Face alignment methods have been actively studied using coordinate and heatmap regression tasks. Although these regression tasks have the same objective for facial landmark detection, each task requires different valid feature maps. Therefore, it is...
Underwater image degradation and occlusion make diver keypoints less visually discernible, leading to substantial localization errors in the keypoint pseudo-labels generated by existing semi-supervised methods. These errors can then accumulate and pr...
This work addresses computational inefficiency in ultra-wide-area remote sensing image (RSI) object detection. Traditional homogeneous tiling strategies enforce computational symmetry by processing all image regions uniformly, ignoring the intrinsic...
Visual navigation, characterized by its autonomous capabilities, cost effectiveness, and robust resistance to interference, serves as the foundation for vision-based autonomous landing systems. These systems rely heavily on runway instance segmentati...
Reliable estimation of humanoid robot body configuration from monocular RGB frames is useful for external monitoring in traffic, logistics, and service-robotics environments. However, direct transfer of human pose models is challenged by differences...
This paper proposes a model-less feedback system driven by tourist tracking data that are automatically collected through mobile applications to visualize the gap between geomedia recommendations and the actual routes selected by tourists. High-frequ...
The decarbonization of the electricity system coupled with the electrification of transport, heat, and industry represents a practical and cost-effective approach to deep decarbonization. A key question is as follows: where to build new solar and win...
Introduction The diagnosis of glomerular diseases is primarily based on visual assessment of histologic patterns. Semi-quantitative scoring of active and chronic lesions is often required to assess individual characteristics of the disease. Reproduci...
Face super-resolution (FSR) has made great progress thanks to deep learning and facial priors. However, many existing methods do not fully exploit landmark heatmaps and lack effective multi-scale texture modeling, which often leads to texture loss an...
We develop Categorical Exploratory Data Analysis (CEDA) with mimicking to explore and exhibit the complexity of information content that is contained within any data matrix: categorical, discrete, or continuous. Such complexity is shown through visib...
The identification method of rice seedling rows based on machine vision is affected by environmental factors that decrease the accuracy and the robustness of the rice seedling row identification algorithm (e.g., ambient light transformation, similari...
Detecting small targets in infrared imagery remains highly challenging due to sub-pixel target sizes, low signal-to-noise ratios, and complex background clutter. This paper proposes PSHNet, a hybrid deep-learning framework that combines dense spatial...
Road surface quality is essential for driver comfort and safety, making it crucial to monitor pavement conditions and detect defects in real time. However, the diversity of defects and the complexity of ambient conditions make it challenging to devel...
A panoptic segmentation network to predict masks and classes for things and stuff in images is proposed in this work. Recently, panoptic segmentation has been advanced through the combination of the query-based learning and end-to-end learning approa...
Preoperative prediction of microvascular invasion (MVI) is essential for management decision in hepatocellular carcinoma (HCC). Deep learning-based prediction models of MVI are numerous but lack clinical interpretation due to their “black-box&r...
Melanoma is a highly prevalent and lethal form of skin cancer, which has a significant impact globally. The chances of recovery for melanoma patients substantially improve with early detection. Currently, deep learning (DL) methods are gaining popula...
This study analyses pedestrian behaviour patterns at unsignalized crossings using multiple data-mining approaches, aiming to improve pedestrian safety by understanding the relationship between movement patterns, location, and infrastructure. Utilisin...
High-fidelity simulation testing is a critical component in ensuring the safety and reliability of autonomous driving systems. However, traditional methods for constructing simulation scenarios face two major bottlenecks. First, acquiring realistic r...
Measured radar point-target detection under ground clutter is difficult because weak target echoes often compete with clutter peaks, and image-space detections do not directly represent physical range-Doppler coordinates. This paper proposes a wavefo...
In image classification of tomato leaf diseases based on deep learning, models often focus on features such as edges, stems, backgrounds, and shadows of the experimental samples, while ignoring the features of the disease area, resulting in weak gene...
MASLD (Metabolic Dysfunction-Associated Steatotic Liver Disease) is a growing global concern. Nutraceuticals offer an appealing approach by targeting key mechanisms, such as oxidative stress, inflammation, lipid metabolism, and insulin resistance. Th...
This paper examines the transformative potential of generative artificial intelligence (AI) and neuroaesthetic methodologies in archaeology, museum collections and art history. It introduces the concept of the AI multiverse, which allows archaeologis...
This study aimed to provide an overview of eco-innovations in the Brazilian industry. To address this issue, we analyzed specific data of eco-innovative companies. In addition, we applied the cluster heatmap technique, which allowed us to analyze the...
Small objects in underwater and traffic-sign images often have weak boundaries and low contrast. Downsampling and multi-scale fusion can further weaken the features needed to detect them. We propose ContextFlow-YOLO, a YOLOv8n-based detector designed...
The integration of Bitcoin into corporate treasuries constitutes a critical strategic choice, motivated by its capacity to bolster liquidity and serve as an inflation hedge, while simultaneously being encumbered by pronounced financial volatility and...
Background/Objectives: Spatial neglect after stroke may be difficult to characterize in patients with severe motor, cognitive, and communication impairment. Augmentative and alternative communication interfaces require visual scanning and intentional...
The engineering design of complex systems increasingly relies on model-based methods that generate large-scale models with a vast multitude of couplings between the functional requirements and design parameters. The so-called Axiomatic Design Approac...
31 October 2026
Biological vision integrates cues according to their reliability and context and uses coarse contextual information to form initial hypotheses before directing attention to local evidence. Inspired by these principles, we propose ADCCR (Adaptive Desc...
A targeted and timely treatment can be a beneficial tool for patients with hematological emergencies (particularly acute leukemias). The key challenges in the early diagnosis of leukemias and related hematological disorders are their symptom-sharing...
This study introduces the Normalized Difference Gamma Ray Index (NDGRI), a novel spectral composite derived from Sentinel 2 imagery for mapping elevated natural gamma radiation in semi-arid and arid basins. We hypothesized that water-sensitive spectr...
This study applies reinforcement learning to search parameter regimes that yield chaotic dynamics across six systems: the Logistic map, the Hénon map, the Lorenz system, Chua’s circuit, the Lorenz–Haken model, and a custom 5D hyper...
Cross-view image matching between UAV and satellite platforms is critical for geographic localization but remains challenging due to domain gaps caused by disparities in imaging sensors, viewpoints, and illumination conditions. To address these chall...
Cooperative path planning in complex coastal mountainous environments near the shore is a knowledge-intensive engineering task crucial for demanding multi-UAV operations such as disaster rescue, environmental monitoring, and coastal emergency respons...
Segmentation neural networks are widely used in medical imaging to identify anomalies that may impact patient health. Despite their effectiveness, these networks face significant challenges, including the need for extensive annotated patient data, ti...
Background/Objectives: Brain tumors arise from abnormal, uncontrolled cell growth due to changes in the DNA. Magnetic Resonance Imaging (MRI) is vital for early diagnosis and treatment planning. Artificial intelligence (AI), especially deep learning,...
Object detection in Wide Area Motion Imagery (WAMI) is crucial for large-scale intelligent surveillance and monitoring systems. However, detecting extremely small moving targets in low-frame-rate grayscale WAMI remains highly challenging. In particul...
Remote sensing referring image segmentation faces critical challenges including arbitrary target rotation, drastic scale variation, cluttered complex backgrounds, and large visual-language semantic gaps. Existing mainstream segmentation models adopt...
In millimeter-wave frequency-modulated continuous-wave (FMCW) multiple-input multiple-output synthetic-aperture radar (MIMO-SAR) imaging, platform displacement beyond the spatial Nyquist limit during a slow-time sampling interval creates aperture gap...
Due to the complexity of airborne remote sensing scenes, strong background and noise interference, positive and negative sample imbalance, and multiple ship scales, ship detection is a critical and challenging task in remote sensing. This work propos...
Understanding and controlling thermal rectification is pivotal for designing phononic devices that guide heat flow in a preferential direction. This study investigates one-dimensional atomic chains with binary mass asymmetry and nonlinear interatomic...
To address insufficient detail representation, inadequate cross-modal fusion, and limited localization accuracy in object detection under low-light and complex background conditions, this study proposes an improved CenterNet-based multimodal object d...
Pedestrian detection in crowds is a challenging problem in computer vision. Existing occlusion-handling methods heavily rely on expensive visible-box annotations to locate visible body parts, posing severe limitations in label acquisition cost and op...
While global nutrient insufficiency remains a critical health challenge, eggs have emerged as a potential solution due to their profile as an accessible and nutrient-dense food source. To quantitatively assess this potential for mitigating nutrient i...
Objective: To use deep learning to predict the probability of triangular fibrocartilage complex (TFCC) injury in patients’ MRI scans. Methods: We retrospectively studied medical records over 11 years and 2 months (1 January 2009–29 Februa...
Background: Intracranial atherosclerotic stenosis (ICAS) is a leading cause of ischemic stroke, particularly in the anterior circulation. Understanding the underlying stroke mechanisms is essential for guiding personalized treatment strategies. This...
This study explores the application of Eye-Tracking technology for the ergonomic evaluation of assistive device usability. Sixty-four participants evaluated six jar-opening devices in a two-phase study. First, the participants’ gaze was recorde...
Accurate and robust brain tumor segmentation remains a critical challenge in medical image analysis due to high inter-patient variability, complex tumor morphology, and modality-specific noise in MRI scans. This study proposes PSO-GA-U-Net, a novel h...
Smart city environmental monitoring depends on sparse air quality sensor networks and analytics services that remain reliable under node additions, outages, and missing streams. We propose an operational deep learning framework for citywide cross-loc...
Although the accurate lithological segmentation of outcrops plays a key role in hydrocarbon exploration, complex field environments and substantial scale variations within outcrops, particularly in extremely thin sand–mudstone interbeds, presen...
Apomixis seems to emerge from the deregulation of preexisting genes involved in sexuality by genetic and/or epigenetic mechanisms. The trait is associated with polyploidy, but diploid individuals of Paspalum rufum can form aposporous embryo sacs and...
of 2