
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