- 标题
- 摘要
- 关键词
- 实验方案
- 产品
-
Simultaneous determination of trace amounts of copper and cobalt in high concentration zinc solution using UV–vis spectrometry and Adaboost
摘要： Simultaneous determination of trace ions in zinc metallurgical solution provides effective process information for optimal control in zinc hydrometallurgy. In this paper, Ultraviolet and Visible (UV–vis) spectrometry with the analytical system based on nitroso R salt is applied to simultaneously determine the trace concentrations of copper and cobalt in high and varying concentration zinc sulfate solution. Firstly, fractional differentiation is applied to reduce the overlap between ions and covering of zinc on trace ions. Then, a multi-indexes fusion wavelength selection is utilized to find the optimal combination of variables for the partial least squares model. Next, to reduce the interference caused by competitive reaction and matrix effect of zinc ions, Adaboost creates a group of weak models to analyze trace ion concentration from multiple perspectives. Finally, Adaboost trains the sample weights and model weights of weak models and integrates those weak models into a strong model to predict the trace ion concentration comprehensively. A spectrum dataset containing 72 samples of zinc, copper and cobalt ions mixture solution is prepared for the proposed method. Results show that the proposed method can simultaneously determine the trace concentrations of copper and cobalt in high and varying concentration zinc sulfate solution accurately.
关键词： Adaboost,UV–vis,Simultaneous determination,Trace ion,High concentration zinc solution
更新于2025-09-23 15:23:52
-
Photovoltaic Solar Cells for Outdoor LiFi Communications
摘要： Most state-of-the-art methods in pedestrian detection are unable to achieve a good trade-off between accuracy and efficiency. For example, ACF has a fast speed but a relatively low detection rate, while checkerboards have a high detection rate but a slow speed. Inspired by some simple inherent attributes of pedestrians (i.e., appearance constancy and shape symmetry), we propose two new types of non-neighboring features: side-inner difference features (SIDF) and symmetrical similarity features (SSFs). SIDF can characterize the difference between the background and pedestrian and the difference between the pedestrian contour and its inner part. SSF can capture the symmetrical similarity of pedestrian shape. However, it for neighboring features to have such above characterization abilities. Finally, we propose to combine both non-neighboring features and neighboring features for pedestrian detection. It is found that non-neighboring features can further decrease the log-average miss rate by 4.44%. The relationship between our proposed method and some state-of-the-art methods is also given. Experimental results on INRIA, Caltech, and KITTI data sets demonstrate the effectiveness and efficiency of the proposed method. Compared with the state-of-the-art methods without using CNN, our method achieves the best detection performance on Caltech, outperforming the second best method (i.e., checkerboards) by 2.27%. Using the new annotations of Caltech, it can achieve 11.87% miss rate, which outperforms other methods.
关键词： feature extraction,non-neighboring features,Pedestrian detection,neighboring features,adaboost
更新于2025-09-23 15:19:57
-
[IEEE 2018 7th European Workshop on Visual Information Processing (EUVIP) - Tampere, Finland (2018.11.26-2018.11.28)] 2018 7th European Workshop on Visual Information Processing (EUVIP) - A Hybrid Approach to Hand Detection and Type Classification in Upper-Body Videos
摘要： Detection of hands in videos and their classification into left and right types are crucial in various human-computer interaction and data mining systems. A variety of effective deep learning methods have been proposed for this task, such as region-based convolutional neural networks (R-CNNs), however the large number of their proposal windows per frame deem them computationally intensive. For this purpose we propose a hybrid approach that is based on substituting the 'selective search' R-CNN module by an image processing pipeline assuming visibility of the facial region, as for example in signing and cued speech videos. Our system comprises two main phases: preprocessing and classification. In the preprocessing stage we incorporate facial information, obtained by an AdaBoost face detector, into a skin-tone based segmentation scheme that drives Kalman filtering based hand tracking, generating very few candidate windows. During classification, the extracted proposal regions are fed to a CNN for hand detection and type classification. Evaluation of the proposed hybrid approach on four well-known datasets of gestures and signing demonstrates its superior accuracy and computational efficiency over the R-CNN and its variants.
关键词： region-based convolutional neural network (R-CNN),hand type classification,Hand detection,AdaBoost face detection,Kalman filtering
更新于2025-09-19 17:15:36
-
Leak monitoring and localization in baghouse filtration system using a distributed optical fiber dynamic air pressure sensor
摘要： Coherent Rayleigh backscattering noise produced by the detection of the dynamic air?ow applied to a standard optical ?ber is proposed to monitor and locate the potential broken fabric bags within a baghouse ?ltration system with a sensing distance of 2 km. The optical ?ber cable hangs freely inside the fabric bags with small leak holes. Experimental results demonstrated that the proposed distributed optical air pressure sensor is capable of identifying broken bags via the measurement of air?ow perturbation applied onto the optical ?ber cable. Field test at a baghouse ?ltration test platform was conducted and results showed that the location accuracy of the system is less than ± 5 m with a detectable hole diameter of 0.3 cm and a recognition rate of ~87.6% measured by Adaboost-Support Vector Machine (ADA-SVM) method. A false alarm rate of 9% for this particular leak diameter is achieved.
关键词： Optical ?ber sensor,Air pressure monitoring,Leak detection and localization,Air ?ow,Adaboost
更新于2025-09-19 17:13:59
-
An Overview on the Applications of Typical Non-linear Algorithms Coupled With NIR Spectroscopy in Food Analysis
摘要： Near-infrared (NIR) spectroscopy as a low-cost technique with its non-destructive fast nature, precision, control, accuracy, repeatability, and reproducibility has been extensively employed in most industries for food quality measurements. Its coupling to different modeling techniques has been identified as a way of improving the accuracy and robustness of non-destructive measurement of foodstuffs. This review provides an overview of the application of non-linear algorithms in food quality and safety specific to NIR spectroscopy. The review also provides in-depth knowledge about the principle of NIR spectroscopy along with different non-linear models such as artificial neural network (ANN), AdaBoost, local algorithm (LA), support vector machine (SVM), and extreme learning machine (ELM). Moreover, non-linear algorithms coupled with NIR spectroscopy for ensuring food quality and their future perspective has been discussed.
关键词： BP-ANN,NIR spectroscopy,Non-linear applications,Non-linear algorithm,AdaBoost
更新于2025-09-19 17:13:59
-
[IEEE 2019 IEEE 8th International Conference on Advanced Optoelectronics and Lasers (CAOL) - Sozopol, Bulgaria (2019.9.6-2019.9.8)] 2019 IEEE 8th International Conference on Advanced Optoelectronics and Lasers (CAOL) - New aspects of resonant effects in laser-modified Quantum Electrodynamics processes : (Invited)
摘要： Most state-of-the-art methods in pedestrian detection are unable to achieve a good trade-off between accuracy and efficiency. For example, ACF has a fast speed but a relatively low detection rate, while checkerboards have a high detection rate but a slow speed. Inspired by some simple inherent attributes of pedestrians (i.e., appearance constancy and shape symmetry), we propose two new types of non-neighboring features: side-inner difference features (SIDF) and symmetrical similarity features (SSFs). SIDF can characterize the difference between the background and pedestrian and the difference between the pedestrian contour and its inner part. SSF can capture the symmetrical similarity of pedestrian shape. However, it for neighboring features to have such above characterization abilities. Finally, we propose to combine both non-neighboring features and neighboring features for pedestrian detection. It is found that non-neighboring features can further decrease the log-average miss rate by 4.44%. The relationship between our proposed method and some state-of-the-art methods is also given. Experimental results on INRIA, Caltech, and KITTI data sets demonstrate the effectiveness and efficiency of the proposed method. Compared with the state-of-the-art methods without using CNN, our method achieves the best detection performance on Caltech, outperforming the second best method (i.e., checkerboards) by 2.27%. Using the new annotations of Caltech, it can achieve 11.87% miss rate, which outperforms other methods.
关键词： feature extraction,non-neighboring features,Pedestrian detection,neighboring features,adaboost
更新于2025-09-16 10:30:52
-
Quantitative Analysis of Major Metals in Agricultural Biochar Using Laser-Induced Breakdown Spectroscopy with an Adaboost Artificial Neural Network Algorithm
摘要： To promote the green development of agriculture by returning biochar to farmland, it is of great signi?cance to simultaneously detect heavy and nutritional metals in agricultural biochar. This work aimed ?rst to apply laser-induced breakdown spectroscopy (LIBS) for the determination of heavy (Pb, Cr) and nutritional (K, Na, Ca, Mg, Cu, and Zn) metals in agricultural biochar. Each batch of collected biochar was prepared to a standardized sample using the separating and milling method. Two types of univariate analysis model were developed using peak intensity and integration area of the sensitive emission lines, but the performance did not satisfy the requirements of practical application because of the poor correlations between the measured values and predicted values, as well as large relative standard deviation of the prediction (RSDP) values. An ensemble learning algorithm, adaboost backpropagation arti?cial neural network (BP-Adaboost), was then used to develop the multivariate analysis models, which had a more robust performance than traditional univariate analysis, partial least squares regression (PLSR), and backpropagation arti?cial neural network (BP-ANN). The optimized RSDP values for K, Ca, Mg, and Cu were less than 10%, while the RSDP values for Pb, Cr, Zn, and Na were in the range of 10–20%. Moreover, the pairwise t-test of its prediction set showed that there was no signi?cant di?erence between the measurements of LIBS and ICP-MS. The promising results indicate that rapid and simultaneous detection of major heavy and nutritional metals in agricultural biochar can be achieved using LIBS and reasonable chemometric algorithms.
关键词： agricultural biochar,LIBS,BP-Adaboost,heavy and nutritional metals
更新于2025-09-12 10:27:22
-
[IEEE 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) - Honolulu, HI (2018.7.18-2018.7.21)] 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) - Corner Detection Based Automatic Segmentation of Bioresorbable Vascular Scaffold Struts in IVOCT Images
摘要： Bioresorbable Vascular scaffold (BVS) is a promising type of stent in percutaneous coronary intervention. Struts apposition assessment is important to ensure the safety of implanted BVS. Currently, BVS struts apposition analysis in IVOCT images still depends on manual delineation of struts, which is labor intensive and time consuming. Automatic struts segmentation is highly desired to simplify and speed up quantitative analysis. However, it is difficult to segment struts accurately based on the contour, due to the influence of fractures inside strut and blood artifacts around strut. In this paper, a novel framework of automatic struts segmentation based on four corners is introduced, in which priori knowledge is utilized that struts have obvious feature of box-shape. Firstly, a cascaded AdaBoost classifier based on enriched haar-like features is trained to detect struts corners. Then, segmentation result can be obtained based on the four detected corners of each strut. Tested on five pullbacks consisting of 483 images with strut, our novel method achieved an average Dice’s coefficient of 0.82 for strut segmentation areas. It concludes that our method can segment struts accurately and robustly. Furthermore, automatic struts malapposition analysis in clinical practice is feasible based on the segmentation results.
关键词： Intravascular Optical Coherence Tomography (IVOCT),Bioresorbable Vascular Scaffold (BVS),Struts Segmentation,Corner Detection,AdaBoost Classifier
更新于2025-09-10 09:29:36
-
DETECTION OF TUBERCULOSIS USING CHEST X RAY (CXR)
摘要： Tuberculosis is an airborne disease that affects many organs in the body especially lungs. This disease is caused by a bacteria known as Mycobacterium Tuberculosis. When the bacteria becomes active it affects the body. If the disease is not treated properly a loss of life may occur. A robotic detection of tuberculosis is presented in this paper with the help of patient chest x ray(CXR).The input image is then filtered by Gaussian filter to remove noise and then the lung region gets segmented by using graph cut segmentation. The segmented lung region is partitioned into four lobes. The infected region is then segmented for that region the feature values are calculated. With these values it is classified as normal or abnormal by using Ada boost classifier.
关键词： Tuberculosis,lobes,AdaBoost,Classification,CXR,Feature extraction
更新于2025-09-09 09:28:46
-
[IEEE 2018 IEEE 7th Global Conference on Consumer Electronics (GCCE) - Nara, Japan (2018.10.9-2018.10.12)] 2018 IEEE 7th Global Conference on Consumer Electronics (GCCE) - Accuracy Improvement of Image Recognition by Contrast Correction for Autonomous Drone Flights
摘要： Research and practical applications for autonomous travel for implementation on a range of mobile device platforms have been developed in recent years. With a wide variety of applications for autonomous driving, the topic has attracted a great deal of attention in the delivery industry. In this paper, we propose a method that offers high precision and high-speed processing for autonomous flight using a drone and a low-cost HD camera.
关键词： Image recognition,Haar-like features,Drone,AdaBoost
更新于2025-09-04 15:30:14