Weakly-Supervised Autism Severity Assessment in Long Videos
Abid AliMahmoud AliCamilla BarbiniSéverine DubuissonJean‐Marc OdobezFrançois BrémondSusanne Thümmler
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Autism Spectrum Disorder (ASD) is a diverse collection of neurobiological conditions marked by challenges in social communication and reciprocal interactions, as well as repetitive and stereotypical behaviors. Atypical behavior patterns in a long, untrimmed video can serve as biomarkers for children with ASD. In this paper, we propose a video-based weakly-supervised method that takes spatio-temporal features of long videos to learn typical and atypical behaviors for autism detection. On top of that, we propose a shallow TCN-MLP network, which is designed to further categorize the severity score. We evaluate our method on actual evaluation videos of children with autism collected and annotated (for severity score) by clinical professionals. Experimental results demonstrate the effectiveness of behavioral biomarkers that could help clinicians in autism spectrum analysis.Keywords:
Reciprocal
Starting by ntroducing four common definitions on reciprocal two-ports,this paper provides the essential consideration on the word reciprocal and thus deduces the definition based on the port variables.Then this definition is proved to be equivalent to the definition based on the two-port parameters.The definition of the reciprocal element has then been given.The author also introduces that the reciprocal theorem is actually the simple statement that two-ports constituted by reciprocal elements are reciprocal and points out that it is only the sufficient condition for reciprocal two-ports.The relationship between reciprocal two-ports and passive two-ports has also been discussed.
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We can categorize our environment into different scene categories (e.g., a kitchen or a highway) within a glance. Object information has been suggested to play a crucial role in this process, and some proposals even claim that recognition of a single object can be sufficient to categorize the scene around it. Here, we tested this claim by having participants categorize real-world scene photographs reduced to a single, cut-out object. We show that single objects can indeed be sufficient for correct scene categorization and that scene category information can be extracted within 50 ms of object presentation. Furthermore, we identify the exact properties that make certain objects diagnostic of scene categories using human ratings and statistical measures derived from labelled image databases. Interestingly, fast scene categorization is best explained by human ratings of estimated frequency and specificity of the presented objects for the target scene category and less so by objective database measures. Taken together, our findings support a central role of object information during fast scene categorization, showing that single objects can be indicative of a scene category if they are assumed to frequently and exclusively occur in a certain environment.
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The paper uses as its theoretical framework the Membership Categorization Analysis, a way of understanding how interlocutors interpret and give meaning to reality. The concepts underlying the analysis are members, categories, categorization devices, and categorization methods. The data drawn upon are seven interviews recorded with students from the Faculty of Letters at Transilvania University of Brașov. The paper investigates the values the respondents associate with being a student by resorting to categories, categorization devices (considered as expressing moral principles and attitudes), and categorization methods.
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Reciprocal processes are stochastic processes such that the current state only depends on the nearest past and future. The research on continuous-time reciprocal processes has been comprehensive since the 1970s, while surprisingly discrete-time reciprocal processes (i.e., reciprocal chains) are rarely seen in the literature. What is worse is that in the scant literature where reciprocal chains are mentioned, a misunderstanding on how to formally define reciprocal chains has existed since 2008. This article aims to formally define reciprocal chains and provide foundations for the study of them.
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Categorization is an interactive process between human’s cognitive activity and nature. The result of categorization forms category. During categorization, the co-action of many factors results in cognitive differences for the same category prototype. Using the theories related to category and categorization to analyze the cognitive differences can find out the reasons for the differences, which mainly contain culture, living environment, scientific development, living experience and age.
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Categorization researchers typically present single objects to be categorized. But real-world categorization often involves object recognition within complex scenes. It is unknown how the processes of categorization stand up to visual complexity or why they fail facing it. The authors filled this research gap by blending the categorization and visual-search paradigms into a visual-search and categorization task in which participants searched for members of target categories in complex displays. Participants have enormous difficulty in this task. Despite intensive and ongoing category training, they detect targets at near-chance levels unless displays are extremely simple or target categories extremely focused. These results, discussed from the perspectives of categorization and visual search, might illuminate societally important instances of visual search (e.g., diagnostic medical screening).
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