- 标题
- 摘要
- 关键词
- 实验方案
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Use of Hyperspectral Image Data Outperforms Vegetation Indices in Prediction of Maize Yield
摘要： Hyperspectral cameras can provide reflectance data at hundreds of wavelengths. This information can be used to derive vegetation indices (VIs) that are correlated with agronomic and physiological traits. However, the data generated by hyperspectral cameras are richer than what can be summarized in a VI. Therefore, in this study, we examined whether prediction equations using hyperspectral image data can lead to better predictive performance for grain yield than what can be achieved using VIs. For hyperspectral prediction equations, we considered three estimation methods: ordinary least squares, partial least squares (a dimension reduction method), and a Bayesian shrinkage and variable selection procedure. We also examined the benefits of combining reflectance data collected at different time points. Data were generated by CIMMYT in 11 maize (Zea mays L.) yield trials conducted in 2014 under heat and drought stress. Our results indicate that using data from 62 bands leads to higher prediction accuracy than what can be achieved using individual VIs. Overall, the shrinkage and variable selection method was the best-performing one. Among the models using data from a single time point, the one using reflectance collected at 28 d after flowering gave the highest prediction accuracy. Combining image data collected at multiple time points led to an increase in prediction accuracy compared with using single-time-point data.
关键词： maize yield,hyperspectral imaging,prediction accuracy,vegetation indices,Bayesian methods
更新于2025-09-23 15:23:52
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Laboratory and clinical reliability of two spectrophotometers
摘要： Objective: To evaluate the repeatability, interexaminer, and interdevice reliability of two clinically applicable spectrophotometers under laboratory and clinical conditions. Material and Methods: For the in vitro part of the study, measurements were performed by the use of Vita Easyshade Advance 4.0 (ES-A) and the Easyshade V (ES-V) at identical positions on different shade tabs (3D-Master; Vita Zahnfabrik, Bad S?ckingen, Germany). To test repeatability, one shade tab was measured 50 times by one operator. To determine interrater and interdevice agreement, two operators used both devices to perform 10 measurements on five different shade tabs. Clinical interdevice and interexaminer reliability was checked with a positioning jig used (15 participants). Measurement accuracy of both devices was evaluated for the recommended color of shade tabs. Results: Repeatability of results from both Easyshades was excellent for all color components (maximum deviation between measurements was ≤0.1 units). Interrater agreement was also perfect (intraclass correlation, ICC = 1.000). Interdevice agreement was lower, but still good (ICC ≥ 0.834). In the clinical environment, interrater and interdevice agreements were similar (ICC > 0.964 and ICC > 0.873). Accuracy was satisfactory for both devices, with both observers in full agreement for nearly 80% of ratings. Conclusions: Both Easyshades produced reliable and accurate measurements and can therefore be recommended for clinical determination of tooth color. Clinical Significance: The outcome of this study might help clinicians estimate the performance of a new digital shade determination device.
关键词： L*a*b*,accuracy,reliability,Easyshade,spectrophotometer
更新于2025-09-23 15:23:52
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Glint Removal Assessment to Estimate the Remote Sensing Reflectance in Inland Waters with Widely Differing Optical Properties
摘要： The quality control of remote sensing reflectance (Rrs) is a challenging task in remote sensing applications, mainly in the retrieval of accurate in situ measurements carried out in optically complex aquatic systems. One of the main challenges is related to glint effect into the in situ measurements. Our study evaluates four different methods to reduce the glint effect from the Rrs spectra collected in cascade reservoirs with widely differing optical properties. The first (i) method adopts a constant coefficient for skylight correction (ρ) for any geometry viewing of in situ measurements and wind speed lower than 5 m·s?1; (ii) the second uses a look-up-table with variable ρ values accordingly to viewing geometry acquisition and wind speed; (iii) the third method is based on hyperspectral optimization to produce a spectral glint correction, and (iv) computes ρ as a function of wind speed. The glint effect corrected Rrs spectra were assessed using HydroLight simulations. The results showed that using the glint correction with spectral ρ achieved the lowest errors, however, in a Colored Dissolved Organic Matter (CDOM) dominated environment with no remarkable chlorophyll-a concentrations, the best method was the second. Besides, the results with spectral glint correction reduced almost 30% of errors.
关键词： remote sensing accuracy,inland waters,optically complex systems
更新于2025-09-23 15:23:52
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DeepSpectra: An end-to-end deep learning approach for quantitative spectral analysis
摘要： Learning patterns from spectra is critical for the development of chemometric analysis of spectroscopic data. Conventional two-stage calibration approaches consist of data preprocessing and modeling analysis. Misuse of preprocessing may introduce artifacts or remove useful patterns and result in worse model performance. An end-to-end deep learning approach incorporated Inception module, named DeepSpectra, is presented to learn patterns from raw data to improve the model performance. DeepSpectra model is compared to three CNN models on the raw data, and 16 preprocessing approaches are included to evaluate the preprocessing impact by testing four open accessed visible and near infrared spectroscopic datasets (corn, tablets, wheat, and soil). DeepSpectra model outperforms the other three convolutional neural network models on four datasets and obtains better results on raw data than in preprocessed data for most scenarios. The model is compared with linear partial least square (PLS) and nonlinear artificial neural network (ANN) methods and support vector machine (SVR) on raw and preprocessed data. The results show that DeepSpectra approach provides improved results than conventional linear and nonlinear calibration approaches in most scenarios. The increased training samples can improve the model repeatability and accuracy.
关键词： model accuracy,Inception,convolutional neural network,chemometrics,repeatability
更新于2025-09-23 15:23:52
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[IEEE 2018 WRC Symposium on Advanced Robotics and Automation (WRC SARA) - Beijing, China (2018.8.16-2018.8.16)] 2018 WRC Symposium on Advanced Robotics and Automation (WRC SARA) - Improved Monocular ORB-SLAM2 Inspired By The Optical Flow With Better Accuracy
摘要： ORB-SLAM2 is currently the best open source SLAM system with high positioning accuracy and map reusability. However, when using a monocular camera in a dynamic environment, the accuracy will be disturbed by the moving objects. Besides, even though there are no moving objects in the frame, there is space for further improvement in accuracy. This article improves the feature point selection based on monocular ORB-SLAM2 system, by creatively using the idea comes from optical flow and then using the K-Means algorithm to classify the matched feature point pairs. The existing open source datasets are used for evaluating the improvement. Under the pre-requirement that the improved system should ensure the real-time performance, the positioning accuracy of the improved system has been significantly improved.
关键词： Accuracy,Feature Point Classification,Optical Flow,K-Means
更新于2025-09-23 15:23:52
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: A Novel Similarity Measure for Matching Local Image Descriptors
摘要： mp-dissimilarity is a recently proposed data-dependence similarity measure. In the literature, how mp-dissimilarity is generally used for matching local image descriptors has been formalized, and three matching strategies have been proposed by incorporating (cid:96)p-norm distance and mp-dissimilarity. Each of these three matching strategies is essentially a two-round matching process that utilizes (cid:96)p-norm distance and mp-dissimilarity individually. This paper presents two novel similarity measures for matching local image descriptors. The first similarity measure normalizes and weights the similarities that are calculated using (cid:96)p-norm distance and mp-dissimilarity, respectively. The second similarity measure involves a novel calculation that takes into account both spatial distance and data distribution between descriptors. The proposed similarity measures are extensively evaluated on a few image registration benchmark data sets. Experimental results will demonstrate that the proposed similarity measures achieve higher matching accuracy and are able to attain better recall results when registering multi-modal images compared with the existing matching strategies that combine (cid:96)p-norm distance and mp-dissimilarity.
关键词： local descriptors,accuracy,mp-dissimilarity,image registration,(cid:96)p-norm distance,Similarity measure
更新于2025-09-23 15:23:52
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Geometric accuracy of remote sensing images over oceans: The use of global offshore platforms
摘要： The geometric accuracy of tens of millions of scenes of medium-resolution remote sensing (RS) images collected in the past 45 years has been systematically evaluated for land scenes, but the accuracy of ocean scenes is poorly known due to the lack of ground control points (GCPs). In this study, the locations of offshore platforms are first derived from time-series of Landsat-8 OLI images, and are then used as offshore reference points to systematically assess the geometric performance of RS images covering offshore oil/gas development areas. An inventory of 16,131 offshore platforms at the global scale is established, and then a novel method using the position-invariant characteristic of offshore platforms and the coherent characteristic of the geometric shift among tie-points (i.e. between sensed points from to-be-assessed images and the corresponding OLI-derived reference points) is developed for assessing the geometric accuracy of Landsat and other RS images. The method has been applied to 112,935 Landsat scenes (~1.87% of the entire archive) over oceans. The results indicate an optimal performance of Landsat OLI images (both pre-collection and Collection-1) but a less reliable performance of Landsat TM/ETM+ L1TP images. Approximately 50% of TM L1GS and ETM+ L1GT images have at least 2 pixels of geometric error. The new reference points inventory and the developed method were also applied to many other low-resolution and finer-resolution imagery (e.g. VIIRS Night-fire product, Terra/Aqua MODIS active fire product, ENVISAT ASAR, ALOS-1 PALSAR, Sentinel-1 SAR, Sentinel-2 MSI, the National Agriculture Imagery Program (NAIP) aerial images, and images from several Chinese satellites), and a quantitative description of the geometric accuracy of these sensors is also presented. The findings suggest that the new offshore reference point inventory is probably useful to help establish more robust offshore GCPs for U.S. Geological Survey (USGS) GCP library and further improve the ongoing USGS Global GCP improvement plan and European Space Agency Global Reference Image plan.
关键词： Offshore platforms,Remote sensing images,Landsat,Geometric accuracy,Ground control points
更新于2025-09-23 15:23:52
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Optical coordinate measurements in automotive industry
摘要： Photogrammetry is a technique of measuring 3D coordinates using photography as the main medium of metrology. This paper describes the use of the photogrammetric system in the automotive industry for control and measuring tasks. This contactless method is suitable for industrial application, because the measuring instruments are robust and mobile, so precise measurements are possible in production conditions. Presented results of measurements show that the optical measuring systems are powerful tools for quality control, analysis and discovering of causes of faults.
关键词： photogrammetry,optical measurement,accuracy,automotive industry
更新于2025-09-23 15:23:52
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - The Effect of Ground Truth on Accuracy Indexes in Hyperspectral Image Classification
摘要： In this paper, the effect of ground truths on performance evaluation of hyperspectral image classification is studied. The purpose is to investigate whether the accuracies in terms of three representative accuracy indexes, i.e., the overall accuracy (OA), the average accuracy (AA), and the Kappa coefficient, can be completely responsible when the ground truth is insufficient. The major contribution of this work is designing several experiments so as to subjectively and objectively analysis the influences of ground truths on performance evaluation. Furthermore, four evaluation metrics, i.e., the Pearson linear correlation coefficient (PLCC), root mean square error (RMSE), Spearmans rank correlation coefficient (SRCC), and Kendalls rank correlation coefficient (KRCC) have been adopted to measure the robustness of different classification methods to ground truths containing different numbers of labeled pixels and the location of ground truth in the image. Based on the designed experiments, a conclusion is obtained that insufficient ground truths may affect the performance of existing accuracy indexes. This underlines that over optimistic performance evaluations may exist when the ground truth contains a small number of labeled pixels.
关键词： accuracy indexes,Hyperspectral image classification,performance evaluation
更新于2025-09-23 15:22:29
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[IEEE 2018 IEEE 21st International Multi-Topic Conference (INMIC) - Karachi, Pakistan (2018.11.1-2018.11.2)] 2018 IEEE 21st International Multi-Topic Conference (INMIC) - Textural and Intensity Feature Based Retinal Vessels Classification for the Identification of Hypertensive Retinopathy
摘要： Hypertensive retinopathy is a retinal disease which results as a consequence of high blood pressure. Its early detection is necessary in reducing the likelihood of permanent visual damage. The percentage of people suffering from Hypertension is high, so it is required to develop a system which automatically detects the presence of this disease. High blood pressure damages retinal vessels and due to which arteries width is reduced. This damage can be analyzed by extracting the blood vessels, classifying the segmented vessels into veins and arteries and their Arteriovenous Ratio, which is an important measure to establish whether a person is suffering from Hypertensive Retinopathy or not. This research presents a technique for automatic classification of blood vessels of retina using different classifiers and the performance of each classifier is compared on same feature set. A novel combination of features is used for classification of vessels, which is an essential step for calculation of Arteriovenous Ratio and subsequently the detection of Hypertensive Retinopathy. MATLAB has been used for this research. The results that are achieved using the proposed feature set show’s 89% accuracy.
关键词： Accuracy (ACC),Arteriovenous Ratio (AVR),Support Vector Machine (SVM),Armed Forces Institute of Ophthalmology (AFIO),Hypertensive Retinopathy (HR)
更新于2025-09-23 15:22:29