Advances in data generation and acquisition have resulted in a volume of available data of such magnitude that our ability to interpret and extract valuable knowledge from them has been surpassed. Our capacity to analyze data is hampered not only by...
In recent decades, multiple approaches have emerged to assess architectural visual character, including fractal dimension analysis, visual equilibrium calculations, and visual preference surveys. However, the relationships among these methods and the...
Analyzing visual scan paths, the time-ordered sequence of eye fixations and saccades, can help us understand how operators visually search the environment before making a decision. To analyze and compare visual scan paths, prior studies have used met...
Many citizens, researchers, civil organizations, and policymakers strive for equitable housing. Changing demographics, rising housing prices, and material and energy crises all add to the complexity of that quest. Responding to it, even on a project...
Grounded Visual Question Answering systems place heavy reliance on substantial computational power and data resources in pretraining. In response to this challenge, this paper introduces the LCV2 modular approach, which utilizes a frozen large langua...
Neurobehavioral signatures, such as cortical hyperexcitability, thalamo-cortical dysrhythmia, and pulvinar dysfunction, appear to drive the persistent visual misperceptions in Visual Snow Syndrome (VSS). We propose that heightened perceptual uncertai...
Sensor networks generate substantial amounts of frequently updated, highly dynamic data that are transmitted as packets in a data stream. The high frequency and continuous unbound nature of data streams leads to challenges when deriving knowledge fro...
The goal of multimodal named entity recognition (MNER) is to detect entity spans in given image–text pairs and classify them into corresponding entity types. Despite the success of existing works that leverage cross-modal attention mechanisms t...
The collaborative execution of tasks by multiple Unmanned Ground Vehicles (UGVs) has become a development trend in the field of unmanned systems. Existing collaborative Simultaneous Localization and Mapping (SLAM) frameworks mainly employ methods bas...
Understanding urban visual perception is crucial for modeling how individuals cognitively and emotionally interact with the built environment. However, traditional survey-based approaches are limited in scalability and often fail to generalize across...
Multimodal human–AI systems generally consider facial expressions and body motions as separate input streams, leading to disjointed interpretations and diminished emotional coherence. To overcome this issue, we offer the Engagement-Safe Express...
This work proposes a hybrid deep learning-based framework for visual feedback control in an eye-in-hand robotic system. The framework uses an early fusion approach in which real and synthetic images define the training data. The first layer of a ResN...
Assistive robotic arms (ARAs) that provide care to the elderly and people with disabilities, are a significant part of Human-Robot Interaction (HRI). Presently available ARAs provide non-intuitive interfaces such as joysticks for control and thus, la...
Visual odometry (VO) estimation from blurred image is a challenging problem in practical robot applications, and the blurred images will severely reduce the estimation accuracy of the VO. In this paper, we address the problem of visual odometry estim...
Visual encoding models based on deep neural networks (DNN) show good performance in predicting brain activity in low-level visual areas. However, due to the amount of neural data limitation, DNN-based visual encoding models are difficult to fit for h...
Grain warehouses are critical nodes in food storage, circulation, and reserve systems, and their safe operation is relevant to occupational protection, reserve stability, and food-system resilience. However, unsafe warehouse behaviors are still mainl...
Audio–visual speech enhancement aims to recover clean speech by jointly using noisy acoustic signals and synchronized visual cues. Although diffusion-based methods achieve promising restoration performance, their multi-step sampling causes high...
Effective inter-hospital coordination is crucial in improving the stroke treatment process and outcomes. The introduction of endovascular thrombectomy (EVT) further emphasized the importance of coordination. Although previous studies considered vario...
Tracking group membership dynamics over time is a persistent challenge in visual analytics, particularly when dealing with complex, multidimensional datasets. Existing tools often struggle to visualize dynamic group transitions while preserving attri...
Tactile sensors play an important role in robotics manipulation to perform dexterous and complex tasks. This paper presents a novel control framework to perform dexterous manipulation with multi-fingered robotic hands using feedback data from tactile...
Contour detection has been extensively investigated as a fundamental problem in computer vision. In this study, a biologically-inspired candidate weighting framework is proposed for the challenging task of detecting meaningful contours. In contrast t...
This paper introduces a biomimetic framework and novel brain-inspired AI (BIAI) models based on spiking neural networks (SNNs) for emotional state recognition from audio (speech), visual (face), and integrated multimodal audio–visual data. The...
Visual emotion recognition plays a critical role in human–computer interaction and mental health applications. Although existing Vision–Language Models (VLMs) alleviate the limitations of conventional vision models in high-level semantic...
Visual–language tracking often faces challenges like target deformation and confusion caused by similar objects. These issues can disrupt the alignment between visual inputs and their textual descriptions, leading to cross-modal semantic drift...
This study explores how lighting can be employed as a visual language to enhance communication between the space and its users and develop a design framework for educational spaces. A primary school is used as a case study to apply the proposed desig...
To address the inherent scale ambiguity and positioning drift in monocular visual Simultaneous Localization and Mapping (SLAM), this paper proposes a novel localization method that integrates monocular visual SLAM with Ultra-Wideband (UWB) ranging in...
Autonomous docking is a core capability enabling full autonomy of unmanned surface vehicles (USVs), whose practical deployment demands visual pose estimation with high efficiency, temporal stability, and closed-loop control compatibility. This paper...
This study presents a novel deep learning framework for classifying visual images based on brain responses recorded through electroencephalogram (EEG) signals. The primary challenge in EEG-based visual pattern recognition lies in the inherent spatiot...
Visual working memory (VWM) declines with age and has been explained by multiple mechanisms, including reduced precision, capacity limitations, binding deficits, and altered attentional control. However, these accounts are typically framed within a u...
The advancement of the Internet of Things (IoT) has transfigured the overlay of the physical world by superimposing digital information in various sectors, including smart cities, industry, healthcare, etc. Among the various shared information, visua...
Structural Topology Optimisation (STO) plays a critical role in computational engineering, enabling the creation of material-efficient, performance-driven structures. However, dynamic STO workflows, particularly those involving time-varying or seismi...
The increasing trend in the transmission of image-based data across various ecosystems like telemedicine, multimedia communication, Internet of Things (IoT), and cloud storage demands a strong security system that can withstand both classical and eme...
Brain–computer interface (BCI) systems have demonstrated significant potential across medical, educational, and entertainment domains. Recently, visual imagery (VI) has emerged as an alternative to traditional motor imagery (MI) paradigms, offe...
Background: Integrating human neural signals with computational vision systems offers a promising route toward more robust visual recognition, yet supporting mixed-granularity recognition, where both coarse- and fine-grained categories must be distin...
The development of computational artifacts to study cross-modal associations has been a growing research topic, as they allow new degrees of abstraction. In this context, we propose a novel approach to the computational exploration of relationships b...
As a multimodal fusion task, audio-visual segmentation (AVS) aims to locate sounding objects at the pixel level within a given image. This capability holds significant importance and practical value in applications such as intelligent surveillance, m...
Visual pollution (VP) is the deterioration or disruption of natural and man-made landscapes that ruins the aesthetic appeal of an area. It also refers to physical elements that limit the movability of people on public roads, such as excavation barrie...
The rise of advanced deepfake technologies presents new challenges to media authenticity, making it harder to spot manipulated videos through traditional approaches. Current approaches have a quadratic time complexity
Civil structures carry significant service loads over long times but are prone to deterioration due to various natural impacts. Traditionally, these structures are inspected in situ by qualified engineers, a method that is high-cost, risky, time-cons...
Landscape character change in mountain traditional villages is difficult to assess from a single perspective because roof-material replacement, material–color deviation, and visual exposure vary under complex terrain and settlement configuratio...
This study investigates the visual complexity of two opposing historic street façades on Sadrettin Konevi Street in Erzurum using an integrated framework that combines fractal analysis, user perception, expert evaluation, and TOPSIS-based deci...
The post-earthquake damage state of reinforced concrete (RC) double-column piers directly affects bridge traffic capacity and emergency response efficiency. To improve the interpretability of damage assessment, this study proposes a Structural–...
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...
In this paper, we propose a robust and integrated visual odometry framework exploiting the optical flow and feature point method that achieves faster pose estimate and considerable accuracy and robustness during the odometry process. Our method utili...
Early-stage architectural design is still dominated by hand-drawn 2D floor-plan sketches, and converting these sketches into object-based Building Information Modeling (BIM) models remains a manual bottleneck that delays downstream simulation, costin...
In low-light conditions, UAV localization faces substantial challenges due to reduced visibility, elevated noise levels, and diminished contrast. To address these issues, we propose a low-light-optimized visual localization framework that integrates...
As intelligent vehicle technologies evolve, reliable driver monitoring systems have become increasingly critical for ensuring the safety of human drivers and operational reliability. This paper proposes a novel visual computing framework for Driver F...
In GNSS-denied environments, UAV visual positioning faces the critical bottleneck of low matching accuracy between heterogeneous images. To address this, we propose SemGeoFrame, a visual matching framework that leverages surface semantic information...
This paper presents SE2-LET-VINS, an enhanced Visual–Inertial Simultaneous Localization and Mapping (VI-SLAM) system built upon the classic Visual–Inertial Navigation System for Monocular Cameras (VINS-Mono) framework, designed to improve...
Rural digitization in the management of woody crops like olive orchards lags significantly behind the technological benchmarks established in other highly digitized sectors. We propose a modular Digital Twin (DT) framework that implements a multi-sca...
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