Many web-based systems such as online retail, information systems or search engines track the interactions users have with them. Tracked data can comprise high-level information like dwelling time, reviewed items, and...
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ISBN:
(纸本)9798400704666
Many web-based systems such as online retail, information systems or search engines track the interactions users have with them. Tracked data can comprise high-level information like dwelling time, reviewed items, and clicked elements, but also fine-grained information in the form of mouse trajectories and keystrokes. While these data are often fed into user- or behavior models in recommender systems, there are few approaches for interactive visualexploration of multi-modal and complex interaction patterns. Yet, the thorough analysis could reveal important insights for the design and evaluation of said models. We propose a suitable visualanalysis approach that allows to validate and correct models in an intuitive and interactive manner. Our tool provides insights into concrete user (inter)actions and also estimates more complex behavioral patterns. Level of detail views in our system outlines the certainty of detected behaviors and serve the explainability. Our approach can help engineers to understand user interactions and improve behavioral models.
visual Instruction Tuning represents a novel learning paradigm involving the fine-tuning of pre-trained language models using task-specific instructions. This paradigm shows promising zero-shot results in various natu...
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ISBN:
(纸本)9798350353006
visual Instruction Tuning represents a novel learning paradigm involving the fine-tuning of pre-trained language models using task-specific instructions. This paradigm shows promising zero-shot results in various natural language processing tasks but is still unexplored in vision emotion understanding. In this work, we focus on enhancing the model's proficiency in understanding and adhering to instructions related to emotional contexts. Initially, we identify key visual clues critical to visual emotion recognition. Subsequently, we introduce a novel GPT-assisted pipeline for generating emotion visual instruction data, effectively addressing the scarcity of annotated instruction data in this domain. Expanding on the groundwork established by InstructBLIP, our proposed EmoVIT architecture incorporates emotion-specific instruction data, leveraging the powerful capabilities of Large Language Models to enhance performance. Through extensive experiments, our model showcases its proficiency in emotion classification, adeptness in affective reasoning, and competence in comprehending humor. The comparative analysis provides a robust benchmark for Emotion visual Instruction Tuning in the era of LLMs, providing valuable insights and opening avenues for future exploration in this domain. Our code is available at https://***/aimmemotion/EmoVIT.
Big dataanalysis and insight extraction are critical in contemporary large-scale criminal investigations. Analyzing large sets of information related to criminal activities can assist in the identification of correla...
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Artificial Intelligence (AI) tools have recently gained widespread interest for image creation, but tool developers have largely focused on technical capabilities or specialized domain uses, rather than visual artists...
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ISBN:
(纸本)9798400718281
Artificial Intelligence (AI) tools have recently gained widespread interest for image creation, but tool developers have largely focused on technical capabilities or specialized domain uses, rather than visual artists as users. We collected survey data from 89 practising visual artists and conducted follow-up interviews with 30 of them, to better understand their diverse needs and values. Through reflexive thematic analysis, we explored visual artists' attitudes towards collaboration in art creation both with human artists and with AI- and other technology-based support systems. Our results suggest that the focus of popular AI tools on high-quality, finished images does not meet the needs of visual artists. Instead, they wanted reference images, ideation support, and variant exploration. We identified similarities and differences between how visual artists view collaboration with other artists or with machine support, enabling designers of new tools to adopt a more user-centered approach.
This study is devoted to the development and application of dataanalysis and visualization software in the process of oil testing, aiming at improving the understanding of underground reservoirs and the accuracy of r...
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The diversity of genome-mapped data and analysis tasks makes it challenging for a single visualization tool to fulfill all visualization needs. To design a visualization tool that supports various genomics workflows o...
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ISBN:
(纸本)9798350325577
The diversity of genome-mapped data and analysis tasks makes it challenging for a single visualization tool to fulfill all visualization needs. To design a visualization tool that supports various genomics workflows of users, it is critical to first gain insights into the diverse workflows and the limitations of existing genomics tools for supporting them. In this paper, we conducted semi-structured interviews (N=9) to understand the role of visualization in genomics dataanalysis workflows. Our main goals were to identify various genomics workflows, from dataanalysis to visualexploration and presentation, and to observe challenges that genomics analysts encounter in these workflows when using existing tools. Through the interviews, we found several unique characteristics of genomics workflows, such as the use of multiple visualization tools and many repetitive tasks, which can significantly affect the overall performance. Based on our findings, we discuss implications for designing effective visualization authoring tools that tightly support genomics workflows, such as supporting automation and reproducibility.
This Paper introduces a novel Enhanced visual Retrieval and analysis for Charging Efficiency (EVRACE) system, which presents a novel two-stage framework for visual retrieval and advanced analytics for massive charging...
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Confidence scores of automatic speech recognition (ASR) outputs are often inadequately communicated, preventing its seamless integration into analytical workflows. In this paper, we introduce Confides, a visual analyt...
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The possibility of measuring temporal change in cognitive workload during tasks is examined using microsaccade (MS) rates and pupillary change. The experimental task was designed as a search for a specific figure, whe...
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ISBN:
(纸本)9798350380170;9798350380163
The possibility of measuring temporal change in cognitive workload during tasks is examined using microsaccade (MS) rates and pupillary change. The experimental task was designed as a search for a specific figure, where the task difficulty and reaction accuracy were controlled during the trials. Individual cognitive workload was measured after the experimental sessions were completed, using ratings for NASA-TLX scale. Since the source may be a common one, changes in latent attention resources required for the task were estimated using a designated state-space model, using the observation data in order to synthesise measurement of MS rates and pupillary change. The predicted levels of attention resources correspond to the activity during the performance of the experimental tasks during the trials, and reflected some of the rating scores for workload scales. Also, the ranges of confidence intervals for attention resources correlate significantly with the ratings for information processing at the stage where visual stimulus is presented during tasks.
One of the main ways to evaluate information is through visual learning, which traditionally combines textual reading with visual aids like graphical representations. However, separating the visual method of learning ...
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