Literatura científica selecionada sobre o tema "Canopy volume detection"
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Artigos de revistas sobre o assunto "Canopy volume detection"
Wang, Mengmeng, Hanjie Dou, Hongyan Sun, Changyuan Zhai, Yanlong Zhang e Feixiang Yuan. "Calculation Method of Canopy Dynamic Meshing Division Volumes for Precision Pesticide Application in Orchards Based on LiDAR". Agronomy 13, n.º 4 (7 de abril de 2023): 1077. http://dx.doi.org/10.3390/agronomy13041077.
Texto completo da fonteGu, Chenchen, Xiu Wang, Xiaole Wang, Fuzeng Yang e Changyuan Zhai. "Research Progress on Variable-Rate Spraying Technology in Orchards". Applied Engineering in Agriculture 36, n.º 6 (2020): 927–42. http://dx.doi.org/10.13031/aea.14201.
Texto completo da fonteRoman, Carla, Hongyoung Jeon, Heping Zhu, Javier Campos e Erdal Ozkan. "Stereo Vision Controlled Variable Rate Sprayer for Specialty Crops: Part II. Sprayer Development and Performance Evaluation". Journal of the ASABE 66, n.º 5 (2023): 1005–17. http://dx.doi.org/10.13031/ja.15578.
Texto completo da fonteGu, Chenchen, Changyuan Zhai, Xiu Wang e Songlin Wang. "CMPC: An Innovative Lidar-Based Method to Estimate Tree Canopy Meshing-Profile Volumes for Orchard Target-Oriented Spray". Sensors 21, n.º 12 (21 de junho de 2021): 4252. http://dx.doi.org/10.3390/s21124252.
Texto completo da fonteZhou, Huitao, Weidong Jia, Yong Li e Mingxiong Ou. "Method for Estimating Canopy Thickness Using Ultrasonic Sensor Technology". Agriculture 11, n.º 10 (16 de outubro de 2021): 1011. http://dx.doi.org/10.3390/agriculture11101011.
Texto completo da fonteSaha, Kowshik Kumar, Nikos Tsoulias, Cornelia Weltzien e Manuela Zude-Sasse. "Estimation of Vegetative Growth in Strawberry Plants Using Mobile LiDAR Laser Scanner". Horticulturae 8, n.º 2 (19 de janeiro de 2022): 90. http://dx.doi.org/10.3390/horticulturae8020090.
Texto completo da fonteLim, Kevin, Paul Treitz, Michael Wulder, Benoît St-Onge e Martin Flood. "LiDAR remote sensing of forest structure". Progress in Physical Geography: Earth and Environment 27, n.º 1 (março de 2003): 88–106. http://dx.doi.org/10.1191/0309133303pp360ra.
Texto completo da fonteColaço, A. F., R. G. Trevisan, J. P. Molin, J. R. Rosell-Polo e A. Escolà. "Orange tree canopy volume estimation by manual and LiDAR-based methods". Advances in Animal Biosciences 8, n.º 2 (1 de junho de 2017): 477–80. http://dx.doi.org/10.1017/s2040470017001133.
Texto completo da fonteHermosilla, Txomin, Luis A. Ruiz, Alexandra N. Kazakova, Nicholas C. Coops e L. Monika Moskal. "Estimation of forest structure and canopy fuel parameters from small-footprint full-waveform LiDAR data". International Journal of Wildland Fire 23, n.º 2 (2014): 224. http://dx.doi.org/10.1071/wf13086.
Texto completo da fonteLeite, Rodrigo Vieira, Cibele Hummel do Amaral, Raul de Paula Pires, Carlos Alberto Silva, Carlos Pedro Boechat Soares, Renata Paulo Macedo, Antonilmar Araújo Lopes da Silva, Eben North Broadbent, Midhun Mohan e Hélio Garcia Leite. "Estimating Stem Volume in Eucalyptus Plantations Using Airborne LiDAR: A Comparison of Area- and Individual Tree-Based Approaches". Remote Sensing 12, n.º 9 (9 de maio de 2020): 1513. http://dx.doi.org/10.3390/rs12091513.
Texto completo da fonteTeses / dissertações sobre o assunto "Canopy volume detection"
Mohammadi, Vahid. "Design, Development and Evaluation of a System for the Detection of Aerial Parts and Measurement of Growth Indices of Bell Pepper Plant Based on Stereo and Multispectral Imaging". Electronic Thesis or Diss., Bourgogne Franche-Comté, 2022. http://www.theses.fr/2022UBFCK109.
Texto completo da fonteDuring the growth of plants, monitoring them brings much benefits to the producers. This monitoring includes the measurement of physical properties, counting plants leaves, detection of plants and separation of them from weeds. All these can be done different techniques, however, the techniques are favorable that are non-destructive because plant is a very sensitive creature that any manipulation can put disorder in its growth or lead to losing leaves or branches. Imaging techniques are of the best solutions for plants growth monitoring and geometric measurements. In this regard, in this project the use of stereo imaging and multispectral data was studied. Active and passive stereo imaging were employed for the estimation of physical properties and counting leaves and multispectral data was utilized for the separation of crop and weed. Bell pepper plant was used for imaging measurements for a period of 30 days and for crop/weed separation, the spectral responses of bell pepper and five weeds were measured. Nine physical properties of pepper leaves (i.e. main leaf diameters, leaf area, leaf perimeter etc.) were measured using a scanner and was used as a database and also for comparing the estimated values to the actual values. The stereo system consisted of two LogiTech cameras and a video projector. First the stereo system was calibrated using sample images of a standard checkerboard in different position and angles. The system was controlled using the computer for turning a light line on, recording videos of both cameras while light is being swept on the plant and then stopping the light. The frames were extracted and processed. The processing algorithm first filtered the images for removing noise and then thresholded the unwanted pixels of environment. Then, using the peak detection method of Center of Mass the main and central part of the light line was extracted. After, the images were rectified by using the calibration information. Then the correspondent pixels were detected and used for the 3D model development. The obtained point cloud was transformed to a meshed surface and used for physical properties measurement. Passive stereo imaging was used for leaf detection and counting. For passive stereo matching six different matching algorithms and three cost functions were used and compared. For spectral responses of plants, they were freshly moved to the laboratory, leaves were detached from the plants and placed on a blur dark background. Type A lights were used for illumination and the spectral measurements were carried out using a spectroradiometer from 380 nm to 1000 nm. To reduce the dimensionality of the data, PCA and wavelet transform were used. Results of this study showed that the use of stereo imaging can propose a cheap and non-destructive tool for agriculture. An important advantage of active stereo imaging is that it is light-independent and can be used during the night. However, the use of active stereo for the primary stage of growth provides acceptable results but after that stage, the system will be unable to detect and reconstruct all leaves and plant's parts. Using ASI the R2 values of 0.978 and 0.967 were obtained for the estimation leaf area and perimeter, respectively. The results of separation of crop and weeds using spectral data were very promising and the classifier—which was based on deep learning—could completely separate pepper from other five weeds
Capítulos de livros sobre o assunto "Canopy volume detection"
Herbert, Rosemary. "Sir Arthur Conan Doyle (1859–1930)". In Murder on Deck!, 3–18. Oxford University PressNew York, NY, 1998. http://dx.doi.org/10.1093/oso/9780195086034.003.0001.
Texto completo da fonteTrabalhos de conferências sobre o assunto "Canopy volume detection"
Lifeng, Zhou, Cheng Zhaoyu, Cai Jiafan e Tang Yi. "In-Service Inspection Technology Research on CANOPY Seal Weld of Control Rod Drive Mechanism in PWR". In 2017 25th International Conference on Nuclear Engineering. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/icone25-66999.
Texto completo da fonteForget, Magali, e Mark Davies. "Liquid Bridges: A Novel Approach for Dispensing Biofluids, Characterisation and Correlations". In ASME 2007 5th International Conference on Nanochannels, Microchannels, and Minichannels. ASMEDC, 2007. http://dx.doi.org/10.1115/icnmm2007-30099.
Texto completo da fonte