Relevant bibliographies by topics / Tree training

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
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Academic literature on the topic 'Tree training'

Author: Grafiati
Published: 4 June 2021
Last updated: 15 February 2022

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Journal articles on the topic "Tree training"

1

Graehl, Jonathan, Kevin Knight, and Jonathan May. "Training Tree Transducers." Computational Linguistics 34, no. 3 (September 2008): 391–427. http://dx.doi.org/10.1162/coli.2008.07-051-r2-03-57.

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Many probabilistic models for natural language are now written in terms of hierarchical tree structure. Tree-based modeling still lacks many of the standard tools taken for granted in (finite-state) string-based modeling. The theory of tree transducer automata provides a possible framework to draw on, as it has been worked out in an extensive literature. We motivate the use of tree transducers for natural language and address the training problem for probabilistic tree-to-tree and tree-to-string transducers.
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Blackburn, Bryan, and Curt R. Rom. "Early Performance of Six Peach Training Systems." HortScience 33, no. 4 (July 1998): 600a—600. http://dx.doi.org/10.21273/hortsci.33.4.600a.

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The effects of six freestanding training systems (Open Center, Untrained, 2-Scaffold V, 4-Scaffold V, Leaning V, and Central Leader at tree densities of 161, 161, 245, 375, 375, and 300 trees/acre, respectively) on yield and tree growth of `Redhaven' on Lovell rootstock were evaluated. Open-center and untrained trees were largest and had greatest yields per tree. The 2-scaffold V had the greatest production in kilograms per acre. Early productivity was related to tree density and pruning severity, not tree size. Training systems had no effect on fruit size.
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Churn, Peter. "The tree of training." Education for Primary Care 30, no. 4 (May 30, 2019): 243–45. http://dx.doi.org/10.1080/14739879.2019.1613934.

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Evans, G. E., D. E. Deyton, and J. W. High. "COMPARISONS OF PLANT DENSITIES AND TRAINING SYSTEMS OF PEACH TREES." HortScience 27, no. 6 (June 1992): 638d—638. http://dx.doi.org/10.21273/hortsci.27.6.638d.

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`Redhaven' peach tree plantings were established in 1985 to compare tree densities (299 trees/ha to 1794 trees/ha) and training systems (Open Vase, Central Leader, Y-shaped, Palmette Trellis, Tatura Trellis, and MIA Trellis). Tree trunk growth (diameter) was significantly less as the population of trees increased. Trunks of trees trained to the Open Vase were larger than Central Leader or Y-shaped trees. In 1988, yields per ha increased as tree density increased. Trees trained to the Tatura Trellis (897 trees/ha) had the highest yields (27.7 t/ha). Trees trained to the Central Leader and planted at 1794, 897, and 598 trees/ha had next highest yields of 24.5, 21.4, and 24.3 t/ha, respectively. By the 6th year, yield differences were not generally related to tree density. The top yielding systems were Open Vase (598 trees/ha) and Tatura Trellis (897 trees/ha) with yields of 32.1 and 29.0 t/ha, respectively. Trees trained to Open Vase had higher yield efficiencies (kg/cm2 limb CSA) in 1991 than trees in other systems-spacings and had yields of 23.6, 27.4, and 32.1 t/ha for plant densities of 299, 448 and 598 trees/ha, respectively.
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Blažková, J., H. Drahošová, and I. Hlušičková. "Tree vigour, cropping, and phenology of sweet cherries in two systems of tree training on dwarf rootstocks." Horticultural Science 37, No. 4 (November 3, 2010): 127–38. http://dx.doi.org/10.17221/60/2010-hortsci.

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Five cultivars and four rootstocks (Gisela 5, P-HL-A, P-HL-B, and Tabel Edabriz) were evaluated on trees in fruiting stage trained like spindle and on trellis. Tree vigour was significantly related to cultivar, rootstock and to tree training. Spindles were generally more vigorous than trees on trellis with exception of cv. Kordia. In several cases special combinations of cultivar, rootstock, and method of tree training differed significantly from mean effects of the three factors. Time of flowering was significantly dependent on the cultivar and varied annually within 15 days. Time of fruit harvest was also influenced by the rootstock and in two cases mutually contradictory to the tree training method. Yields per tree were generally dependent on the cultivar. With Burlat and cv. Kordia rootstock and tree training were also important. Higher specific yields were recorded on trellis-trained trees. Remarkable in this respect were Vanda and trees of Summit on P-HL-B and Starking Hardy Giant on Tabel Edabriz. Higher specific yields on spindle had Kordia on P-HL-A and Tabel Edabriz and Burlat on P-HL-A. Mean values of annual yields per hectare in spindle ranged between 10.0 to 17.5 t whereas in trellis between 6.7 to 12.3 t. The absolute highest annual yield (35.7 t) was recorded on spindle trees of Kordia on P-HL-A. In trellis the highest yield of 27.1 t had Kordia on Gisela 5. The advantage of spindle over trellis was greater in Burlat and Kordia but much lower in cv. Vanda. Fruit size mainly depended on the year. Only two rootstocks influenced fruit size differently in some years. Training system had no effect on fruit size.
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Ozkan, Y., K. Yıldız, E. Küçüker, Ç. Çekiç, M. Özgen, and Y. Akça. " Early performance of cv. Jonagold apple on M.9 in five tree training systems." Horticultural Science 39, No. 4 (November 19, 2012): 158–63. http://dx.doi.org/10.17221/35/2012-hortsci.

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The effects of five training systems on tree growth, fruit yield and some fruit characteristics were assessed in Jonagold apple cv. grafted on M.9 rootstock. The trees were trained in one of five ways: slender spindle (SS; 4,761 trees/ha), vertical axis (VA; 2,857 trees/ha), hytec (HT; 1,904 tree/ha) and two different tree densities of super spindle (L-Super S with 5,000 trees/ha; H-Super S with 10,000 trees/ha). Trunk cross-sectional area (TCA) was higher in HT and VA than SS, L-Super S and H-Super S in the 4<sup>th</sup> year. While HT had the highest cumulative yield/tree, the lowest cumulative yield was observed in H-Super S. Although HT had the highest yield/ tree, it ranked the last in cumulative yield efficiency (CYE) due to high TCA. The highest (CYE) was measured in trees trained as L-Super S. When cumulative yields (CY)/ha were evaluated, the yield advantage of high density planting was clearly evident for the first three cropping years. H-Super S systems (10,000 trees/ha) had the highest CY/ha and achieved a yield of 91.24 t/ha in year 4. HT (1,904 trees/ha) had the lowest CY/ha (33.46 t). Training systems had no consistent effect on average fruit diameter, weight, firmness, soluble solid and titratable acidity. &nbsp;
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Connell, Joseph H., Warren Micke, James Yeager, Janine Hasey, Bill Krueger, and Craig Weakley. "TRAINING PERMANENT AND TEMPORARY TREES." HortScience 25, no. 9 (September 1990): 1169c—1169. http://dx.doi.org/10.21273/hortsci.25.9.1169c.

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High orchard establishment costs require greater production early in an orchard's life. Our goal was to develop temporary trees at the least cost with the best early production. Health and longevity of permanent trees is essential. Six pruning treatments were evaluated in five-tree plots using a randomized complete block design. Each treatment was replicated four times on the `Butte' and `Mission' almond cultivars. After six years, temporary trees receiving the least pruning had the highest yields. Permanent trees had lower yields since more pruning was done in the second through fourth dormant seasons to develop branch framework for the long term. `Butte' and `Mission' responses to treatment varied due to varietal growth habits. Effects on tree development and the need for later corrective pruning were noted. After four harvests, yields were greater with less pruning.
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McFadyen, Lisa, David Robertson, Stephen Morris, and Trevor Olesen. "Effects of Early Tree Training on Macadamia Production." HortTechnology 26, no. 6 (December 2016): 707–12. http://dx.doi.org/10.21273/horttech03479-16.

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The current industry recommendation for the training of young macadamia (Macadamia integrifolia, Macadamia tetraphylla, and hybrids) trees is to prune the trees to a central leader, but there is little science to support this recommendation. We planted an orchard to assess the merits of central leader training relative to a minimally pruned control. We used two cultivars, 246 and 816, representing spreading and upright growth habits, respectively. Training to a central leader reduced cumulative yields per tree over the first 3 years of production by 16% in ‘246’ and 23% in ‘816’. The reduction in yield was correlated with a reduction in the number of racemes per tree. The early training of the upright cultivar 816 appeared to improve its resistance to storm damage, but no such effect was seen in the more spreading cultivar 246. The yield penalty in training young trees to a central leader is such that industry should reconsider its early tree training recommendation.
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Campbell, JE, HI Nicol, and BR Cullis. "Effect of four different canopy shapes on apple yields." Australian Journal of Experimental Agriculture 36, no. 4 (1996): 489. http://dx.doi.org/10.1071/ea9960489.

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The cultivars, Jonathan, Delicious and Granny Smith apple (Malus domestica Borkh.) trees on MM.106, Northern Spy, Seedling and MM.102 rootstocks were trained as-vase, central leader, palmette and Hawkes Bay multi-leade; systems for 18 years. Rootstock significantly affected tree size, and there were interactions of rootstock with training systems or cultivars. There was also an interaction between training ' systems and cultivars. In the early years, while the training systems were being established, fruit yield was inversely related to the severity of the pruning; central leader- and palmette-trained trees had higher yields and tree efficiency than Hawkes Bay trees whose yields and tree efficiency were higher than vase trees. When yields reached maximum and the training systems became well established (after about 8 years of cropping), the total annual yield and tree efficiency per tree of individual training systems within a cultivar and rootstock differed only slightly. Cumulative yields of central leader, palmette and Hawkes Bay were higher than vase in the early years of all training systems and cultivars, while tree size was often smaller. In the latter years, cumulative yields of the central leader, palmette and Hawkes Bay systems remained slightly higher than vase, except with the less vigorous Jonathan and Granny Smith/ MM.102 combinations where yields were similar.
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Fallahi, Esmaeil, Bahar Fallahi, and Shahla Mahdavi. "Branch Configuration Impacts on Production, Fruit Quality, and Leaf Minerals of ‘Aztec Fuji’ Apple Trees in an Upright Single Row High-Density Orchard System Over Five Years." Journal of Agricultural Science 12, no. 4 (March 15, 2020): 53. http://dx.doi.org/10.5539/jas.v12n4p53.

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Tree architectures play a critical role in the productivity of high-density orchards, but limited information is available in this subject. We studied effects of three branch configurations on tree growth, yield components, fruit quality and leaf mineral nutrients in &lsquo;Aztec Fuji&rsquo; apple (Malus domestica Bork.) in a single row upright high-density system under southwest Idaho, USA conditions over 2012-2016. This study revealed that trees trained into a Tall Spindle (TS) had larger trunk cross sectional area (TCSA) than those with an Overlapped Arm (OA) system. Trees trained into a TS had higher number of fruit and yield per tree, three years after planting in 2012, than those with a Tipping Arm (TA) or OA system. However, in 2013, trees with a TA system had higher yield than those with a TS or OA configuration due to trees&rsquo; biennial bearing habit and higher spur formation in trees with a TA system. Trees receiving a TA training had lower biennial bearing index between all consecutive years. Trees with an OA training had smaller fruit than those with either a TA or TS training in all years between 2012-2016. Training systems did not have any effect on fruit color, soluble solids concentration, or starch degradation pattern at harvest. However, fruit from trees with an OA training had higher firmness and lower water core than those from trees with a TS or TA training. Leaves from trees receiving a TA training had greater leaf area, fresh weight, and potassium (K) and magnesium (Mn) concentrations than those with other trainings. Leaves from trees receiving an OA training had higher leaf iron (Fe), zinc (Zn), and copper (Cu) than those with a TS training. In this study, we concluded that training trees into a TA configuration rather than an OA system is recommended if the management and operation of apple production mandate the use of an &ldquo;upright wall&rdquo; structure to facilitate mechanical harvesting.
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Dissertations / Theses on the topic "Tree training"

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Teichmann, Markus. "Expressing Context-Free Tree Languages by Regular Tree Grammars." Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2017. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-224756.

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In this thesis, three methods are investigated to express context-free tree languages by regular tree grammars. The first method is a characterization. We show restrictions to context-free tree grammars such that, for each restricted context-free tree grammar, a regular tree grammar can be constructed that induces the same tree language. The other two methods are approximations. An arbitrary context-free tree language can be approximated by a regular tree grammar with a restricted pushdown storage. Furthermore, we approximate weighted context-free tree languages, induced by weighted linear nondeleting context-free tree grammars, by showing how to approximate optimal weights for weighted regular tree grammars.
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Gerber, Hein Jaco. "Tree training and managing complexity and yield in fig (Ficus carica L.)." Thesis, Stellenbosch : University of Stellenbosch, 2010. http://hdl.handle.net/10019.1/3184.

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Thesis (MscAgric (Horticulture))--University of Stellenbosch, 2010.
ENGLISH ABSTRACT: Commercial fig production with popular European cultivars, Bourjasotte Noire, Col de Damme Noire and Noire de Caromb, is new to the Western Cape. Little research on fig production has been conducted in South Africa and producers are struggling to implement effective commercial practices. In order to establish practices that will maximise yield of quality fruit, the most productive one-year-old shoot lengths were identified in a phenological study. All shoot length categories evaluated in ‘Bourjasotte Noire’ (10 – 15 cm, 25 – 40 cm, 50 – 65 cm, 75+ cm) yielded fruit and will probably yield well the following season. In ‘Col de Damme Noire’, shoots longer than 60 cm seem to be suited to reproduction, yet they might produce a poor yield the following season. Shoots 10 – 20 cm long in ‘Noire de Caromb’ are productive relative to their length, while shoots 30 – 50 cm and 60 – 80 cm long are also fairly productive. Shoots longer than 100 cm produced suitable shoot lengths for yield the following season. Two experiments were conducted on ‘Bourjasotte Noire’ and ‘Col de Damme Noire’ to establish the type (Experiment 1, different intensity heading cuts) and timing (Experiment 2) of pruning cuts required to stimulate the growth of shoots of the same length as the shoots selected to be optimal for yield in the phenology study, and to reduce the expression of distal branching. In ‘Bourjasotte Noire’, removing one third of the total length of one-year-old shoots on 21 July by heading stimulated the development of more growth and longer current season shoots compared to other treatments, while reducing yield slightly. Heading back to three nodes in ‘Col de Damme Noire’ stimulated the growth of current season shoots of the optimal length established in the phenology study, while heading cuts on 30 June produced the longest average current season shoot length in ‘Col de Damme Noire’. To further address the effects of distal branching (acrotony), an experiment was conducted to establish whether rest breaking agents (RBA’s) in combination with tip-pruning can increase tree complexity by improving bud break, and whether increased complexity would increase yield in all three cultivars. A second experiment was conducted to evaluate the effects of timing RBA applications on bud break and harvest scheduling. Lift® increased the number of buds breaking in ‘Bourjasotte Noire’, while in ‘Noire de Caromb’ Dormex® and oil increased bud break. Tip-pruning increased the average shoot length in ‘Bourjasotte Noire’ and ‘Col de Damme Noire’, while causing a reduction in the amount of new growth in ‘Noire de Caromb’. Lift® applied 3 August and Dormex® applied 30 June shortened the number of days to 50% bud break in ‘Bourjasotte Noire’ and ‘Col de Damme Noire’. Both Lift® and Dormex® applied on 30 June decreased the number of days to 50% bud break and 50% harvest of the breba crop in ‘Noire de Caromb’. These treatments increased the number of fruit in both the breba and main crop of ‘Noire de Caromb’, but reduced fruit size. In conclusion, different approaches with regards to pruning needs to be followed for each cultivar to establish or maintain the optimal shoots for reproduction, while RBA’s can be used to force earlier, increased- bud break and harvest of breba fruit.
AFRIKAANSE OPSOMMING: Kommersiele verbouing van drie Europese vykultivars, Bourjasotte Noire, Col de Damme Noire en Noire de Caromb is nuut tot die Wes-Kaap. Baie min navorsing oor die verbouing van vye is al in Suid-Afrika gedoen, met die gevolg dat produsente sukkel om effektiewe kommersiële verbouingspraktyke te implementeer. ‘n Fenologiese studie van die drie kultivars is uitgevoer om vas te stel wat die mees produktiewe een-jaar-oue lootlengte is, met die doel om die opbrengs van kwaliteit vrugte te maksimeer. Al vier kategorieë wat ge-evalueer is in ‘Bourjasotte Noire’ (10 – 15 cm, 25 – 40 cm, 50 – 65 cm, 75+ cm) is gevind om geskik te wees vir huidige en volgende seisoen opbrengs. Lote langer as 60 cm is geskik vir opbrengs in ‘Col de Damme Noire’ in die huidige seisoen, maar mag in die volgende seisoen swak presteer a.g.v. die gebrekkige lengte van nuwe lote wat daarop ontwikkel. In ‘Noire de Caromb’ is gevind dat lote 10 – 20 cm lank baie produktief is relatief tot hul lengte en dat lote 20 – 50 cm en 60 – 80 cm lank ook relatief produktief is. Lote langer as 100 cm was minder produktief, maar het nuwe lote gelewer wat geskik is vir opbrengs die volgende seisoen. Twee snoei eskperimente is uitgevoer op ‘Bourjasotte Noire’ en ‘Col de Damme Noire’ om vas te stel wat die mees geskikte tipe snoeisnit (Eksperiment 1, verskillende dieptes van topsnitte) en tydstip om te snoei (Eksperiment 2) is met die doel om lote te produseer soortgelyk in lengte aan die wat in die fenologie studie uitgewys is as die produktiefste, en om moontlik die voorkoms van “kaalnekke” te verminder. In ‘Bourjasotte Noire’ is gevind dat die wegsnoei van ‘n derde van die loot op 21 Julie aanleiding gee tot meer groei, langer een-jaar-oue lote en ‘n effense afname in opbrengs. Geskikte lote langer as 60 cm kan in ‘Col de Damme Noire’ verkry word deur lote te top sodat net drie nodes oorbly. Die uitvoer van topsnitte op 30 Junie het langer gemiddelde lootlengtes tot gevolg gehad. Om die probleem van “kaalnekke” (apikale dominansie) verder aan te spreek, is ‘n eksperiment uitgevoer om vas te stel of rusbreekmiddels gekombineerd met tip-snoei gebruik kan word om kompleksiteit te vermeerder deur knopbreek te verhoog, en indien wel, of dit sal aanleiding gee tot verhoogde opbrengs in al drie kultivars. ‘n Tweede eksperiment met verskillende toedieningstye van rusbreekmiddels is uitgevoer om vas te stel of oeste geskeduleer kan word. Lift® het knopbreek verhoog in ‘Bourjasotte Noire’, terwyl Dormex® en olie knopbreek verhoog het in ‘Noire de Caromb’. Tip-snoei het die gemiddelde lootlengtes verhoog in ‘Bourjasotte Noire’ en ‘Col de Damme Noire’, terwyl dit groei verminder het in ‘Noire de Caromb’. Lift® toediening op 3 Augustus en Dormex® toediening op 30 Junie het die aanvang van 50% knopbreek vervroeg in ‘Boujasotte Noire’ en ‘Col de Damme Noire’. Beide Lift® en Dormex® toediening op 30 Junie het die bereiking van 50% knopbreek- en 50% oes vervroeg in ‘Noire de Caromb’. Hierdie behandeling het ook die aantal vrugte van die breba- en hoofoes vermeerder, maar vruggrootte verminder. Verskillende snoeibenaderings behoort dus gevolg te word om vir elke kultivar die regte lootlengtes te genereer of te onderhou, terwyl rusbreekmiddels gebruik kan word om knopbreek te vervroeg en verhoog, en om die breba oes te vervroeg.
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Mesa, Juliani Karen <1982&gt. "Starch distribution in pear tree organs in relation to training systems, rootstocks and fruit quality." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2015. http://amsdottorato.unibo.it/7158/.

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Starch is the main form in which plants store carbohydrates reserves, both in terms of amounts and distribution among different plant species. Carbohydrates are direct products of photosynthetic activity, and it is well know that yield efficiency and production are directly correlated to the amount of carbohydrates synthesized and how these are distributed among vegetative and reproductive organs. Nowadays, in pear trees, due to the modernization of orchards, through the introduction of new rootstocks and the development of new training systems, the understanding and the development of new approaches regarding the distribution and storage of carbohydrates, are required. The objective of this research work was to study the behavior of carbohydrate reserves, mainly starch, in different pear tree organs and tissues: i.e., fruits, leaves, woody organs, roots and flower buds, at different physiological stages during the season. Starch in fruit is accumulated at early stages, and reached a maximum concentration during the middle phase of fruit development; after that, its degradation begins with a rise in soluble carbohydrates. Moreover, relationships between fruit starch degradation and different fruit traits, soluble sugars and organic acids were established. In woody organs and roots, an interconversion between starch and soluble carbohydrates was observed during the dormancy period that confirms its main function in supporting the growth and development of new tissues during the following spring. Factors as training systems, rootstocks, types of bearing wood, and their position on the canopy, influenced the concentrations of starch and soluble carbohydrates at different sampling dates. Also, environmental conditions and cultural practices must be considered to better explain these results. Thus, a deeper understanding of the dynamics of carbohydrates reserves within the plant could provide relevant information to improve several management practices to increase crop yield efficiency.
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DeGomez, Tom. "Training and Pruning Newly Planted Decidous Fruit Trees." College of Agriculture, University of Arizona (Tucson, AZ), 2015. http://hdl.handle.net/10150/559564.

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Training and pruning newly-planted deciduous fruit trees is one of the most important steps in developing trees with a strong framework (scaffold branches). Trees with a good framework of branches can support heavy crops without limb breakage and will help to bring the young tree into production at an early age. Selection and arrangement of these branches determines the type of development and growth in later years. The goal of pruning and training is to balance vegetative and fruiting wood growth.
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Belzer, Jessica A. "Unmanned Aircraft Systems in the National Airspace System: Establishing Equivalencyin Safety and Training Through a Fault Tree Analysis Approach." Ohio University / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1492778505498031.

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Prince, Jared. "Exploring the Effect of Different Numbers of Convolutional Filters and Training Loops on the Performance of AlphaZero." TopSCHOLAR®, 2018. https://digitalcommons.wku.edu/theses/3087.

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In this work, the algorithm used by AlphaZero is adapted for dots and boxes, a two-player game. This algorithm is explored using different numbers of convolutional filters and training loops, in order to better understand the effect these parameters have on the learning of the player. Different board sizes are also tested to compare these parameters in relation to game complexity. AlphaZero originated as a Go player using an algorithm which combines Monte Carlo tree search and convolutional neural networks. This novel approach, integrating a reinforcement learning method previously applied to Go (MCTS) with a supervised learning method (neural networks) led to a player which beat all its competitors.
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Dietze, Toni [Verfasser], Heiko [Akademischer Betreuer] Vogler, and Johanna [Gutachter] Björklund. "A Formal View on Training of Weighted Tree Automata by Likelihood-Driven State Splitting and Merging / Toni Dietze ; Gutachter: Johanna Björklund ; Betreuer: Heiko Vogler." Dresden : Technische Universität Dresden, 2019. http://d-nb.info/1226899870/34.

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Xia, Tian. "Learning to Rank Algorithms and Their Application in Machine Translation." Wright State University / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=wright1451610555.

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Davison, Elisabeth, and Tom DeGomez. "Pruning Deciduous Shade Trees." College of Agriculture, University of Arizona (Tucson, AZ), 2015. http://hdl.handle.net/10150/560971.

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Revised; Originally published:1999
6 pp.
The pruning principles discussed in this publication have proven to provide the best possible out comes including tree longevity and safety. Although trees may live for years following improper pruning their life span and safety may be severely reduced. We encourage proper pruning so that the trees we care for may bring us pleasure for many years.
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Castellanos, de Varona Maria Elena. "Cross-cultural training program." Theological Research Exchange Network (TREN), access this title online, 2001. http://dx.doi.org/10.2986/tren.108-0017.

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Books on the topic "Tree training"

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Berges, Amanda J. Training tree for riders. Loveland, CO: Alpine Publications, 2012.

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Wick, John. Walk with dick: The tree dog encyclopedia. [United States?]: John Wick, 1985.

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Wick, John. Walk with Wick: The tree dog encyclopedia. [United States: Westwick Pub., 2003.

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Jepson, Jeff. The tree climber's companion: A compact field reference and training manuel [sic] for tree climbers. Longville, MN (Rt. 1, Box 546, Longville 56655): J. Jepson, 1997.

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Johansson, Kicki. Planting trees: An illustrated technical guide and training manual. [New York]: United Nations Development Programme, 1993.

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Edwards, D. G. W. A training guide for laboratory analysis of forest tree seeds. Victoria, B.C: Pacific Forestry Centre, 1995.

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FAO/DANIDA Training Course on Forest Tree Improvement (1980 Mérida, Venezuela). Forest tree improvement: Report on the FAO/DANIDA Training Course on Forest Tree Improvement ; Mérida, Venezuela, January - February 1980. Rome: Food and Agriculture Organization of the United Nations, 1985.

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The illustrated practical encyclopedia of pruning, training & topiary: How to prune and train trees, shrubs, hedges, topiary, tree and soft fruit, climbers and roses. London: Lorenz, 2005.

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Nelson, William R. Response tree evaluation: Experimental assessment of an expert system for nuclear reactor operators. [Idaho Falls, Idaho]: EG&G Idaho, 1985.

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United States. President (1989-1993 : Bush). Proposed legislation: "National Tree Trust Act of 1990" : message from the President of the United States transmitting a legislative proposal to authorize the President to designate a private nonprofit Foundation as eligible to receive funds for the purpose of promoting community tree planting and cultivation projects ... to establish a rural tree planting program and a community tree planting program, and for other purposes. Washington: U.S. G.P.O., 1990.

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Book chapters on the topic "Tree training"

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Asadi, Nima, and Jimmy Lin. "Training Efficient Tree-Based Models for Document Ranking." In Lecture Notes in Computer Science, 146–57. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-36973-5_13.

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López De Luise, M. D., M. Soffer, and F. Spelanzon. "Improved Induction Tree Training for Automatic Lexical Categorization." In Advanced Techniques in Computing Sciences and Software Engineering, 51–53. Dordrecht: Springer Netherlands, 2009. http://dx.doi.org/10.1007/978-90-481-3660-5_9.

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Cervantes, Jair, Asdrúbal López, Farid García, and Adrián Trueba. "A Fast SVM Training Algorithm Based on a Decision Tree Data Filter." In Advances in Artificial Intelligence, 187–97. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-25324-9_16.

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Appice, Annalisa, Sonja Pravilovic, Donato Malerba, and Antonietta Lanza. "Sampling Training Data for Accurate Hyperspectral Image Classification via Tree-Based Spatial Clustering." In AI*IA 2017 Advances in Artificial Intelligence, 309–20. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-70169-1_23.

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Sutton-Charani, Nicolas, Sébastien Destercke, and Thierry Denœux. "Training and Evaluating Classifiers from Evidential Data: Application to E2M Decision Tree Pruning." In Belief Functions: Theory and Applications, 87–94. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-11191-9_10.

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Liu, Haozhe, Hongzhan Lin, and Guang Chen. "TANTP: Conversational Emotion Recognition Using Tree-Based Attention Networks with Transformer Pre-training." In Advances in Knowledge Discovery and Data Mining, 730–42. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-75765-6_58.

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Fang, Huang, Minhao Cheng, Cho-Jui Hsieh, and Michael Friedlander. "Fast Training for Large-Scale One-versus-All Linear Classifiers using Tree-Structured Initialization." In Proceedings of the 2019 SIAM International Conference on Data Mining, 280–88. Philadelphia, PA: Society for Industrial and Applied Mathematics, 2019. http://dx.doi.org/10.1137/1.9781611975673.32.

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Winter, Jerrold. "The Training Effect." In True Nutrition, True Fitness, 245–50. Totowa, NJ: Humana Press, 1991. http://dx.doi.org/10.1007/978-1-4612-0479-4_19.

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Cao, Qing-qing, and Wen-juan Huai. "Safety Risk Assessment and Management of Military Physical Fitness Training Based on Triangular Fuzzy Mathematics and Fault Tree Analysis." In IE&EM 2019, 94–100. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-4530-6_10.

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Benenson, Efim. "Diagnostic Training and Rheumatology Trees." In Rheumatology, 1–37. London: Springer London, 2011. http://dx.doi.org/10.1007/978-0-85729-240-7_1.

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Conference papers on the topic "Tree training"

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Karapinar, Zehra, Arafat Senturk, Sultan Zavrak, Resul Kara, and Pakize Erdogmus. "Binary apple tree: A game approach to tree traversal algorithms." In 2012 11th International Conference on Information Technology Based Higher Education and Training (ITHET). IEEE, 2012. http://dx.doi.org/10.1109/ithet.2012.6246026.

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Dalponte, Michele, Liviu Theodor Ene, Hans Ole Orka, Terje Gobakken, and Erik Naesset. "Unsupervised selection of training plots and trees for tree species classification." In IGARSS 2013 - 2013 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2013. http://dx.doi.org/10.1109/igarss.2013.6723225.

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Wen, Zeyi, Bingsheng He, Ramamohanarao Kotagiri, Shengliang Lu, and Jiashuai Shi. "Efficient Gradient Boosted Decision Tree Training on GPUs." In 2018 IEEE International Parallel and Distributed Processing Symposium (IPDPS). IEEE, 2018. http://dx.doi.org/10.1109/ipdps.2018.00033.

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Wong, Jeremy H. M., and Mark J. F. Gales. "Student-Teacher Training with Diverse Decision Tree Ensembles." In Interspeech 2017. ISCA: ISCA, 2017. http://dx.doi.org/10.21437/interspeech.2017-145.

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Dietterich, Thomas G., Adam Ashenfelter, and Yaroslav Bulatov. "Training conditional random fields via gradient tree boosting." In Twenty-first international conference. New York, New York, USA: ACM Press, 2004. http://dx.doi.org/10.1145/1015330.1015428.

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Choudhury, Rituparna, S. R. Ahamed, and Prithwijit Guha. "Efficient Hardware Implementation of Decision Tree Training Accelerator." In 2020 IEEE International Symposium on Smart Electronic Systems (iSES) (Formerly iNiS). IEEE, 2020. http://dx.doi.org/10.1109/ises50453.2020.00055.

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Robert, Ornprapa P., Chamnan Kumsap, and Sibsan Suksuchano. "Modeling realistic 3D trees using materials from field survey for terrain analysis of tactical training center." In THE 9TH INTERNATIONAL DEFENCE AND HOMELAND SECURITY SIMULATION WORKSHOP. CAL-TEK srl, 2019. http://dx.doi.org/10.46354/i3m.2019.dhss.006.

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This paper elaborates processes of modeling 3D trees for the simulation of the Army’s Tactical Training Center. The ultimate objective is to develop the 3D model database for inclusion to a game engine library. The adopted methodology includes collecting a forestry inventory for later 3D tree modeling in a Unity’s 3D Tree Modeler. Leaves and trunks were closely modeled using the data collected from the real site in the package SpeedTree modeler. Three tree types were sampled to demonstrate how close and realistic the adopted processes were to produce result 3D models for inclusion to the simulation of the tactical center. Visual comparison was made to show the final models. 3D scenes generated from the inclusion of the models were illustrated in comparison to the photo taken from the site. Further studies to adopt surface modeling data from UAV terrain mapping for tree canopies were recommended to verify photorealism of the processed 3D models.
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Sadasue, Tamon, and Tsuyoshi Isshiki. "Scalable Full Hardware Logic Architecture for Gradient Boosted Tree Training." In 2020 IEEE 28th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM). IEEE, 2020. http://dx.doi.org/10.1109/fccm48280.2020.00067.

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Ouzounis, G. K., and L. Gueguen. "Interactive collection of training samples from the Max-Tree structure." In 2011 18th IEEE International Conference on Image Processing (ICIP 2011). IEEE, 2011. http://dx.doi.org/10.1109/icip.2011.6115714.

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Kazama, Jun'ichi, and Kentaro Torisawa. "Speeding up training with tree kernels for node relation labeling." In the conference. Morristown, NJ, USA: Association for Computational Linguistics, 2005. http://dx.doi.org/10.3115/1220575.1220593.

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Reports on the topic "Tree training"

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Bonner, F. T., James A. Vozzo, W. W. Elam, and S. B. Land. Tree Seed Technology Training Course. New Orleans, LA: U.S. Department of Agriculture, Forest Service, Southern Forest Experiment Station, 1994. http://dx.doi.org/10.2737/so-gtr-107.

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Bonner, F. T., John A. Vozzo, W. W. Elam, and S. B. Land. Tree Seed Technology Training Course - Instructor's Manual. New Orleans, LA: U.S. Department of Agriculture, Forest Service, Southern Forest Experiment Station, 1994. http://dx.doi.org/10.2737/so-gtr-106.

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Abate, Gashaw Tadesse, Tanguy Bernard, Mekdim D. Regassa, and Bart Minten. Improving coffee productivity in Ethiopia: The impact of a coffee tree rejuvenation training program on stumping. Washington, DC: International Food Policy Research Institute, 2021. http://dx.doi.org/10.2499/p15738coll2.134408.

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PARSONS ENGINEERING SCIENCE INC DENVER CO. Treatability Study in Support of the Intrinsic Remediation Option at the Christmas Tree Fire Training Area at Westover Air Reserve Base Chicopee, Massachusetts. Fort Belvoir, VA: Defense Technical Information Center, January 1997. http://dx.doi.org/10.21236/ada343849.

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Contreras Salamanca, Luz Briyid, and Yon Garzón Ávila. Generational Lagging of Dignitaries, Main Cause of Technological Gaps in Community Leaders. Analysis of Generation X and Boomers from the Technology Acceptance Model. Universidad Nacional Abierta y a Distancia, May 2021. http://dx.doi.org/10.22490/ecacen.4709.

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Community and neighborhood organizations are in the process of renewing the organizational culture, considering technological environments in the way of training, and advancing communally, being competitive in adaptation and learning, creating new solutions, promoting change, and altering the status quo, based on the advancement of technology over the last few years, currently applied in most organizations. The decisive factor is the ability of true leaders to appropriate the Technological Acceptance Model –TAM– principles, participating in programs and projects, adopting new technologies from the different actors involved, contributing to the welfare of each community. There is, however, a relative resistance to the use of technology as support in community management, due to the generational differences in leaders and dignitaries, according to collected reports in this study, in relation to the age range of dignitaries –Generation X and Baby Boomers predominate–. They present a challenge to digital inclusion with difficulties related to age, cognitive, sensory, difficulty in developing skills, and abilities required in Digital Technologies, necessary to face new scenarios post-pandemic and, in general, the need to use technological facilities.
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Logger in training dies after being struck by a previously felled tree which rolled off of a bank in West Virginia. U.S. Department of Health and Human Services, Public Health Service, Centers for Disease Control and Prevention, National Institute for Occupational Safety and Health, March 2003. http://dx.doi.org/10.26616/nioshsface02wv040.

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West Virginia dozer operator dies after being struck-by a tree which was pushed over by the worker he was training. U.S. Department of Health and Human Services, Public Health Service, Centers for Disease Control and Prevention, National Institute for Occupational Safety and Health, July 2002. http://dx.doi.org/10.26616/nioshsface02wv009.

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