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Journal articles on the topic 'Multi-Light Image Collections'

Author: Grafiati

Published: 11 March 2023

Last updated: 31 July 2025

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1

Fattal, Raanan, Maneesh Agrawala, and Szymon Rusinkiewicz. "Multiscale shape and detail enhancement from multi-light image collections." ACM Transactions on Graphics 26, no. 3 (2007): 51. http://dx.doi.org/10.1145/1276377.1276441.

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Pintus, Ruggero, Alberto Jaspe Villanueva, Antonio Zorcolo, Markus Hadwiger, and Enrico Gobbetti. "A practical and efficient model for intensity calibration of multi-light image collections." Visual Computer 37, no. 9-11 (2021): 2755–67. http://dx.doi.org/10.1007/s00371-021-02172-9.

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3

Pintus, R., T. G. Dulecha, I. Ciortan, E. Gobbetti, and A. Giachetti. "State‐of‐the‐art in Multi‐Light Image Collections for Surface Visualization and Analysis." Computer Graphics Forum 38, no. 3 (2019): 909–34. http://dx.doi.org/10.1111/cgf.13732.

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Ströbel, Bernhard, Sebastian Schmelzle, Nico Blüthgen, and Michael Heethoff. "An automated device for the digitization and 3D modelling of insects, combining extended-depth-of-field and all-side multi-view imaging." ZooKeys 759 (May 17, 2018): 1–27. http://dx.doi.org/10.3897/zookeys.759.24584.

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Digitization of natural history collections is a major challenge in archiving biodiversity. In recent years, several approaches have emerged, allowing either automated digitization, extended depth of field (EDOF) or multi-view imaging of insects. Here, we present DISC3D: a new digitization device for pinned insects and other small objects that combines all these aspects. A PC and a microcontroller board control the device. It features a sample holder on a motorized two-axis gimbal, allowing the specimens to be imaged from virtually any view. Ambient, mostly reflection-free illumination is asce

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Ströbel, Bernhard, Sebastian Schmelzle, Nico Blüthgen, and Michael Heethoff. "An automated device for the digitization and 3D modelling of insects, combining extended-depth-of-field and all-side multi-view imaging." ZooKeys 759 (May 17, 2018): 1–27. https://doi.org/10.3897/zookeys.759.24584.

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Digitization of natural history collections is a major challenge in archiving biodiversity. In recent years, several approaches have emerged, allowing either automated digitization, extended depth of field (EDOF) or multi-view imaging of insects. Here, we present DISC3D: a new digitization device for pinned insects and other small objects that combines all these aspects. A PC and a microcontroller board control the device. It features a sample holder on a motorized two-axis gimbal, allowing the specimens to be imaged from virtually any view. Ambient, mostly reflection-free illumination is asce

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Bai, Nan, Anran Yang, Hao Chen, and Chun Du. "SatGS: Remote Sensing Novel View Synthesis Using Multi- Temporal Satellite Images with Appearance-Adaptive 3DGS." Remote Sensing 17, no. 9 (2025): 1609. https://doi.org/10.3390/rs17091609.

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Novel view synthesis of remote sensing scenes from satellite images is a meaningful but challenging task. Due to the wide temporal span of image acquisition, satellite image collections often exhibit significant appearance variations, such as seasonal changes and shadow movements, as well as transient objects, making it difficult to reconstruct the original scene accurately. Previous work has noted that a large amount of image variation in satellite images is caused by changing light conditions. To address this, researchers have proposed incorporating the direction of solar rays into neural ra

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Salili-James, Arianna, Ben Scott, Laurence Livermore, et al. "AI-Accelerated Digitisation of Insect Collections: The next generation of Angled Label Image Capture Equipment (ALICE)." Biodiversity Information Science and Standards 7 (September 15, 2023): e112742. https://doi.org/10.3897/biss.7.112742.

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The digitisation of natural science specimens is a shared ambition of many of the largest collections, but the scale of these collections, estimated at at least 1.1 billion specimens (Johnson et al. 2023), continues to challenge even the most resource-rich organisations.The Natural History Museum, London (NHM) has been pioneering work to accelerate the digitisation of its 80 million specimens. Since the inception of the NHM Digital Collection Programme in 2014, more than 5.5 million specimen records have been made digitally accessible. This has enabled the museum to deliver a tenfold increase

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Hereld, Mark, and Nicola Ferrier. "LightningBug ONE: An experiment in high-throughput digitization of pinned insects." Biodiversity Information Science and Standards 3 (June 19, 2019): e37228. https://doi.org/10.3897/biss.3.37228.

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Digital technology presents us with new and compelling opportunities for discovery when focused on the world's natural history collections. The outstanding barrier to applying existing and forthcoming computational methods for large-scale study of this important resource is that it is (largely) not yet in the digital realm. Without development of new and much faster methods for digitizing objects in these collections, it will be a long time before these data are available in digital form. For example, methods that are currently employed for capturing, cataloguing, and indexing pinned insect sp

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Jin, Naiyun, Tingting Hu, Lei Shu, et al. "A Crop Growth Information Collection System Based on a Solar Insecticidal Lamp." Electronics 14, no. 2 (2025): 370. https://doi.org/10.3390/electronics14020370.

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To overcome the challenges during the crop growth process, e.g., pest infestation, inadequate environmental monitoring, and poor intelligence, this study proposes a crop growth information collection system based on a solar insecticidal lamp. The system comprises two primary modules: (1) an environmental information collection module, and (2) a multi-view image collection module. The environmental information collection module acquires crucial parameters, e.g., temperature, relative humidity, light intensity, soil conductivity, nitrogen, phosphorus, potassium content, and pH, by means of vario

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Malinovski, I., I. B. Couceiro, A. D. Alvarenga, et al. "Digital enhancement of OCT images toward better diagnostic of precursor cancer lesions in the uterine colon." Journal of Physics: Conference Series 2606, no. 1 (2023): 012021. http://dx.doi.org/10.1088/1742-6596/2606/1/012021.

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Abstract We present a combination of image processing operations, which improve the quality of OCT images. The sequence is: (1) Gaussian blur, (2) Enhance Local Contrast (CLAHE), (3) FFT based band-pass filter, (4) Background Subtraction, (5) adjustment of the contrast of the image with light saturation (Enhance Contrast) and finally (6) reassignment of the palette such as to enhance the bright part of the images. The multi-step treatment reduces pixel-to-pixel noise, improves the homogeneity of the contrast, supresses vertical strips, reduces cosmetic distractions, equalizes contrast across a

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Touja, Hugo, Frédéric Brau, Thierry Bastien, Brigitte Delhomme, and Martin Oheim. "M-Cube — towards correlative multi-scale light-sheet imaging using a compact, modular and moving illuminator." EPJ Web of Conferences 309 (2024): 04013. http://dx.doi.org/10.1051/epjconf/202430904013.

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The crossed arrangement of excitation and collection optics is the defining feature of selective plane illumination microscopes. It results in an axial sectioning given by the thickness of the light sheet, whereas the lateral resolution depends on the numerical aperture of the collection optics. One disadvantage of this optical scheme is that it has been difficult to image large fields-of-view at high spatial resolution. Yet, it is often not necessary to image the entire sample at high resolution. Instead, a zoom from mm-scale over-views to regions-of-interest that are imaged at μm is often su

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Wu, Siyao, Yanan Lu, Wei Fan, Shengmao Zhang, Zuli Wu, and Fei Wang. "An Efficient Downwelling Light Sensor Data Correction Model for UAV Multi-Spectral Image DOM Generation." Drones 9, no. 7 (2025): 491. https://doi.org/10.3390/drones9070491.

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The downwelling light sensor (DLS) is the industry-standard solution for generating UAV-based digital orthophoto maps (DOMs). Current mainstream DLS correction methods primarily rely on angle compensation. However, due to the temporal mismatch between the DLS sampling intervals and the exposure times of multispectral cameras, as well as external disturbances such as strong wind gusts and abrupt changes in flight attitude, DLS data often become unreliable, particularly at UAV turning points. Building upon traditional angle compensation methods, this study proposes an improved correction approac

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Wan, Zijing. "A multi-dimension information processing method for low-power forest surveillance systems." Journal of Physics: Conference Series 2977, no. 1 (2025): 012115. https://doi.org/10.1088/1742-6596/2977/1/012115.

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Abstract To identify early-stage forest fires using ground-based sensing systems, this paper studies the radiation characteristics of smoke particles and interference particles under natural light in different environments based on a rapid dimensional reduction algorithm of forest monitoring images and a multi-dimensional time series signal graph model. It has completed the forest fire classification and spread prediction method based on multi-sensor and image sequence signal abnormal event detection, which enables the forest fire detection system to achieve comprehensive and efficient collect

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Hussein, Zinah R. "Improvement of noisy images filtered by bilateral process using a multi-scale context aggregation network." Eastern-European Journal of Enterprise Technologies 2, no. 9 (116) (2022): 14–20. http://dx.doi.org/10.15587/1729-4061.2022.255789.

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Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required.

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Zinah, R. Hussein. "Improvement of noisy images filtered by bilateral process using a multi-scale context aggregation network." Eastern-European Journal of Enterprise Technologies 2, no. 9 (116) (2022): 14–20. https://doi.org/10.15587/1729-4061.2022.255789.

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Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required.

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Hashim, Ashwaq T., and Zina A. Saleh. "Fast Iris Localization Based on Image Algebra and Morphological Operations." JOURNAL OF UNIVERSITY OF BABYLON for Pure and Applied Sciences 27, no. 2 (2019): 143–54. http://dx.doi.org/10.29196/jubpas.v27i2.2073.

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The localization of the iris is the most significant factor in biometrics of the iris, which traditionally assumes strictly controlled environments. The proposed method includes the pupillary and limbic iris boundaries localization. A primary advantage of image arithmetic operations is that the process is straightforward and therefore fast, these characteristics are employed and combined with the morphological operators in the designing of the proposed algorithm. The proposed algorithm takes into account the noise area which is found in various parts of the eye image such as light reflections,

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Wang, Jing Yi, Hang Gao, and Chun Lin Shen. "Research on Applied-Information Technology with Data Distribution for Light Field Camera Array." Advanced Materials Research 1046 (October 2014): 436–39. http://dx.doi.org/10.4028/www.scientific.net/amr.1046.436.

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The collection of light field is a key part of 3D image rendering and multi-view display system construction. Data exchange of light field frequently used in light field camera array requires high real-time performance and high bandwidth. This paper presents a new method of light field data exchange by applying data distribution service (DDS). Experiment results show it is feasible to apply data distribution service to the light field camera array.

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18

Guo, Wenping, Yuan Huang, Chunhua Liu, et al. "Upgrade of Thomson Scattering Diagnostic on HL-2A." Instruments 7, no. 1 (2023): 12. http://dx.doi.org/10.3390/instruments7010012.

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The Thomson scattering diagnostic of the HL-2A tokamak device was upgraded to improve its multi-point diagnostic capability, including new collection optics, fibers bundles, and data analysis code. The small old collection lens was replaced by a six-piece lens with a Cooke optical design. The aperture of its first standard sphere face is 310.125 mm, which successfully increases the amount of collected scattering light by about three times. The new collection optic module allows for up to twenty-six spatial points. A kind of Y-type fiber bundle has also been used to ensure that the fiber end-fa

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19

Lai, Wei-Sheng, Yichang Shih, Lun-Cheng Chu, et al. "Face deblurring using dual camera fusion on mobile phones." ACM Transactions on Graphics 41, no. 4 (2022): 1–16. http://dx.doi.org/10.1145/3528223.3530131.

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Motion blur of fast-moving subjects is a longstanding problem in photography and very common on mobile phones due to limited light collection efficiency, particularly in low-light conditions. While we have witnessed great progress in image deblurring in recent years, most methods require significant computational power and have limitations in processing high-resolution photos with severe local motions. To this end, we develop a novel face deblurring system based on the dual camera fusion technique for mobile phones. The system detects subject motion to dynamically enable a reference camera, e.

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20

Choe, Seungho, and Sheela Ramanna. "Cubical Homology-Based Machine Learning: An Application in Image Classification." Axioms 11, no. 3 (2022): 112. http://dx.doi.org/10.3390/axioms11030112.

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Persistent homology is a powerful tool in topological data analysis (TDA) to compute, study, and encode efficiently multi-scale topological features and is being increasingly used in digital image classification. The topological features represent a number of connected components, cycles, and voids that describe the shape of data. Persistent homology extracts the birth and death of these topological features through a filtration process. The lifespan of these features can be represented using persistent diagrams (topological signatures). Cubical homology is a more efficient method for extracti

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21

Smith, S., P. Forscher, M. Cooper, and A. Waxman. "Digital video and laser microscopic studies of developmental events in living neurons and nervous systems." Proceedings, annual meeting, Electron Microscopy Society of America 47 (August 6, 1989): 832. http://dx.doi.org/10.1017/s0424820100156134.

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Motility and structural change are extremely important aspects of nervous system development. We are working to refine digital video and laser confocal light microscopic methods for visualization of neuronal motility both in situ and in vitro. Our efforts are oriented especially toward the collection of digitally-enhanced time-lapse movies, for which purpose we especially favor the use of the optical memory disc video recorder. It is our feeling that such dynamic observations are yielding insights not obtainable from examination of fixed specimens. Work to be discussed includes video microscop

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22

Fan, Jinhao, Lizhi Cui, and Shumin Fei. "Waste Detection System Based on Data Augmentation and YOLO_EC." Sensors 23, no. 7 (2023): 3646. http://dx.doi.org/10.3390/s23073646.

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The problem of waste classification has been a major concern for both the government and society, and whether waste can be effectively classified will affect the sustainable development of human society. To perform fast and efficient detection of waste targets in the sorting process, this paper proposes a data augmentation + YOLO_EC waste detection system. First of all, because of the current shortage of multi-objective waste classification datasets, the heavy workload of human data collection, and the limited improvement of data features by traditional data augmentation methods, DCGAN (deep c

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Etoh, Takeharu, Tomoo Okinaka, Yasuhide Takano, et al. "Light-In-Flight Imaging by a Silicon Image Sensor: Toward the Theoretical Highest Frame Rate." Sensors 19, no. 10 (2019): 2247. http://dx.doi.org/10.3390/s19102247.

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Light in flight was captured by a single shot of a newly developed backside-illuminated multi-collection-gate image sensor at a frame interval of 10 ns without high-speed gating devices such as a streak camera or post data processes. This paper reports the achievement and further evolution of the image sensor toward the theoretical temporal resolution limit of 11.1 ps derived by the authors. The theoretical analysis revealed the conditions to minimize the temporal resolution. Simulations show that the image sensor designed following the specified conditions and fabricated by existing technolog

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Mathys, Aurore, Yann Pollet, Adrien Gressin, et al. "Sphaeroptica: A tool for pseudo-3D visualization and 3D measurements on arthropods." PLOS ONE 19, no. 10 (2024): e0311887. http://dx.doi.org/10.1371/journal.pone.0311887.

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Natural history collections are invaluable reference collections. Digitizing these collections is a transformative process that improves the accessibility, preservation, and exploitation of specimens and associated data in the long term. Arthropods make up the majority of zoological collections. However, arthropods are small, have detailed color textures and share small, complex and shiny structures, which poses a challenge to conventional digitization methods. Sphaeroptica is a multi-images viewer that uses a sphere of oriented images. It allows the visualization of insects including their ti

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Villareal, Marife Kung, and Alejandro Fernandez Tongco. "Multi-sensor Fusion Workflow for Accurate Classification and Mapping of Sugarcane Crops." Engineering, Technology & Applied Science Research 9, no. 3 (2019): 4085–91. https://doi.org/10.5281/zenodo.3249010.

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This study aims to assess the classification accuracy of a novel mapping workflow for sugarcane crops identification that combines light detection and ranging (LiDAR) point clouds and remotely-sensed orthoimages. The combined input data of plant height LiDAR point clouds and multispectral orthoimages were processed using a technique called object-based image analysis (OBIA). The use of multi-source inputs makes the mapping workflow unique and is expected to yield higher accuracy compared to the existing techniques. The multi-source inputs are passed through five phases: data collection, data f

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Sadhasivam, Muniyandi, Manoharan Kalaiselvi Geetha, and James Gladson Maria Britto. "Deep learning based multi disease classification of plant leaves using light weight residual architecture." International Journal of Electrical and Computer Engineering (IJECE) 14, no. 4 (2024): 4646. http://dx.doi.org/10.11591/ijece.v14i4.pp4646-4654.

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Plant diseases can severely impact crop yields, posing a major risk to worldwide food stability. Prompt and precise identification of these diseases is crucial for early intervention and efficient crop administration. This paper introduces an innovative method for detecting plant leaf diseases using residual networks (ResNets) and the PlantVillage dataset. To develop light weight residual (LWR) architecture, five convolutional layers are interleaved with five max-pooling layers, making up the architecture of ten layers. The number of filters in the convolutional layers is gradually increased f

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Arnold, Bradley R., Christopher E. Cooper, Michael R. Matrona, Darren K. Emge, and Jeffrey B. Oleske. "Stand-off deep-UV Raman spectroscopy." Canadian Journal of Chemistry 96, no. 7 (2018): 614–20. http://dx.doi.org/10.1139/cjc-2017-0678.

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UV Raman spectra were measured using a novel experimental configuration. This configuration allows many of the difficulties associated with UV excitation and high-power pulsed laser sources to be mitigated. Large sample areas are imaged into the detection system allowing high power excitation sources to be used while simultaneously avoiding sample degradation and multi-photon absorption effects. Such large detection areas allow large numbers of molecular scatters to be probed even with minimal penetration depth. Alignment issues between sample and collection optics are also simplified. Several

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Sadhasivam, Muniyandi, Geetha Manoharan Kalaiselvi, and Maria Britto James Gladson. "Deep learning based multi disease classification of plant leaves using light weight residual architecture." Deep learning based multi disease classification of plant leaves using light weight residual architecture 14, no. 4 (2024): 4646–54. https://doi.org/10.11591/ijece.v14i4.pp4646-4654.

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Plant diseases can severely impact crop yields, posing a major risk to worldwide food stability. Prompt and precise identification of these diseases is crucial for early intervention and efficient crop administration. This paper introduces an innovative method for detecting plant leaf diseases using residual networks (ResNets) and the PlantVillage dataset. To develop light weight residual (LWR) architecture, five convolutional layers are interleaved with five max-pooling layers, making up the architecture of ten layers. The number of filters in the convolutio

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29

Flaig, Ralf. "Data collection tools for challenging samples at the MX beamlines at Diamond." Acta Crystallographica Section A Foundations and Advances 70, a1 (2014): C329. http://dx.doi.org/10.1107/s2053273314096703.

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Diamond Light Source [1] is the UK third generation synchrotron facility located south of Oxford and it started with the user programme in early 2007. Currently, there are five operational macromolecular crystallography (MX) beamlines that provide state of the art facilities to the user community and eventually there will be seven beamlines dedicated to MX [2]. All MX beamlines provide tools for standard data collection but given the increasing complexity and associated challenges with bigger macromolecular complexes, membrane proteins, smaller crystals, and radiation damage, different approac

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Norton, Cynthia L., Kyle Hartfield, Chandra D. Holifield Collins, Willem J. D. van Leeuwen, and Loretta J. Metz. "Multi-Temporal LiDAR and Hyperspectral Data Fusion for Classification of Semi-Arid Woody Cover Species." Remote Sensing 14, no. 12 (2022): 2896. http://dx.doi.org/10.3390/rs14122896.

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Mapping the spatial distribution of woody vegetation is important for monitoring, managing, and studying woody encroachment in grasslands. However, in semi-arid regions, remotely sensed discrimination of tree species is difficult primarily due to the tree similarities, small and sparse canopy cover, but may also be due to overlapping woody canopies as well as seasonal leaf retention (deciduous versus evergreen) characteristics. Similar studies in different biomes have achieved low accuracies using coarse spatial resolution image data. The objective of this study was to investigate the use of m

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31

Mo, Yiming, Lei Wang, Wenqing Hong, Congzhen Chu, Peigen Li, and Haiting Xia. "Small-Scale Foreign Object Debris Detection Using Deep Learning and Dual Light Modes." Applied Sciences 14, no. 5 (2024): 2162. http://dx.doi.org/10.3390/app14052162.

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The intrusion of foreign objects on airport runways during aircraft takeoff and landing poses a significant safety threat to air transportation. Small-scale Foreign Object Debris (FOD) cannot be ruled out on time by traditional manual inspection, and there is also a potential risk of secondary foreign body intrusion. A deep-learning-based intelligent detection method is proposed to solve the problem of low accuracy and low efficiency of small-scale FOD detection. Firstly, a dual light camera system is utilized for the collection of FOD data. It generates a dual light FOD dataset containing bot

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Guo, Shaolin, Yixuan Wang, Yin Tan, Tonglai Liu, and Qin Qin. "Efficient Coastal Mangrove Species Recognition Using Multi-Scale Features Enhanced by Multi-Head Attention." Symmetry 17, no. 3 (2025): 461. https://doi.org/10.3390/sym17030461.

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Recognizing mangrove species is a challenging task in coastal wetland ecological monitoring due to the complex environment, high species similarity, and the inherent symmetry within the structural features of mangrove species. Many species coexist, exhibiting only subtle differences in leaf shape and color, which increases the risk of misclassification. Additionally, mangroves grow in intertidal environments with varying light conditions and surface reflections, further complicating feature extraction. Small species are particularly hard to distinguish in dense vegetation due to their symmetri

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Cavaleri, Tiziana, Stefano Legnaioli, Francesca Lozar, et al. "A Multi-Analytical Study of an Ancient Egyptian Limestone Stele for Knowledge and Conservation Purposes: Recovering Hieroglyphs and Figurative Details by Image Analysis." Heritage 4, no. 3 (2021): 1193–207. http://dx.doi.org/10.3390/heritage4030066.

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A multi-analytical study was carried out on an ancient Egyptian limestone stele with red figures and hieroglyphs (S. 6145) coming from the village of Deir el-Medina and belonging to the collection of the Museo Egizio (Turin, Italy). With the support of a multidisciplinary team, a project for the preservation and conservation of this stele provided an opportunity to carry out a very detailed study of the object. Petrographic and mineralogical analysis led to the characterization and dating of the limestone, and ultrasonic tests were of great help in shedding light on the state of preservation o

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Villareal, M. K., and A. F. Tongco. "Multi-sensor Fusion Workflow for Accurate Classification and Mapping of Sugarcane Crops." Engineering, Technology & Applied Science Research 9, no. 3 (2019): 4085–91. http://dx.doi.org/10.48084/etasr.2682.

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This study aims to assess the classification accuracy of a novel mapping workflow for sugarcane crops identification that combines light detection and ranging (LiDAR) point clouds and remotely-sensed orthoimages. The combined input data of plant height LiDAR point clouds and multispectral orthoimages were processed using a technique called object-based image analysis (OBIA). The use of multi-source inputs makes the mapping workflow unique and is expected to yield higher accuracy compared to the existing techniques. The multi-source inputs are passed through five phases: data collection, data f

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35

Valdés Sánchez, Amanda. "“A Desora Desperto y vio una Grand Claridat”: The Role of Dreams and Light in the Construction of a Multi-Confessional Audience of the Miracles of the Virgin of Guadalupe." Religions 10, no. 12 (2019): 652. http://dx.doi.org/10.3390/rel10120652.

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This paper examines the religious proselytizing agenda of the order of Saint Jerome that ruled the Extremaduran sanctuary of the Virgin of Guadalupe since 1389. To this end, I analyze how the Hieronymite’s used literary motifs such as dreams and light in the codex of the Miracles of the Virgin of Guadalupe to create a multi-confessional audience for their collection of miracles. I contend that these motifs were chosen because they were key elements in the construction of a particular image of the Virgin that could appeal to pilgrims of different faiths. Through them, the Hieronymites evoked in

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Cao, Yanlong, Xiaoyao Wei, Wenyuan Liu, Binjie Ding, Jiangxin Yang, and Yanpeng Cao. "A Novel Learning Based Non-Lambertian Photometric Stereo Method for Pixel-Level Normal Reconstruction of Polished Surfaces." Machines 10, no. 2 (2022): 120. http://dx.doi.org/10.3390/machines10020120.

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High-quality reconstruction of polished surfaces is a promising yet challenging task in the industrial field. Due to its extreme reflective properties, state-of-the-art methods have not achieved a satisfying trade-off between retaining texture and removing the effects of specular outliers. In this paper, we propose a learning based pixel-level photometric stereo method to estimate the surface normal. A feature fusion convolutional neural network is used to extract the features from the normal map solved by the least square method and from the original images respectively, and combine them to r

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Kakde, Aditya, Nitin Arora, Durgansh Sharma, and Subhash Chander Sharma. "Multi spectral classification and recognition of breast cancer and pneumonia." Polish Journal of Medical Physics and Engineering 26, no. 1 (2020): 1–9. http://dx.doi.org/10.2478/pjmpe-2020-0001.

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AbstractAccording to the Google I/O 2018 key notes, in future artificial intelligence, which also includes machine learning and deep learning, will mostly evolve in healthcare domain. As there are lots of subdomains which come under the category of healthcare domain, the proposed paper concentrates on one such domain, that is breast cancer and pneumonia. Today, just classifying the diseases is not enough. The system should also be able to classify a particular patient’s disease. Thus, this paper shines the light on the importance of multi spectral classification which means the collection of s

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Fisher, Wait G., and Eric A. Wachter. "Improved Signal Processing in Multi-Photon Imaging." Microscopy and Microanalysis 6, S2 (2000): 800–801. http://dx.doi.org/10.1017/s1431927600036497.

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Multi-photon excitation has been used in microscopy for nearly a decade, providing a number of demonstrated advantages over other methods for fluorescence imaging. Because excitation is achieved using longer, less energetic light, photodamage and photobleaching of the sample are reduced. Furthermore, since excitation occurs only at the focal point, this approach allows the practical collection of three-dimensionally resolved fluorescence images of live cells. However, due to the small two-photon cross-section of most fluorophores, pulsed lasers are required to generate detectable signal levels

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Rossi, P., S. Righi, L. Parente, et al. "PHOTOGRAMMETRIC AND FLUORESCENCE SOLUTIONS FOR MONITORING OF HABITAT FORMING ORGANISMS." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B2-2022 (May 30, 2022): 877–83. http://dx.doi.org/10.5194/isprs-archives-xliii-b2-2022-877-2022.

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Abstract. The development and testing of innovative technologies and automated data analysis methodologies offer tools for the monitoring of complex marine ecosystems and the direct and indirect effects of climate change on natural heritage. Photogrammetric methods allow precise mapping of the underwater landscape as well as detailed three-dimensional (3D) reconstruction of marine structures, improving the study of complex marine ecosystems. Moreover, fluorescence analyses can provide critical information about the health status of marine organisms. Analysing the variations in their self-fluor

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Keller, Harold W., and Vanessa M. Marshall. "A new iridescent corticolous myxomycete species (Licea: Liceaceae: Liceales) and crystals on American elm tree bark in Texas, U.S.A." Journal of the Botanical Research Institute of Texas 13, no. 2 (2019): 367–86. http://dx.doi.org/10.17348/jbrit.v13.i2.793.

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A Licea species new to science is described on the bark surface of living American elm (Ulmus americana L.) cultured in moist chambers. It is characterized by an iridescent peridium on the sides of the sporangium, a black apical circular patch of globular debris, and dark reddish black spores that are smooth over half the surface and ridged-reticulate over the other half with the paler thinner wall collapsing into a coffee-bean shape. This combination of morphological characters is distinct and separates this taxon from all other species of Licea. The history of moist chamber culture use and f

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Adeniyi, Makinde A., RaRasaq K. Adewoye, Gbenga O. Popoola, Babatunde Aderukuola, Azeez O. Ibrahim, and Ayotunde S. Azees. "Awareness, prevalence and risk burden of cataract among adults in IDO/OSI local government area, a rural community of Ekiti state, southwest Nigeria." International Journal Of Community Medicine And Public Health 10, no. 9 (2023): 3077–85. http://dx.doi.org/10.18203/2394-6040.ijcmph20232663.

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Background: Cataract is characterized by lens opacity, making images look blurred and hazy. It causes increased light sensitivity, decreased vision at night, and seeing double images, leading to total blindness. The WHO also estimates that cataract blindness will reach 40 million by 2025 due to ageing population and longer life expectancy. Developing countries, including Sub-Saharan Africa have the highest number of people who are blind due to cataract. This study aims to determine the awareness, prevalence and risk burden of cataract among adults in Ido/Osi LGA, a rural community of Ekiti Sta

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Letcher, Theodore, Julie Parno, Zoe Courville, Lauren Farnsworth, and Jason Olivier. "A generalized photon-tracking approach to simulate spectral snow albedo and transmittance using X-ray microtomography and geometric optics." Cryosphere 16, no. 10 (2022): 4343–61. http://dx.doi.org/10.5194/tc-16-4343-2022.

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Abstract. A majority of snow radiative transfer models (RTMs) treat snow as a collection of idealized grains rather than an organized ice–air matrix. Here we present a generalized multi-layer photon-tracking RTM that simulates light reflectance and transmittance of snow based on X-ray microtomography images, treating snow as a coherent 3D structure rather than a collection of grains. The model uses a blended approach to expand ray-tracing techniques applied to sub-1 cm3 snow samples to snowpacks of arbitrary depths. While this framework has many potential applications, this study's effort is f

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Windisch, Michael, Jakob Wassermann, Monica Leba, and Olimpiu Stoicuta. "Hadamard Error-Correcting Codes and Their Application in Digital Watermarking." Sensors 24, no. 10 (2024): 3062. http://dx.doi.org/10.3390/s24103062.

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In communication technologies such as digital watermarking, wireless sensor networks (WSNs), and visual light communication (VLC), error-correcting codes are crucial. The Enhanced Hadamard Error-Correcting Code (EHC), which is based on 2D Hadamard Basis Images, is a novel error correction technique that is presented in this study. This technique is used to evaluate the effectiveness of the video watermarking scheme. Even with highly sophisticated embedding techniques, watermarks usually fail to resist such comprehensive attacks because of the extraordinarily high compression rate of approximat

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Coopey, Ewan. "Inscribed funerary monuments of Legio VII and the emergence of military communities in 1st century AD Dalmatia." Prilozi Instituta za arheologiju u Zagrebu 40, no. 2 (2023): 89–128. http://dx.doi.org/10.33254/piaz.40.2.3.

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The Imperial Roman military consisted of a vast collection of armies and overlapping sub-communities, causing it to be a multi-layered entity. Scholars have explored its social dynamics since the 1980s, with epigraphic material – particularly of a funerary nature – providing valuable insight. The provinces of southeastern Europe, such as Dalmatia, are home to a great deal of well-catalogued archaeological and epigraphical material which could contribute to these studies, however, they are often left unconsidered in scholarship from outside the region. This paper conducts an epigraphical and ar

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APOPEI, Andrei-Ionuț, Nicolae BUZGAR, Andrei BUZATU, Andreea-Elena MAFTEI, and Liliana APOSTOAE. "DIGITAL 3D MODELS OF MINERALS AND ROCKS IN A NUTSHELL: ENHANCING SCIENTIFIC, LEARNING, AND CULTURAL HERITAGE ENVIRONMENTS IN GEOSCIENCES BY USING CROSS-POLARIZED LIGHT PHOTOGRAMMETRY." Carpathian Journal of Earth and Environmental Sciences 16, no. 1 (2021): 237–49. http://dx.doi.org/10.26471/cjees/2021/016/170.

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Three-dimensional (3D) minerals and rocks in the form of interactive, engaging, and immersive experiences are of paramount importance to the geoscience community, researchers, students, and philomaths. Moreover, the SARS-CoV-2 (COVID-19) crisis affecting our society in the spring of 2020 highlighted the importance of 3D material in geoscience education — compared to 2D images, the three-dimensional models provide a better way to learn and to recognize different minerals and rocks, properties, textures, etc. This paper seeks to provide a comprehensive method to create an interactive scientific,

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Liu, Jianyang, Ying Quan, Bin Wang, Jinan Shi, Lang Ming, and Mingze Li. "Estimation of Forest Stock Volume Combining Airborne LiDAR Sampling Approaches with Multi-Sensor Imagery." Forests 14, no. 12 (2023): 2453. http://dx.doi.org/10.3390/f14122453.

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Timely and reliable estimation of forest stock volume is essential for sustainable forest management and conservation. Light detection and ranging (LiDAR) data can provide an effective depiction of the three-dimensional structure information of forests, but its large-scale application is hampered by spatial continuity. This study aims to construct a LiDAR sampling framework, combined with multi-sensor imagery, to estimate the regional forest stock volume of natural secondary forests in Northeast China. Two sampling approaches were compared, including systematic sampling and classification-base

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Loda, Liubov, Iryna Pigel, and Lesia Dzendzeluk. "A Study on the state of photographic documents in Vasyl Stefanyk National Scientific Library of Ukraine in Lviv." Proceedings of Vasyl Stefanyk National Scientific Library of Ukraine in Lviv, no. 11(27) (2019): 195–208. http://dx.doi.org/10.37222/2524-0315-2019-11(27)-12.

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Collections of photographic documents constitute considerable information, document and art heritage. Photographs with non-existing today art and architectural objects are of particular importance. The task for their keepers is to save all visual information and to ensure accessibility to users. The paper’s purpose is to study the state of photographic documents kept in Vasyl Stefanyk National Scientific Library of Ukraine in Lviv. The article provides a profound analyze of damages’ types as well as factors that caused them and measures for their preservation. Authors highlighted the role of i

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Vásconez, Norma Lara, and Hernán Chamorro Sevilla. "Uso De Los Sensores Remotos En Mediciones Forestales." European Scientific Journal, ESJ 14, no. 15 (2018): 58. http://dx.doi.org/10.19044/esj.2018.v14n15p58.

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To understand the use of remote sensors in forestry measurements, some of the most relevant definitions have been taken from a wide variety that currently exist, therefore, we will say that these generally play a predominant role in the Dasometry and that all The forest resource requires qualitative and quantitative information regarding the state of the forest and its evolution over time, with sampling that follows one of the existing methods. Historically, modern discipline arises with the invention of flight and the first photographs are obtained from a balloon in the years 1858 and 1859, i

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Mao, Jianing, Yuye Ling, Ping Xue, and Yikai Su. "Importance sampling-accelerated simulation of full-spectrum backscattered diffuse reflectance." Biomedical Optics Express 14, no. 9 (2023): 4644. http://dx.doi.org/10.1364/boe.495489.

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The Monte Carlo (MC) method is one of the most widely used numerical tools to model the light interaction with tissue. However, due to the low photon collection efficiency and the need to simulate the entire emission spectrum, it is computationally expensive to simulate the full-spectrum backscattered diffuse reflectance (F-BDR). Here, we propose an acceleration scheme based on importance sampling (IS). We derive the biasing sampling function tailored for simulating BDR based on the two-term scattering phase function (TT). The parameters of the TT function at different wavelengths are directly

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Imai, N. N., M. H. Shimabukuro, A. F. C. Carmo, E. H. Alcântara, T. W. P. Rodrigues, and F. S. Y. Watanabe. "Bio-optical data integration based on a 4 D database system approach." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-7/W3 (April 29, 2015): 635–41. http://dx.doi.org/10.5194/isprsarchives-xl-7-w3-635-2015.

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Bio-optical characterization of water bodies requires spatio-temporal data about Inherent Optical Properties and Apparent Optical Properties which allow the comprehension of underwater light field aiming at the development of models for monitoring water quality. Measurements are taken to represent optical properties along a column of water, and then the spectral data must be related to depth. However, the spatial positions of measurement may differ since collecting instruments vary. In addition, the records should not refer to the same wavelengths. Additional difficulty is that distinct instru

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