Text visualization is a rapidly growing sub-field of information visualization and visual analytics. There are many approaches and techniques introduced every year to address a wide range of challenges and analysis tasks, enabling researchers from di...
The increasing specialization of science is motivating the fragmentation of traditional and well-established research areas into interdisciplinary communities of practice that focus on cooperation between experts to solve problems in a wide range of...
Many parts of big data, such as web documents, online posts, papers, patents, and articles, are in text form. So, the analysis of text data in the big data domain is an important task. Many methods based on statistics or machine learning algorithms h...
Background and Objectives. Anxiety and depressive disorders are the most prevalent mental disorders, and due to the COVID-19 pandemic, more people are suffering from anxiety and depressive disorders, and a considerable fraction of COVID-19 survivors...
Nowadays, lots of applications and websites utilize text-based captchas to partially protect the authentication mechanism. However, in recent years, different ways have been exploited to automatically recognize text-based captchas especially deep lea...
This study investigates the effects of ambient illumination and negatively polarized text color on visual fatigue, exploring the issue of visual fatigue when using visual display terminals in low-illumination environments. The research methodology ut...
Curved, blurred, low-contrast, and cluttered scene text remains difficult to localize and transcribe because visual boundaries and character identities are often ambiguous. Most detectors refine spatial regions from visual and positional features, wh...
Text recognition in natural scene images has always been a hot topic in the field of document-image related visual sensors. The previous literature mostly solved the problem of horizontal text recognition, but the text in the natural scene is usually...
Visual grounding for remote sensing (RSVG) focuses on localizing specific objects in remote sensing (RS) imagery based on linguistic expressions. Existing methods typically employ pre-trained models to locate the referenced objects. However, due to t...
For decades, co-relating different data domains to attain the maximum potential of machines has driven research, especially in neural networks. Similarly, text and visual data (images and videos) are two distinct data domains with extensive research...
The core challenge in video-text retrieval lies in measuring the cross-modal gap between visual and linguistic representations. While mainstream methods leverage deep learning to project video and text features into a shared space for similarity matc...
The visual exploration of large and complex network structures remains a challenge for many application fields. Moreover, a growing number of real-world networks is multivariate and often interconnected with each other. Entities in a network may have...
This paper investigates recent research on active learning for (geo) text and image classification, with an emphasis on methods that combine visual analytics and/or deep learning. Deep learning has attracted substantial attention across many domains...
Every minute, vast amounts of video and image data are uploaded worldwide to the internet and social media platforms, creating a rich visual archive of human experiences—from weddings and family gatherings to significant historical events such...
Visually deceptive text, such as homoglyph-based and near-duplicate variations, poses a significant challenge in applications ranging from financial systems to online identity verification. Existing approaches rely on either string-based similarity m...
Exhibit texts are commonly presented as labels or information panels near artworks to provide visitors with direct access to key exhibit information. Digital museums offer flexible and diverse ways to present artworks and communicate their cultural m...
Open-vocabulary semantic segmentation (OVSS) of unmanned aerial vehicle (UAV) imagery aims to recognize arbitrary text-specified categories in aerial scenes, but existing OVSS models often suffer from UAV-domain shifts. To provide a reproducible test...
Previous research has shown the importance of font type, size, and spacing to facilitate text reading in dyslexia. Great heterogeneity in the population of readers with specific learning disorders suggests that personalized parameters should be prefe...
Eye tracking can reveal how visual attention is allocated within complex displays, but gaze allocation does not necessarily predict what is later remembered. This exploratory study examined image and text regions in three commercial poster identities...
In the realm of public safety, the automated identification of potential threats from voluminous surveillance streams is pivotal for developing intelligent security systems. Manual monitoring of such massive video feeds is highly inefficient, prone t...
Relying on user-generated content narrating individual experiences and personalized contextualization of location-specific realities, this study introduced a novel methodological approach and analysis tool that can aid health informatics in understan...
When blind and deaf people are passengers in fully autonomous vehicles, an intuitive and accurate visualization screen should be provided for the deaf, and an audification system with speech-to-text (STT) and text-to-speech (TTS) functions should be...
In this article, we overview the research literature exploring the teaching of evaluative language in written and/or visual texts in the elementary years of schooling. We then review the recently redrafted Australian Curriculum: English to identify t...
Rapid advances in text-to-image (T2I) generative models have significantly enhanced visual content creation. However, evaluating these models remains challenging, particularly when assessing their ability to handle complex textual content. The primar...
Recognizing places of interest (POIs) can be challenging for humans, especially in foreign environments. In this study, we leverage smartphone sensors (i.e., camera, GPS) and deep learning algorithms to propose an intelligent solution to recognize PO...
E-reading devices are becoming more and more common in our daily life, and they are used under a wide range of ambient light levels, from completely dark to extremely bright conditions. In this study, a psychophysical experiment is carried out to inv...
For visually impaired people (VIPs), the ability to convert text to sound can mean a new level of independence or the simple joy of a good book. With significant advances in optical character recognition (OCR) in recent years, a number of reading aid...
Social media datasets have been widely used in disaster assessment and management. When a disaster occurs, many users post messages in a variety of formats, e.g., image and text, on social media platforms. Useful information could be mined from these...
Persistent multimodal conversational memory requires unified access to textual and visual evidence across sessions, yet differences between image content and textual queries make relevant sources harder to locate. We propose DualBridgeMem, a structur...
Historical topic modeling and semantic concepts exploration in a large corpus of unstructured text remains a hard, opened problem. Despite advancements in natural languages processing tools, statistical linguistics models, graph theory and visualizat...
Ugarit is a public web-based tool for manual annotation of parallel texts for generating word-level translation alignment. We aimed to develop a user-friendly interactive interface to visualize aligned texts and collect training data in the form of t...
Linguistic knowledge helps a lot in scene text recognition by providing semantic information to refine the character sequence. The visual model only focuses on the visual texture of characters without actively learning linguistic information, which l...
With continuous development of artificial intelligence, text classification has gradually changed from a knowledge-based method to a method based on statistics and machine learning. Among them, it is a very important and efficient way to classify tex...
Security analysts working in the modern threat landscape face excessive events and alerts, a high volume of false-positive alerts, significant time constraints, innovative adversaries, and a staggering volume of unstructured data. Organizations thus...
This essay takes a practical viewpoint—that of a graphic designer, a creator of visual messages that assembles text and images in a single product—and examines case studies in which the type becomes an image using different methods depending on the c...
Researchers must read and understand a large volume of technical papers, including patent documents, to fully grasp the state-of-the-art technological progress in a given domain. Chemical research is particularly challenging with the fast growth of n...
Assistive technology (AT) is any item, device, software, or product system used to enhance, maintain, or improve the functional abilities of people with disabilities. There are many people with disabilities in the world, including the visually impair...
More than 7000 rare diseases affect over 400 million people, posing significant challenges for medical research and healthcare. The integration of precision medicine with artificial intelligence offers promising solutions. This work introduces a clas...
In 2023, global data revealed that approximately 2.2 billion people are affected by some form of vision impairment. By addressing the specific challenges faced by individuals who are blind and visually impaired, this research paper introduces a novel...
In order to facilitate designers to explore the market demand trend of laptops and to establish a better “network users-market feedback mechanism”, we propose a design and research method of a short text mining tool based on the K-means c...
Recently, cross-border logistics has experienced rapid development. Cross-border logistics courier orders come in various formats, featuring diverse layouts. Additionally, there is no standardized format for the writing of address and other informati...
During the Joseon Dynasty, Korean Buddhism intentionally negotiated its survival and ongoing relevance in response to the predominance of Neo-Confucian state ideology by aligning Buddhist teaching with Confucian ethical ideals, especially filial piet...
Robust autonomous navigation systems rely on mapping, locomotion, path planning, and localization factors. Localization, one of the most essential factors of navigation, is a crucial requirement for a mobile robot because it needs the capability to l...
With the widespread deployment of mobile imaging sensors and smart devices, the risk of image privacy leakage is increasing daily. Protecting sensitive information in captured images has become increasingly critical. Existing image privacy protection...
Text-to-image generative artificial intelligence tools are increasingly used in interior architecture and design education, yet it remains unclear whether biomimicry and sustainability retain their distinct design intentions when visualized through s...
Accurate scene understanding is crucial for the safe and stable operation of underground utility tunnel inspections. Addressing the characteristics of low-light environments, this paper proposes an object recognition method based on low-light enhance...
Typically, textual information is available as unstructured data, which require processing so that data mining algorithms can handle such data; this processing is known as the pre-processing step in the overall text mining process. This paper aims at...
Extreme weather events are expected to increase in frequency and intensity due to global warming. During disaster events, up-to-date relevant information is crucial for early detection and response. Recently, Twitter emerged as a potentially importan...
Vision impairment affects an individual’s quality of life, posing challenges for visually impaired people (VIPs) in various aspects such as object recognition and daily tasks. Previous research has focused on developing visual navigation system...
Automated animal identification is a practical task for reuniting lost pets with their owners, yet current systems often struggle due to limited dataset scale and reliance on unimodal visual cues. This study introduces a multimodal verification frame...
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