Search results for "näkö"
showing 10 items of 223 documents
Mothers’ self-representations and representations of childhood on social media
2023
Funding Information: This work was supported by Kone Foundation, Academy of Finland (#320370), Strategic Research Council (#327237), Strategic Research Council (#327395), Intimacy in Data-driven Culture (IDA). The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. Publisher Copyright: © 2023, Minna Kallioharju, Terhi-Anna Wilska and Annamari Vänskä. Purpose: The purpose of this paper is to examine mothers’ social media accounts that focus on children’s fashion. The authors probed children’s fashion photo practices as representations of the mothers’ extended self and the kind of childhood representations produce…
Representation of Children’s Views in Finnish Newspaper Media Across Three Decades
2020
As the United Nations Convention on the Rights of the Child (UNCRC) celebrates its thirtieth anniversary, it is relevant to explore how understandings of children’s rights have appeared during these three decades. As a key public actor in society, the media provides an interesting field in which to study the salience of children’s rights in societal and public discussions. Thus, in this article, we examine how children’s views are represented in «Helsingin Sanomat», the main national newspaper of Finland, in 1997, 2007, and 2017. This examination is based on articles 12 and 13 of the UNCRC, where it is stated that children have the right to express themselves in all matters affecting them. …
Negative and Positive Bias for Emotional Faces: Evidence from the Attention and Working Memory Paradigms
2021
Visual attention and visual working memory (VWM) are two major cognitive functions in humans, and they have much in common. A growing body of research has investigated the effect of emotional information on visual attention and VWM. Interestingly, contradictory findings have supported both a negative bias and a positive bias toward emotional faces (e.g., angry faces or happy faces) in the attention and VWM fields. We found that the classical paradigms—that is, the visual search paradigm in attention and the change detection paradigm in VWM—are considerably similar. The settings of these paradigms could therefore be responsible for the contradictory results. In this paper, we compare previou…
Automatic image-based identification and biomass estimation of invertebrates
2020
1. Understanding how biological communities respond to environmental changes is a key challenge in ecology and ecosystem management. The apparent decline of insect populations necessitates more biomonitoring but the time-consuming sorting and expert-based identification of taxa pose strong limitations on how many insect samples can be processed. In turn, this affects the scale of efforts to map and monitor invertebrate diversity altogether. Given recent advances in computer vision, we propose to enhance the standard human expert-based identification approach involving manual sorting and identification with an automatic image-based technology. 2. We describe a robot-enabled image-based ident…
One-Pixel Attack Deceives Computer-Assisted Diagnosis of Cancer
2020
Computer vision and machine learning can be used to automate various tasks in cancer diagnostic and detection. If an attacker can manipulate the automated processing, the results can be devastating and in the worst case lead to wrong diagnosis and treatment. In this research, the goal is to demonstrate the use of one-pixel attacks in a real-life scenario with a real pathology dataset, TUPAC16, which consists of digitized whole-slide images. We attack against the IBM CODAIT's MAX breast cancer detector using adversarial images. These adversarial examples are found using differential evolution to perform the one-pixel modification to the images in the dataset. The results indicate that a mino…
Computer Vision on X-ray Data in Industrial Production and Security Applications: A Comprehensive Survey
2023
X-ray imaging technology has been used for decades in clinical tasks to reveal the internal condition of different organs, and in recent years, it has become more common in other areas such as industry, security, and geography. The recent development of computer vision and machine learning techniques has also made it easier to automatically process X-ray images and several machine learning-based object (anomaly) detection, classification, and segmentation methods have been recently employed in X-ray image analysis. Due to the high potential of deep learning in related image processing applications, it has been used in most of the studies. This survey reviews the recent research on using com…
Scavenging in the realm of senses: smell and vision drive recruitment at carcasses in Neotropical ecosystems
2022
Social information, acquired through the observation of other individuals, is especially relevant among species belonging to the same guild. The unpredictable and ephemeral nature of carrion implies that social mechanisms may be selected among scavenger species to facilitate carcass location and consumption. Here, we apply a survival-modelling strategy to data obtained through the placement and monitoring of carcasses in the field to analyse possible information transmission cascades within a Neotropical scavenger community. Our study highlights how the use of different senses (smell and sight) within this guild facilitates carcass location through the transmission of social information bet…
Interactive decision support and trade-off analysis for sustainable forest landscape planning under deep uncertainty
2022
Sustainable environmental management often involves long-term time horizons and multiple conflicting objectives and, by nature, is affected by different sources of uncertainty. Many sources of uncertainty, such as climate change or government policies, cannot be addressed using probabilistic models, and, therefore, they can be seen to contain deep uncertainty. In this setting, the variety of possible future states is represented as a set of scenarios lacking any information about the likelihood of occurring. Integrating deep uncertainty into multiobjective decision support increases complexity, calling for the elaboration of appropriate methods and tools. This paper proposes a novel intera…