检索结果-内蒙古大学图书馆

Application of computer vision technology in Agriculture

Agricultural Science & technology 2017年第11期18卷 2158-2162页

作者：黄喜梅毕建杰张楠丁筱玲李飞侯发东山东农业大学机械与电子工程学院山东省园艺机械与装备重点实验室泰安271018 山东农业大学作物生物学国家重点实验室山东泰安271018

With the development of image processing technology and computer, computer vision technology has been widely used in the production of agriculture,and has made many important achievements. This paper reviews its-research progress on diagnosis of agricultural products, water diagnosis, weed identification,product quality testing and grading, agricultural picking and sorting and other as- pects, and finally put forward its existing problems and prospects for the future.

关键词： Image processing computer vision technology Agriculture production Prospect

来源：评论

学校读者我要写书评

暂无评论

Multiplexed Pathogenic Bacteria Detection via a Two-Dimensional Encoded Fluorescent Microsphere System

引用

NANO LETTERS 2025年第6期25卷 2256-2265页

作者： Wang, Mengjiao Li, Letian Wei, Luyu Han, Yu Chen, Yiping Dalian Polytech Univ State Key Lab Marine Food Proc & Safety Control Dalian 116034 Liaoning Peoples R China Huazhong Agr Univ Key Lab Environm Correlat Dietol Minist Educ Wuhan 430070 Hubei Peoples R China Zhejiang Univ Coll Biosyst Engn & Food Sci Hangzhou 310058 Zhejiang Peoples R China Hubei Engn Univ Coll Life Sci & Technol Hubei Key Lab Qual Control Characterist Fruits & V Xiaogan 432000 Peoples R China

We developed an advanced microscopy imaging platform enabling amplification-free, multiplex detection of pathogenic bacteria in food and clinical samples, eliminating the need for DNA extraction. This platform leverages two-dimensional encoded polystyrene (PS) microspheres and an Argonaute-based decoding system to create multiplexed signal libraries. Each PS microsphere probe, encoded with spectrally distinct fluorophores and differing particle sizes, achieves high fluorescence through a tetrahedral DNA-enhanced hybridization chain reaction (TDNA-HCR), significantly enhancing signal intensity and reducing reaction time by 67%. Pathogenic bacteria identification relies on aptamer-specific recognition, which transduces pathogenic bacteria presence into guide DNA (gDNA) signals that activate Clostridium butyricum Argonaute (CbAgo) for precise DNA cleavage, encoding pathogenic bacteria type and concentration in the color, size, and count of fluorescent PS probes. A custom computer vision-powered algorithm processes these signals, offering sensitive detection at 102 CFU/mL within 1.5 h, demonstrating significant potential for food safety and clinical diagnostic applications.

关键词： Clostridium butyricum Argonaute programmablemicroscopy imaging pathogenic bacteria multiplexeddetection computer vision technology

来源：评论

学校读者我要写书评

暂无评论

A dual-channel correlation filtering tracker for real-time tracking based on deep features of improved CaffeNet and integrated manual features

引用

VISUAL computer 2025年第6期41卷 4347-4361页

作者： Xiao, Yuqi Wu, Yongjun West Anhui Univ Sch Mech & Vehicle Engn Luan City 237012 Anhui Peoples R China Chongqing Jiaotong Univ Sch Traff & Transportat Chongqing 400074 Peoples R China

This study proposed an adaptive dual-channel correlation filtering visual tracking approach based on deep features of improved CaffeNet and integrated manual features (ADCF for short). Firstly, to deal with the issue that the fixed learning rate in the update process of correlation filter can easily mix in too many invalid features and increase the burden of computation, we present a modified correlation filter learning rate, which can adjust its value according to the relationship between the CF-response value of the current candidate region and the given threshold value. Secondly, we integrated multiple manual features with fuzzy logic rule to combine their strengths including strong resistance to size change, rotation interference and illumination variation. Thirdly, we promoted the standard CaffeNet framework by introducing batch normalization, optimizing the nonlinearity of the activation function and accelerating the efficiency of the dropout layer with SVM. Finally, we parallel the depth features extracted by the improved CaffeNet with the proposed manual fusion features to form a dual-feature channel, thus obtaining a strategy for parallel extraction of visual features based on depth features and fusion of manual features. This dual-channel feature processing strategy combines the advantages of manual features and deep features, which can balance the details and semantic information of the target, making the tracker more robust in tracking diverse interference scenarios such as target rotation, lighting changes, scale changes and complex backgrounds. We visualized and numerically compared the tracking performance of the proposed method with other cutting-edge visual trackers using multiple classic tracking evaluation benchmarks, including OTB2015, VOT2018, TrackingNet and LaSOT. The tracking performance under diverse interference factors demonstrated that our proposed tracker has good performance in terms of accuracy, robustness and efficiency.

关键词： Correlation filter Visual tracking Feature integration CaffeNet computer vision technology

来源：评论

学校读者我要写书评

暂无评论

Detection of organic acids in maize silage based on fusion of near infrared spectroscopy and computer vision

引用

MICROCHEMICAL JOURNAL 2025年 213卷

作者： Yu, Yang Tian, Haiqing Zhang, Jue Li, Haijun Sun, Jianying Inner Mongolia Agr Univ Coll Mech & Elect Engn Hohhot 010018 Peoples R China Inner Mongolia Engn Res Ctr Intelligent Equipment Hohhot 010018 Peoples R China Inner Mongolia Normal Univ Coll Phys & Elect Informat Hohhot 010020 Peoples R China

Lactic acid, acetic acid, and propionic acid content in maize silage is an important indicator of feed quality and has a significant impact on livestock health and palatability. In this study, a new method combining near-infrared (NIR) spectroscopy and computer vision (CV) technology was proposed. By collecting spectral and image data during the secondary fermentation of maize silage, a predictive fusion model for lactic acid, acetic acid, and propionic acid was constructed, covering three dimensions: data-level, feature-level, and decision-level. In datalevel fusion, the preprocessed spectral and image features were fused. In feature-level fusion, the spectral features were screened separately by the bootstrapping soft shrinkage (BOSS), successive projections algorithm (SPA), and variable combination population analysis and iterative retained information variable (VCPA-IRIV) methods. The image features were screened by the least absolute shrinkage and selection operator (Lasso) regression algorithm, and these selected features were then fused separately. In decision-level fusion, a dynamic adaptive weighted stacked integration model (DAWSIM) was proposed. The results showed that DAWSIM performed the best among all models, with prediction set coefficients of determination (R2P) of 0.97, 0.81, and 0.69 for lactic acid, acetic acid, and propionic acid, respectively, and residual predictive deviation (RPD) of 6.07, 2.31, and 1.80. The results of this study demonstrate that data fusion holds substantial potential to improve model performance in predicting the organic acid content of maize silage.

关键词： Near-infrared spectroscopy technology computer vision technology Data fusion multiple sensor Organic acids Maize silage Stacked integration

来源：评论

学校读者我要写书评

暂无评论

Use neural Networks to Recognize Students' Handwritten Letters and Incorrect Symbols

Use neural Networks to Recognize Students' Handwritten Lette...

引用

2024 International Conference on Mechatronics and Intelligent Control, ICMIC 2024

作者： Zhu, Jia Jun Yang, Zichuan Hong, Binjie Song, Jiacheng Wang, Jiwei Chen, Tianhao Yang, Shuilan Lan, Zixun Ma, Fei Department of Information and Computing Science Xi'an Jiaotong-Liverpool University Suzhou China School of Engineering Suzhou Centennial College Suzhou China Department of Applied Mathematics Xi'an Jiaotong-Liverpool University Suzhou China GROW Inc. Suzhou China EasyStack Inc. Nanjing China TAL Education Group Beijing China

ISBN: (数字)9781510686847

ISBN: (纸本)9781510686830

Correcting students' multiple-choice answers is a repetitive and mechanical task that can be considered an image multi-classification task. Assuming possible options are 'abcd' and the correct option is one of the four, some students may write incorrect symbols or options that do not exist. In this paper, five classifications were set up - four for possible correct options and one for other incorrect writing. This approach takes into account the possibility of non-standard writing options. © 2025 SPIE.

关键词： Education and training Machine learning Data modeling Neural networks Image classification Visual process modeling computer vision technology Deep learning Performance modeling Transformers

来源：评论

学校读者我要写书评

暂无评论

A vision technology Fusion Framework for Sorting Panax notoginseng

引用

IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 2024年 73卷 1页

作者： Xing, Kaizhe Wang, Sen Chen, Mingfang Kunming Univ Sci & Technol Fac Mech & Elect Engn Kunming 650500 Peoples R China

In the automated processing of traditional Chinese medicine, the efficiency and accuracy of sorting are key factors affecting its quality. Panax notoginseng's various parts must be clearly distinguished before pharmaceutical preparation due to the different content of saponins and heavy metals. However, the various parts have significant differences among individuals, which makes it difficult for existing methods to distinguish them accurately and efficiently. Therefore, a multiclass detection method net integrating detector, tracker, and classifier (DTC-Net), which integrated multiple vision techniques, was proposed to aggregate the time domain characteristics with more refined part discrimination. Then, make a comprehensive judgment on the categories for each part. Compared to other algorithms, DTC-Net can track multicategory targets end-to-end in real time and has higher inference efficiency by jointly training the detector and classifier. On the video (or image) dataset taken in actual application scenarios, DTC-Net achieved excellent performance in industrial-grade scenarios under good and harsh lighting conditions, while efficiently focusing on multicategory targets. This can later guide pharmaceutical quality control.

关键词： Feature extraction Detectors Trajectory Target tracking Biomedical imaging Training Task analysis computer vision technology deep learning joint training Panax notoginseng real-time identifying time domain dynamic feature

来源：评论

学校读者我要写书评

暂无评论

Texture classification using a fuzzy texture spectrum and neural networks

引用

JOURNAL OF ELECTRONIC IMAGING 1998年第1期7卷 29-35页

作者： Taur, JS Tao, CW Natl Chung Hsing Univ Dept Elect Engn Taichung 40227 Taiwan Natl I Lan Inst Agr & Technol Dept Elect Engn I Lan Taiwan

In the research areas in computer vision, many applications have been discovered using texture classification techniques, such as the content retrieval in multimedia, the computer-aided diagnosis of medical images, and the segmentation of remote sensing images. The success of the texture classification of a given set of images hinges on the designs of texture features and the classifiers. We present a new texture feature, fuzzy texture spectrum, for texture classification, which is based on the relative gray levels between pixels. A vector of fuzzy values is used to indicate the relationship of the gray levels between the neighboring pixels. The fuzzy texture spectrum can be considered as the distribution of the fuzzified differences between the neighboring pixels. It is an improved version of the reduced texture spectrum, and it is less sensitive to the noise and the changing of the background brightness in texture images. We use 12 Brodatz texture images in the simulations to show the effectiveness of the new texture feature. Our simulation results show that the rate of classification error can be reduced to 0.2083%. (C) 1998 SPIE and IS&T. [S1017-9909(98)00301-8].

关键词： Neural networks Simulations Remote sensing computer vision technology computer-aided diagnosis Multimedia

来源：评论

学校读者我要写书评

暂无评论

Multiscale image analysis through the surface-shape operator

引用

JOURNAL OF ELECTRONIC IMAGING 2000年第3期9卷 305-316页

作者： Sukanya, P Takamatsu, R Sato, M Mahidol Univ Dept Comp Sci Bangkok 10400 Thailand Saitama Univ Fac Econ Urawa Saitama 3388570 Japan Tokyo Inst Technol Precis & Intelligence Lab Midori Ku Yokohama Kanagawa 2268503 Japan

This paper proposes a new operator called the surface-shape operator for describing image structure. We consider an image function as a bivariate surface, then established the surface-shape operator for describing the shape of each pixel compared with its neighborhood. From a geometry viewpoint, the types of surface shapes are elliptic, hyperbolic, cylindrical, etc. To give clearer meanings, in general, here we label them based on the topographic structure such as hill, dale, ridge, valley, etc. We also extend the surface-shape operator to have the capability of describing multi-scale topographic structures by incorporating in scale-space representation. The surface-shape operator has invariant properties under linear and monotonic gray-tone transformations, and is insensitive to additive noises modeled by linear functions, so if has robustness with brightness variations and shading effects. Finally, we illustrate applicability of the surface-shape operator with applications to image classifications. The proposed method is compared with the spatial gray-level-dependence method and the multiresolution simultaneous autoregressive method. The results show that the proposed method works better, and has much more robustness with brightness variations and shading effects than those methods. (C) 2000 SPIE and IS&T. [S1017-9909(00)00103-3].

关键词： Image classification Image analysis Matrices Computing systems Mahalanobis distance Atrial fibrillation Autoregressive models computer vision technology Machine vision Visualization

来源：评论

学校读者我要写书评

暂无评论

Non-Destructive Prediction Approach for Pomelo Granulation Rate Using MRI technology

引用

JOURNAL OF FOOD PROCESS ENGINEERING 2024年第12期47卷

作者： Jie, Dengfei Li, Zhihong Wu, Shuang Tian, Botao Wang, Ping He, Jincheng Wei, Xuan Fujian Agr & Forestry Univ Coll Mech & Elect Engn Fuzhou Peoples R China Fujian Agr & Forestry Univ Coll Hort Fuzhou Peoples R China

Pomelo is prone to juice sac granulation during ripening and storage, resulting in decreased moisture content, hard flesh, and bland flavor, which affects market value and consumer experience. Due to the complexity of the causes of juice sac granulation, coupled with the thick peel of pomelo, the detection means of pomelo is lacking and difficult to detect. In order to solve the shortcomings of the traditional granulation rate calculation, which has an error and cannot realize non-destructive detection. This study proposes a non-destructive detection of pomelo juice sac granulation and the calculation of granulation rate based on the nuclear magnetic resonance imaging (MRI) technology combined with the computer vision technology. Based on the strong analytical power of the MRI technology for moisture and the change of moisture in the granulated juice sac of pomelo, in this study, the cross section of pomelo was scanned by MRI scanner to obtain the corresponding MRI images. The MRI images of the cross section of pomelo were segmented using the threshold segmentation method to realize the calculation of the percentage of granulated pulp. The experimental results show that the segmentation threshold T1 = 102 can effectively segment the pulp from the peel, and the segmentation threshold T2 = 175 can effectively segment the granulated pulp from the normal pulp. The granulation rate of pomelo pulp can be calculated by calculating the ratio of the granulated pulp area to the total pulp area. Therefore, based on the MRI technology can be used for the detection of the granulation rate of pomelo juice sac, which provides a certain reference value for the subsequent non-destructive detection of the internal quality of large melons and fruits.

关键词： computer vision technology granulation MRI Otsu algorithm pomelo

来源：评论

学校读者我要写书评

暂无评论

Recognition of plants using a stochastic L-system model

引用

JOURNAL OF ELECTRONIC IMAGING 2002年第1期11卷 50-58页

作者： Samal, A Peterson, B Holliday, DJ Univ Nebraska Dept Comp Sci & Engn Lincoln NE 68588 USA

Recognition of natural shapes like leaves, plants, and trees, has proven to be a challenging problem in computer vision. The members of a class of natural objects are not identical to each other They are similar, have similar features, but are not exactly the same. Most existing techniques have not succeeded in effectively recognizing these objects. One of the main reasons is that the models used to represent them are inadequate themselves. In this research we use a fractal model, which has been very effective in modeling natural shapes, to represent and then guide the recognition of a class of natural objects, namely plants, Variation in plants is accommodated by using the stochastic L-systems, A learning system is then used to generate a decision tree that can be used for classification. Results show that the approach is successful for a large class of synthetic plants and provides the basis for further research into recognition of natural plants. (C) 2002 SPIE and IST.

关键词： Fractal analysis Stochastic processes 3D modeling Visual process modeling Computing systems computer vision technology Machine vision Mathematical modeling Feature extraction Visualization

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：