Search Results (550)

Halophytes such as Salicornia europaea rely on biochemical and structural mechanisms to survive in saline environments. This study aimed to evaluate oxidative stress and structural defense responses in four inland populations—Poland (Inowrocław, Ciechocinek), Germany (Salzgraben-Salzdahlum, Salz), and Soltauquelle (Soltq)—subjected to 0, 200, 400, and 1000 mM NaCl, using non-destructive, image-based approaches. Lipid peroxidation was assessed via malondialdehyde (MDA) detected with Schiff’s reagent, and hydrogen peroxide (H₂O₂) accumulation was visualized with 3,3′-diaminobenzidine (DAB). Roots and shoots were analyzed through colour image analysis and quantified using a computer vision system (CVS). MDA accumulation revealed population-specific differences, with Salz tending to exhibit lower peroxidation, characterized by lower L* ≈ 42–43 and higher b* ≈ 37–18 in shoots at 200–400 mM, which may reflect a potentially more effective salt-management strategy. Although H₂O₂ responses deviated from a direct salinity-dependent trend, particularly in the tolerant Salz and Soltq populations, both approaches effectively tracked population-specific adaptation, with German populations displaying detectable basal H₂O₂ levels, consistent with its multifunctional signalling role in salt management and growth regulation. Structural defences were further explored through histochemical mapping and image analysis of pectin and lignin distribution, which revealed population-specific patterns consistent with cell wall remodelling under stress. Non-destructive, image-based methods proved effective for detecting oxidative and structural responses in halophytes. Such a non-destructive, cost-efficient, and reproducible approach can accelerate the identification of salt-tolerant ecotypes for saline agriculture and reinforce S. europaea as a model species for elucidating salt-tolerance mechanisms. Full article

Surface defect detection serves as one of the crucial auxiliary components in the quality control of varistors, and it faces real challenges such as the scarcity of defect samples, high labelling cost, and insufficient a priori knowledge, which makes unsupervised deep learning-based detection methods attract attention. However, existing unsupervised models have problems such as inaccurate defect localisation and a low recognition rate of subtle defects in the detection results. To solve the above problems, an unsupervised detection method (Var-MNDR) is proposed to reconstruct the normal distribution of surface defects of varistors under mask constraints. Firstly, on the basis of colour space as well as morphology, an image preprocessing method is proposed to extract the main body image of the varistor, and a mask-constrained main body pseudo-anomaly generation strategy is adopted so that the model focuses on the texture distribution of the main body region of the image, reduces the model’s focus on the background region, and improves the defect localisation capability of the model. Secondly, Kolmogorov–Arnold Networks (KANs) are combined with the U-Network (U-Net) to construct a segmentation sub-network, and the Gaussian radial basis function is introduced as the learnable activation function of the KAN to improve the model’s ability to express the image features, so as to realise more accurate defect detection. Finally, by comparing the four unsupervised defect detection methods, the experimental results prove the superiority and generalisation of the proposed method. Full article

Several approaches are currently being used by law enforcement to locate the remains of victims. Yet, traditional methods are invasive and time-consuming. Unmanned Aerial Vehicle (UAV)-based remote sensing has emerged as a potential tool to support the location of human remains and clandestine graves. While offering a non-invasive and low-cost alternative, UAV-based remote sensing needs to be tested and validated for forensic case work. To assess current knowledge, a systematic review of 19 peer-reviewed articles from four databases was conducted, focusing specifically on UAV-based remote sensing for human remains and clandestine grave location. The findings indicate that different sensors (colour, thermal, and multispectral cameras), were tested across a range of burial conditions and models (human and mammalian). While UAVs with imaging sensors can locate graves and decomposition-related anomalies, experimental designs from the reviewed studies lacked robustness in terms of replication and consistency across models. Trends also highlight the potential of automated detection of anomalies over manual inspection, potentially leading to improved predictive modelling. Overall, UAV-based remote sensing shows considerable promise for enhancing the efficiency of human remains and clandestine grave location, but methodological limitations must be addressed to ensure findings are relevant to real-world forensic cases. Full article

Accurate delineation of fields is difficult in fragmented landscapes where single-date images provide no seasonal cues and supervised models require labels. We propose a method that explicitly represents phenology to improve zero-shot delineation. Using 22 cloud-free PlanetScope scenes over a 5 × 5 km area, a single harmonic model is fitted to the NDVI per pixel to obtain the phase, amplitude and mean. These values are then mapped into cylindrical colour spaces (Hue–Saturation–Value, Hue–Whiteness–Blackness, Luminance-Chroma-Hue). The resulting recoloured composites are segmented using the Segment Anything Model (SAM), without fine-tuning. The results are evaluated object-wise, object-wise grouped by area size, and pixel-wise. Pixel-wise evaluation achieved up to F1 = 0.898, and a mean Intersection-over-Union (mIoU) of 0.815, while object-wise performance reached F1 = 0.610. HSV achieved the strongest area match, while HWB produced the fewest fragments. The ordinal time-of-day basis provided better parcel separability than the annual radian adjustment. The main errors were over-segmentation and fragmentation. As the parcel size increased, the IoU increased, but the precision decreased. It is concluded that recolouring using harmonic NDVI time series is a simple, scalable, and interpretable basis for field delineation that can be easily improved. Full article

Introduction: Oral squamous cell carcinoma (OSCC) is one of the most common tumours worldwide. This study investigated the suitability of visible and near-infrared hyperspectral imaging compared to visual assessment and conventional digital image analysis for quantifying immunohistochemical staining on the example of Dickkopf-3 (DKK-3) in OSCC. Materials and methods: A retrospective analysis of TMAs containing DKK-3 stained OSCC of 50 patients was retrieved from the archives at the Institute of Pathology, Medical University of Innsbruck. TMAs were first evaluated visually, followed by digital image analysis using QuPath (version 0.3.2, open-source software). For hyperspectral imaging, six exemplary cases were selected (three cases with strong expression and three cases with weak expression) and evaluated. The collected hyperspectral images were visualised using TIVITA (Tissue Imaging System). The resulting true-colour images and the classified HSI images were then assessed using the QuPath software. The Allred score and the H-score were used for all analyses. Results: 97 tissue cores were used for visual and digital image analysis. No significant difference was found between the evaluations of visual and digital image analysis using the H-score (pWilcoxon = 0.278), and both H-scores correlated significantly with each other (p^Spearman < 0.001). Similar results were also found using the Allred score. The kappa value was 0.67, which represents a “substantial” correlation. Finally, the H-scores and Allred scores were compared for visual, digital, and HSI imaging. No significant differences were found between the three groups concerning the H-score (pWilcoxon > 0.1). Using Cohen’s Kappa, a “fair” to “moderate” correlation was observed between the three evaluations. Conclusion: Visible and near-infrared hyperspectral imaging (VIS-NIR-HSI) is a promising complementary tool for digital pathology workflows. This proof-of-concept study suggests that HSI offers the potential for more objective quantification of DKK-3 expression in oropharyngeal squamous cell carcinoma, particularly in cases with weak staining. However, given the small sample size and exploratory design, the findings should be regarded as hypothesis-generating. Future studies with larger, clinically annotated cohorts and standardised workflows are needed before any consideration of routine clinical application. Full article

In the face of the challenge of urban water resource degradation, green infrastructure construction has become a core strategy in modern urban water resource management. Urban aquatic horticulture (UAH), as an important component of this strategy, possesses the dual value of ecological purification and landscape aesthetics. However, its practical implementation is often constrained by public awareness and acceptance. This study aims to address the mismatch between the dual values of urban aquatic horticulture and public perception, and to develop an optimised plant selection strategy that integrates purification functions with public perception. Based on literature reviews, 18 images of aquatic plant landscapes showcasing different ornamental forms, species richness, and life types were created. A questionnaire survey was conducted on 320 participants to assess their perceptions of landscape aesthetic appeal and visual preferences, and a quantitative relationship model was established using multiple stepwise linear regression analysis. The public’s aesthetic perception of aquatic plant landscapes with different ornamental forms and species richness varies significantly, with flowering plant landscapes more likely to evoke aesthetic perception than non-flowering landscapes. The public’s visual preferences for landscape attributes significantly influence their aesthetic perception of aquatic plant landscapes. A multiple stepwise linear regression equation was established to model the relationship between the aesthetic perception of aquatic plant community landscapes and the public’s visual preferences for landscape attributes. There is no significant association between species richness and perceived landscape aesthetic appeal. The study developed an optimised selection strategy for aquatic plants that integrates purification functions with public perception, providing theoretical basis and practical guidance for the scientific configuration of aquatic horticultural systems in urban green infrastructure. In landscape design, flowering plants with ornamental value should be prioritised, with emphasis on landscape layers, colour, and spatial shaping to enhance public acceptance and promote the sustainable development of urban water resource management. Full article

Urban parks often represent the last viable habitats for wildlife in city centres, functioning as crucial refuges and biodiversity hotspots for a wide array of plant and animal species. This study investigates the issue of light pollution in urban parks in selected Polish cities from the perspective of sustainable urban development and dark-sky friendly ordinances. Field data conducted in 2024 and 2025 include measurements of Upward Light Output Ratio (ULOR), illuminance, luminance, correlated colour temperature (CCT), and spectral characteristics of light sources. In addition, an analysis of changes in the level of light pollution in the studied parks and their surroundings between 2012 and 2025 was performed using data from the VIIRS (Visible Infrared Imaging Radiometer Suite) located on the Suomi NPP satellite. Results highlight the mismatch between sustainable development objectives and the current practice of lighting in most of the analysed parks. The study emphasises the need for better integration of light pollution mitigation in urban spatial policies and provides recommendations for environmentally and socially responsible lighting design in urban parks. Full article

Background: The present study investigated the relation between dental inclination, colorimetric variation, and aesthetic perception according to the modification of incisor inclination. Smile aesthetics, shaped by morphological factors and patient perception, are vital for social attractiveness and treatment success. This study aimed to assess the effect of varying head tilt on the perceived colour of upper central incisors by simulating changes in torque of the tooth, as well as evaluate factors influencing the perception of an aesthetic smile, including morphological characteristics and gingival aesthetic parameters. Methods: The study was comprised of three stages: colour analysis, evaluation of micro- and mini-aesthetic smile features, and an image-based assessment to determine evaluator perceptions and overall smile attractiveness. A sample of 50 students with complete, lesion-free anterior dentition was analysed. To simulate the effect of orthodontic torque changes during colour analysis, subjects tilted their heads downward and upward, representing palatal and buccal crown torque, respectively. Standardized macro-intraoral photographs were captured under controlled lighting conditions using a DSLR camera stabilized on a tripod in the different positions: the neutral head position (p0), 15° upward (p + 15), and 15° downward (p − 15). Digital colour analysis was conducted in the CIELAB colour space (L*, a*, b*). In the next stage, focusing on micro- and mini-aesthetic evaluation, an additional 50 smiles were generated using artificial intelligence via the SmileCloud program—one digitally enhanced smile per subject—complementing the initial set of 50 spontaneous smiles. These 100 smile images were evaluated by 50 laypersons and 50 dentists using a visual analogue scale via an online questionnaire, in order to assess perceptions, determine smile attractiveness, and quantify gingival aesthetic parameters. Results: The statistically significant regression results are as follows: those for the L* values in all three head inclinations: downward (−15 degrees), upward (+15 degrees), and total tilting (−15 to +15 degrees), as well as for the a* values for downward tilting and the b* values for total tilting. When the head is tilted downwards, the central incisors are positioned retrusively, and the L* b* values reveal a darker and more yellowish appearance, whereas, with the head tilted upwards, the central incisors protrude, and L* a* values indicate a brighter and more greenish appear. In the evaluation stage of the smile aesthetics study, no significant differences were observed in the judgments between laypersons and dentists or between males and females. Smiles with a high or average anterior line, parallel arc, upward lip curvature, visible first/second premolars, a smile index of 5.08–5.87, and symmetry score of 1.04 were rated as more attractive. Significant asymmetries were observed between upper dental hemi-quadrants in gingival contour and interdental papilla height, highlighting subtle morphological variations relevant to smile aesthetics. Conclusions: Aesthetic assessment revealed that the findings suggest a measurable impact of head position on dental colour perception and aesthetic evaluation. Evaluator variables including profession and gender exerted negligible effects on aesthetic perception, whereas smile attractiveness features and gingival aesthetic parameters demonstrate significant clinical applicability in patient management. Full article

Background: Ultrasound and colour Doppler are adjuvant techniques widely used in clinical settings in obstetrics, cardiology, and others. Its use in dermatology is more incipient although it presents potential for clinical use namely in dermo-oncology. Objective: This study explores the usefulness of the combination of cutaneous ultrasound with Doppler after digital dermatoscopy in distinguishing between most common benign and malignant skin lesions, focusing on the importance of different vascular patterns. To streamline the diagnostic process, we propose a combined imaging workflow that integrates dermoscopic findings with vascular and structural data obtained via Doppler ultrasound. Methods: In total, 42 benign and malignant skin tumours were analysed in a population of 42 patients using a Fotofinder digital dermatoscopy device and a GE ultrasound machine with a high-frequency probe (20 MHz). Doppler was applied to assess lesion vascularization and identify distinct blood flow patterns. Results: Cutaneous ultrasound revealed that malignant lesions often exhibited intense and disorganized vascularization, while benign lesions displayed more ordered and peripheral blood flow patterns. In all of our cases, ultrasound with Doppler imaging clarified the uncertainties raised by dermatoscopy. Conclusions: The use of Doppler cutaneous ultrasound after digital dermatoscopy proved to be a valuable tool to aid the diagnosis in dermatology, as it improved the differential diagnosis between benign and malignant lesions, contributing to the establishment of the final diagnosis in the studied cases. Full article

The health of crops is a major challenge for productivity growth in agriculture, with plant diseases playing a key role in limiting crop yield. Identifying and understanding these diseases is crucial to preventing their spread. In particular, greenhouse pepper leaves are susceptible to diseases such as mildew, mites, caterpillars, aphids, and blight, which leave distinctive marks that can be used for disease classification. The study proposes a seven-class classifier for the rapid and accurate diagnosis of pepper diseases, with a primary focus on pre-processing techniques to enhance colour differentiation between green and yellow shades, thereby facilitating easier classification among the classes. A novel algorithm is introduced to improve image vibrancy, contrast, and colour properties. The diagnosis is performed using a modified VGG16Net model, which includes three additional layers for fine-tuning. After initialising on the ImageNet dataset, some layers are frozen to prevent redundant learning. The classification is additionally accelerated by introducing flattened, dense, and dropout layers. The proposed model is tested on a private dataset collected specifically for this study. Notably, this work is the first to focus on diagnosing aphid and caterpillar diseases in peppers. The model achieves an average accuracy of 92.00%, showing promising potential for seven-class deep learning-based disease diagnostics. Misclassifications in the aphid class are primarily due to the limited number of samples available. Full article

The rapid development of generative artificial intelligence has paved the way for a new approach to reproduce and intelligently generate traditional patterns digitally. This paper focuses on the traditional Chinese phoenix pattern and constructs a “Phoenix Pattern Multidimensional Cultural Gene Model” based on the grounded theory. It summarises seven semantic dimensions covering composition pattern, pixel configuration, colour system, media technology, semantic implication, theme context, and application scenario and divides them into explicit and implicit cultural genes. The study further proposes a control mechanism of “semantic label–prompt–image generation”, constructs a cross-platform prompt structure system suitable for Midjourney and Dreamina AI, and completes 28 groups of prompt combinations and six rounds of iterative experiments. The analysis of the results from 64 user questionnaires and 10 expert ratings reveals that Dreamina AI excels in cultural semantic restoration and context recognition. In contrast, Midjourney has an advantage in composition coordination and aesthetic consistency. Overall, the study verified the effectiveness of the cultural gene model in generating AIGC control. It proposed a framework for generating innovative traditional patterns, providing a theoretical basis and practical support for the intelligent expression of cultural heritage. Full article

The advancement of artificial intelligence (AI) in remote sensing (RS) increasingly depends on datasets that offer rich and structured supervision beyond traditional scene-level labels. Although existing benchmarks for aerial scene classification have facilitated progress in this area, their reliance on single-class annotations restricts their application to more flexible, interpretable and generalisable learning frameworks. In this study, we introduce WHU-RS19 ABZSL: an attribute-based extension of the widely adopted WHU-RS19 dataset. This new version comprises 1005 high-resolution aerial images across 19 scene categories, each annotated with a vector of 38 features. These cover objects (e.g., roads and trees), geometric patterns (e.g., lines and curves) and dominant colours (e.g., green and blue), and are defined through expert-guided annotation protocols. To demonstrate the value of the dataset, we conduct baseline experiments using deep learning models that had been adapted for multi-label classification—ResNet18, VGG16, InceptionV3, EfficientNet and ViT-B/16—designed to capture the semantic complexity characteristic of real-world aerial scenes. The results, which are measured in terms of macro F1-score, range from 0.7385 for ResNet18 to 0.7608 for EfficientNet-B0. In particular, EfficientNet-B0 and ViT-B/16 are the top performers in terms of the overall macro F1-score and consistency across attributes, while all models show a consistent decline in performance for infrequent or visually ambiguous categories. This confirms that it is feasible to accurately predict semantic attributes in complex scenes. By enriching a standard benchmark with detailed, image-level semantic supervision, WHU-RS19 ABZSL supports a variety of downstream applications, including multi-label classification, explainable AI, semantic retrieval, and attribute-based ZSL. It thus provides a reusable, compact resource for advancing the semantic understanding of remote sensing and multimodal AI. Full article

The challenge of accurately representing diverse visual experiences from the real world through image rendering, especially in High Dynamic Range (HDR) imaging, persists due to limitations in conveying luminosity and colour depth on standard displays. In this study, we explore luminosity and Wide Colour Gamut (WCG) in HDR and investigate prevalent HDR/WCG frameworks like hybrid log-gamma (HLG). The focus lies in overcoming the hurdle of displaying transformed HDR images on Standard Dynamic Range (SDR) screens through HDR tone mapping (TM). Despite numerous TM operators available, the need for a detailed comparative analysis remains the same. This study aims to convert HDR images into HLG-transformed images using ISO 22028-5 and transform these to SDR using various TM methods, followed by encoding them into standard displays. Another objective of the study is to also identify the optimal TM method for preserving image quality and artistic integrity on SDR screens, complemented by evaluating content dependencies and optimizing visualization using gain maps. This paper’s comprehensive evaluation involves subjective experiments to discern the most effective TM methodology, providing insights into the transformative potential of HDR images for broader display compatibility. The results indicate that content-aware TM methods combined with gain map optimization provide superior visual fidelity and are recommended for high-quality HDR-to-SDR rendering. Full article

The ability of a virus to be propagated within a host cell is dependent on a multitude of dynamic virus–host interactions. Live-cell imaging is an invaluable approach in the study of virus replication cycles and virus–host interactions as it can allow for the direct visualisation of key events and interactions in real time. These details can provide unique insights into many aspects of viral infections including the cellular pathways that are exploited by viruses, the evasion of host immune defences, and viral pathogenesis. This review summarises the live-cell fluorescence imaging approaches that have been developed and applied to study Flaviviridae virus family members that are responsible for significant public health burdens and outbreaks which, in many instances, are increasing in frequency and severity. We discuss how these approaches have expanded our understanding of fundamental stages of viral replication cycles by enabling the direct visualisation of the localisation, trafficking, and interactions of virus particles, proteins, and genomes at distinct stages. The strategies that can be employed to enhance the biological relevance of live-cell fluorescence imaging acquisitions are discussed, along with how live-cell imaging approaches can be further developed to increase resolution, enable multi-colour imaging, and support the long-term visualisation of multiple stages of a viral replication cycle. Full article

The image analysis of plants provides an opportunity to measure changes in growth and physiology quantitatively, and non-destructively, over time providing significant advantages over traditional methods of assessment which often rely on qualitative and subjective measures to distinguish between different treatments or genotypes in an experiment. Image analysis techniques are commonly deployed for the analysis of plants in the field or glasshouse, but few studies have demonstrated the use of image analysis to phenotype plants grown under aseptic conditions in culture media. Lolium × hybridum Hausskn ‘Shogun’ plants were germinated in vitro and cultured on media containing combinations of thidiazuron [1-phenyl-3-(1,2,3-thiadiazol-5-yl) urea] (TDZ), N6-benzylaminopurine (BA) and gibberellic acid (GA3) or on phytohormone-free control media. RGB images were taken of the plants throughout the experiment and morphological image analysis techniques were used to quantify changes in plant development. A novel approach to quantitatively measure ’greenness‘ in plants using the CIELAB colour model (L*a*b) colour space from RGB images was developed. This methodology could be utilised to develop improved in vitro growth protocols for Lolium and grass species with similar morphology. Full article