Academic literature on the topic 'Sorting machine'

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Journal articles on the topic "Sorting machine"

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Mamajanov, B., S. Abdurahmonov, and A. Shukuraliev. "Cotton seeds sorting with the help of dielectric calibration and sorting machines." Bulletin of Science and Practice 4, no. 3 (2018): 83–86. https://doi.org/10.5281/zenodo.1198030.

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In the article, it is planned to study the influence of the process of cottonseed separation on dielectric calibrating–sorting machines on their sowing properties. The main technological experiments were aimed at studying the effect of the operating voltage of a dielectric calibration and sorting machine on the quality of cottonseed separation and on determining the place of use of a dielectric calibration and sorting machine in cotton plant technological lines. For this, a comparative analysis of the technological circuits was carried out. The authors concluded that dielectric calibrati
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Prasad, Aashika, Gowtham M, Mohanraman S, and Suresh M. "Automatic Sorting Machine." International Research Journal of Multidisciplinary Technovation 2, no. 1 (2020): 7–12. http://dx.doi.org/10.34256/irjmt2102.

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Businesses around the world automate their outbound profiling and sortation process for an increased productivity. Sorting plays a key role in any industrial automation, particularly in the field of packaging industries. This paper aims at providing significant low-cost automation in packaging industries that calls for sorting and how the implication of pneumatics can yield a desirable solution. The prototype of the automatic sorting machine allows a systematic sorting of the carton boxes corresponding to their sizes using a pneumatic system, which is achieved by using pneumatic cylinders and
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Chen, Anzhi. "Examination of an Image Identification System for Agricultural Machines Based on Machine Vision." Journal of Combinatorial Mathematics and Combinatorial Computing 119, no. 1 (2024): 143–52. http://dx.doi.org/10.61091/jcmcc119-15.

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As computer and mechanical automation technologies advance, machine vision-based non-destructive testing technology finds use in a multitude of domains. Non-destructive testing technologies can be used on apple sorting equipment to decrease apple damage while simultaneously increasing sorting efficiency. As a result, the apple sorting machine’s image identification system now incorporates machine vision technology. The automatic classification of apple grades is accomplished by gathering, processing, extracting, and computing the contour features of apple photographs using preset sorting level
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Umurzakov, Akramjon, Тalibjan Sabirjanov, Kamoliddin Okyulov, and Kodir Gaparov. "Determination of the optimal amplitude of vibration behavior in the potato sorting machine." E3S Web of Conferences 538 (2024): 01005. http://dx.doi.org/10.1051/e3sconf/202453801005.

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This article is about potato feather sorting machines. There are mechanical and automatic types of potato sorting machines. In turn, there are types of mechanical potato sorting machines in drum, conveyor, roller and sieve types. While automatic sorting machines have laser, ultrotovushli, rengenli, video visual, spectral and optical intelligent sorting machines. Among mechanical sorting machines, vibration sieve-type devices stand out, with simplicity of construction and high performance. Vibration movement in the sorting machine of potato tugs, the working device of which is sieve type, accel
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Sugiyama, Masao. "Automatic Sheet Sorting Machine." JAPAN TAPPI JOURNAL 52, no. 1 (1998): 88–93. http://dx.doi.org/10.2524/jtappij.52.88.

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Ziqiang, Duan. "Tomato Sorting Machine Design." Journal of Engineering Research and Reports 26, no. 11 (2024): 215–21. http://dx.doi.org/10.9734/jerr/2024/v26i111326.

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This design is based on the existing fruit sorting mechanism, and the sorting mechanism has been improved by using a spiral roller to design a tomato sorting machine. Based on the size of tomatoes, this tomato sorter can classify tomatoes into three categories to meet the needs of different occasions for different sizes of tomatoes, improve the utilization rate of tomatoes, and also speed up the rate of tomato sorting. The threads on the outer layer of the drum push the tomatoes forward while the drum rotates, and the tomatoes fall through the corresponding drum gaps to complete this sorting s
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Miroshnychenko, Yevhen, Wolfgang Alt, Igor Dotsenko, et al. "An atom-sorting machine." Nature 442, no. 7099 (2006): 151. http://dx.doi.org/10.1038/442151a.

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PROF., TAWARE O. H., AJAY VYANKAT DEOKAR, AMOL KRISHNA GHORPADE, and MAYUR GANPAT GHORPADE. "AUTOMATIC FRUIT SORTING MACHINE." JournalNX - A Multidisciplinary Peer Reviewed Journal 3, no. 5 (2017): 60–62. https://doi.org/10.5281/zenodo.1446388.

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The objectives of this study involve the optimize process of sorting machine for a spherical fruits .fruits are today sorted with low efficiency in any country. Thus we innovative fruit sorting machine. With the help of gravity this fruits fall downward in machine. The main objective of this machine is help to farmer for minimize time of fruit sorting and reach market at proper time. https://journalnx.com/
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Bahadirov, G., B. Umarov, N. Obidov, S. Tashpulatov, and D. Tashpulatov. "Justification of the geometric dimensions of drum sorting machine." IOP Conference Series: Earth and Environmental Science 937, no. 3 (2021): 032043. http://dx.doi.org/10.1088/1755-1315/937/3/032043.

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Abstract This article presents the results of research to determine the basic geometric dimensions of a drum sorting machine designed for potato sorting. A critical analysis of the current situation in this area has been carried out. A number of research works have been studied aimed at developing special methods to reduce manual labour and improve the quality of sizing and sorting potatoes. At the same time, it is important to sort by size with a low level of product damage, with high productivity. Known mechanical and robotic machines used for sorting potatoes: roller, drum, conveyor (belt)
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Elkaoud, Nabil S. M., and Ragab K. Mahmoud. "Design and implementation of sequential fruit size sorting machine." Revista Brasileira de Engenharia Agrícola e Ambiental 26, no. 10 (2022): 722–28. http://dx.doi.org/10.1590/1807-1929/agriambi.v26n10p722-728.

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ABSTRACT This study aimed to develop a simple and easy to construct fruits size sorting machine. The sorting machine was designed to sort oranges, apples, and yellow plums in small, medium, large, and extra-large size groups based on physical and mechanical properties including axial dimensions, arithmetic mean diameter, sphericity, mass, volume, projected area, and frictional characteristics (coefficient of static friction) against two structural surfaces of the sorting machine (galvanized iron and rubber). The maximum sorting efficiency of the machine was 98% at 20 rpm for plums. Whereas the
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Dissertations / Theses on the topic "Sorting machine"

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Miroshnychenko, Yevhen. "An atom sorting machine." [S.l.] : [s.n.], 2006. http://deposit.ddb.de/cgi-bin/dokserv?idn=98096489X.

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Chang, Michelle Sueway. "Design of an automated sorting and orienting machine for electronic pins." Thesis, Massachusetts Institute of Technology, 2012. http://hdl.handle.net/1721.1/78162.

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Thesis (M. Eng. in Manufacturing)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2012.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (p. 93-94).<br>At the power electronics manufacturer SynQor, the printed circuit board (PCB) assembly line is fully automated with the exception of the step which inserts electronic pins into the PCBs. Past attempts to automate this process have resulted in two unreliable machines that are not in use on the production line. Thus, electronic pin insertion is currently a manual process. The design proposed
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Alkhaldi, Hashem. "Contact investigations of granular mechanical media in a tumbling sorting machine." [S.l. : s.n.], 2007. http://nbn-resolving.de/urn:nbn:de:bsz:93-opus-31752.

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Guo, Haipeng. "Algorithm selection for sorting and probabilistic inference : a machine learning-based approach /." Search for this dissertation online, 2003. http://wwwlib.umi.com/cr/ksu/main.

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Duman, Asli. "Multiple Criteria Sorting Methods Based On Support Vector Machines." Master's thesis, METU, 2010. http://etd.lib.metu.edu.tr/upload/12612863/index.pdf.

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This study addresses sorting problems with predefined ordinal classes. We develop a new method based on Support Vector Machine (SVM) model, which is mainly used for nominal binary or multi-class classification processes. In the proposed method, the SVM model is extended to include the preferences of the decision maker and the ordinal relationship between classes in sorting problems. New sets of constraints are added to the SVM model. We demonstrate the performance of the proposed method through several data sets. We compare the results with those of classical SVM model and UTADIS method, a wel
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Simard, Carole. "Relational algebra on a parallel-sort database machine." Thesis, McGill University, 1985. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=63225.

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Richardson, Mathews Sears. "A system for continuous sampling of bioaerosols generated by a postal sorting machine." Texas A&M University, 2003. http://hdl.handle.net/1969.1/1210.

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In this study, a system for the collection of bioaerosols emitted from the mail sorting process was designed and characterized. Two different wetted-wall cyclones, the JBPDS cyclone and the glass cyclone sampler (GCS), were evaluated as system collection devices. These devices operate at 780 L/min and have a D50 of ~ 1 μm. A trimming impactor with a D50 of 10 μm was used upstream of the collection devices. Using two reference probes, the cyclone liquid outputs were compared with aerosol collected on filters and the output of an Aerosol-to-Hydrosol Transfer Stage (AHTS). The mass emission rate
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Alkhaldi, Hashem [Verfasser]. "Contact Investigations of Granular Mechanical Media in a Tumbling Sorting Machine / Hashem Alkhaldi." Aachen : Shaker, 2007. http://d-nb.info/116651109X/34.

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Valeri, Nicolò. "Virtual Commissioning of a sorting system of an automatic machine for paper roll packaging." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021.

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What is happening nowadays is, in all respects, a great industrial revolution, which has radically changed the manufacturing industry sector. The complexity of modern production plants is constantly growing, and the continuous technological progress places an enormous effort on the shoulders of manufacturers to satisfy the requirements set by an increasingly competitive market. Today the validation and testing of an automation system is a demanding task, usually performed in very tight deadlines. Therefore, the use of simulations to verify the automation system early in the design phase can be
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Ben, Qingyan. "Flight Sorting Algorithm Based on Users’ Behaviour." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-294132.

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The model predicts the best flight order and recommend best flight to users. The thesis could be divided into the following three parts: Feature choosing, data-preprocessing, and various algorithms experiment. For feature choosing, besides the original information of flight itself, we add the user’s selection status into our model, which the flight class is, together with children or not. In the data preprocessing stage, data cleaning is used to process incomplete and repeated data. Then a normalization method removes the noise in the data. After various balancing processing, the class-imbalan
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Books on the topic "Sorting machine"

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Spring, Joel H. The sorting machine revisited: National educational policy since 1945. Longman, 1989.

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Barkus, Philip. How to prepare for the postal distribution (machine) clerk examination (letter-sorting machine operator). Barron's, 1986.

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Research Institute for Advanced Computer Science (U.S.), ed. A fast sorting algorithm for a hypersonic rarefied flow particle simulation on the connection machine. Research Institute for Advanced Computer Science, NASA Ames Research Center, 1989.

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Barkus, Philip. How to prepare for the postal distribution (machine) clerk examination (letter-sorting machine operator): By Philip Barkus. 2nd ed. Barron's Educational Series, 1992.

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Canada. Dept. of Fisheries and Oceans. Report on the Development of an Automated Fish Sorting System Using Machine Vision. s.n, 1988.

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Canada. Dept. of Fisheries and Oceans. Dry and wet testing of an automated fish sorting system which uses machine vision. s.n, 1988.

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Spring, Joel H. The Sorting Machine Revisited: National Educational Policy Since 1945. Longman Group United Kingdom, 1988.

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Digest, Federal Jobs. U.S. Postal Exam Test 470 for City Carrier, Clerk, Distribution Clerk, Flat Sorting Machine Operator, Mail Handler, Mail Processor, Mark Up Clerk (Hom). Breakthrough Pubns, 1993.

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Gries, Stefan Th. Data in Construction Grammar. Edited by Thomas Hoffmann and Graeme Trousdale. Oxford University Press, 2013. http://dx.doi.org/10.1093/oxfordhb/9780195396683.013.0006.

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This chapter examines the types of data used in constructionist approaches and the parameters along which data types can be classified. It discusses different kinds of quantitative observational/corpus data (frequencies, probabilities, association measures) and their statistical analysis. In addition, it provides a survey of a variety of different experimental data (novel word/construction learning, priming, sorting, etc.). Finally, the chapter discusses computational-linguistic/machine-learning methods as well as new directions for the development of new data and methods in Construction Gramm
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Mau, Steffen, and Nicola Barfoot. Sorting Machines: The Reinvention of the Border in the 21st Century. Polity Press, 2022.

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Book chapters on the topic "Sorting machine"

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Seng, Ng Weng, and Ahmad Shahrizan Abdul Ghani. "Vision Based Smart Sorting Machine." In Lecture Notes in Mechanical Engineering. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-8323-6_2.

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Rajaram, Shyamsundar, Ashutosh Garg, Xiang Sean Zhou, and Thomas S. Huang. "Classification Approach towards Ranking and Sorting Problems." In Machine Learning: ECML 2003. Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-39857-8_28.

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Zheng, Pengfei, Jingjing Lou, Qingdong Luo, Xiyuan Wan, and Yuntong Wang. "A Mango Sorting Method Based on Machine Vision." In Mechanisms and Machine Science. Springer Nature Switzerland, 2024. https://doi.org/10.1007/978-3-031-77489-8_55.

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Luo, Qingdong, Xiyuan Wan, Jingjing Lou, and Pengfei Zheng. "Machine Vision-Based Integrated Sorting System for Loquat." In Mechanisms and Machine Science. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-81673-4_43.

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Chan, Tyson, Jacky H. Cai, Francis Chen, and Ka C. Chan. "Self-sorting of Solid Waste Using Machine Learning." In Advances in Computational Collective Intelligence. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-63119-2_5.

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Arun Kumar, R., and Vijay S. Rajpurohit. "Wavelet Features for Pomegranate Sorting Using Machine Vision." In Innovations in Computer Science and Engineering. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-8201-6_20.

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Zhongzhi, Han. "A Carrot Sorting System Using Machine Vision Technique." In Computer Vision-Based Agriculture Engineering. CRC Press, 2019. http://dx.doi.org/10.1201/9780429289460-14.

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Deb, Kiron, Shobhin Basu, Vamshi Krishna Palakurthy, and Nabarun Bhattacharyya. "Accelerated Sorting of Apples Based on Machine Learning." In Smart Computing Techniques and Applications. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-0878-0_75.

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Devendra Kumar, S. M., S. Prashanth, and Rani Medhashree. "Automatic Plastic Sorting Machine Using Audio Wave Signal." In Lecture Notes in Mechanical Engineering. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-8542-5_98.

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Jin, Xiaoping, Zheng Guo, Ning Jin, and Zhengquan Li. "Probabilistic Sorting Memory Constrained Tree Search Algorithm for MIMO System." In Machine Learning and Intelligent Communications. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-00557-3_41.

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Conference papers on the topic "Sorting machine"

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Laohapensaeng, Teeravisit, Budsaya Laohapensaeng, and Suppakarn Chansareewittaya. "The Tomato Sorting Machine." In 2024 8th International Conference on Information Technology (InCIT). IEEE, 2024. https://doi.org/10.1109/incit63192.2024.10810518.

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Perumal, P., B. Mathivanan, and K. Deepa. "Color based Product Sorting Machine using Raspberry Pi." In 2024 5th International Conference on Smart Electronics and Communication (ICOSEC). IEEE, 2024. http://dx.doi.org/10.1109/icosec61587.2024.10722515.

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Xiong, Zihui. "Automatic sorting system based on image classification." In Third International Conference on Machine Vision, Automatic Identification and Detection, edited by Renchao Jin. SPIE, 2024. http://dx.doi.org/10.1117/12.3036414.

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Ala’Anzy, Mohammed Alaa, Zhanar Mazhit, Alaa Fadhil Ala’Anzy, Abdulmohsen Algarni, Ramis Akhmedov, and Abdiyev Bauyrzhan. "Comparative Analysis of Sorting Algorithms: A Review." In 2024 11th International Conference on Soft Computing & Machine Intelligence (ISCMI). IEEE, 2024. https://doi.org/10.1109/iscmi63661.2024.10851593.

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Li, Hongming, Ye Ding, and Mingyu Shao. "Machine vision-based sorting method for precision industrial components." In 2024 International Conference on Computer Vision, Robotics and Automation Engineering, edited by Qiang Cheng and Lei Chen. SPIE, 2024. http://dx.doi.org/10.1117/12.3041660.

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Chen, Jianyu, Jiapei Wu, Binshuo Chen, et al. "An OpenMV-Based Intelligent Manipulator For Pill Sorting." In 2024 International Conference on Image Processing, Computer Vision and Machine Learning (ICICML). IEEE, 2024. https://doi.org/10.1109/icicml63543.2024.10957908.

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Catacutan, Issaiah Neil T., Symon S. Lee, Mari Grazela P. Legarda, Diony S. Abando, Vivien A. Agustin, and Ariel Antwaun Rolando C. Sison. "BINSIGHT: Waste Sorting Enhanced with Machine Learning and Reward System." In 2024 8th International Symposium on Innovative Approaches in Smart Technologies (ISAS). IEEE, 2024. https://doi.org/10.1109/isas64331.2024.10845356.

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Tian, Zhiwei, Ruliang Qian, and Boyuan Sun. "Research on Logistics Sorting Volume Prediction Based on Machine Learning." In 2024 IEEE 6th International Conference on Power, Intelligent Computing and Systems (ICPICS). IEEE, 2024. https://doi.org/10.1109/icpics62053.2024.10797061.

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Guo, Chuanjing. "Design of material sorting control system based on machine vision." In Fifth International Conference on Telecommunications, Optics, and Computer Science, edited by Witold Pedrycz and Sos S. Agaian. SPIE, 2025. https://doi.org/10.1117/12.3067356.

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Fu, Qingyu, Hao Yan, Zhe He, Wenyao Li, Wenjing Zang, and Cheng Zhu. "Research and Design of Machine Vision-based Workpiece Defect Sorting Robot." In 2024 International Conference on Intelligent Computing and Robotics (ICICR). IEEE, 2024. http://dx.doi.org/10.1109/icicr61203.2024.00046.

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Reports on the topic "Sorting machine"

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Searcy, Stephen, Uri Peiper, and Ron Feller. Sorting Carrots with Machine Vision Inspection. United States Department of Agriculture, 1991. http://dx.doi.org/10.32747/1991.7599655.bard.

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Delwiche, Michael, Yael Edan, and Yoav Sarig. An Inspection System for Sorting Fruit with Machine Vision. United States Department of Agriculture, 1996. http://dx.doi.org/10.32747/1996.7612831.bard.

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Concepts for real-time grading of fruits and vegetables were developed, including multi-spectral imaging with structured illumination to detect and distinguish surface defects from concavities. Based on these concepts, a single-lane conveyor and inspection system were designed and evaluated. Image processing algorithms were developed to inspect and grade large quasi-spherical fruits (peaches and apples) and smaller dried fruits (dates). Adjusting defect pixel thresholds to achieve a 25% error rate on good apples, classification errors for bruise, crack, and cut classes were 51%, 42%, and 46%,
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Searcy, Stephen W., and Kalman Peleg. Adaptive Sorting of Fresh Produce. United States Department of Agriculture, 1993. http://dx.doi.org/10.32747/1993.7568747.bard.

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This project includes two main parts: Development of a “Selective Wavelength Imaging Sensor” and an “Adaptive Classifiery System” for adaptive imaging and sorting of agricultural products respectively. Three different technologies were investigated for building a selectable wavelength imaging sensor: diffraction gratings, tunable filters and linear variable filters. Each technology was analyzed and evaluated as the basis for implementing the adaptive sensor. Acousto optic tunable filters were found to be most suitable for the selective wavelength imaging sensor. Consequently, a selectable wave
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Engel, Bernard, Yael Edan, James Simon, Hanoch Pasternak, and Shimon Edelman. Neural Networks for Quality Sorting of Agricultural Produce. United States Department of Agriculture, 1996. http://dx.doi.org/10.32747/1996.7613033.bard.

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The objectives of this project were to develop procedures and models, based on neural networks, for quality sorting of agricultural produce. Two research teams, one in Purdue University and the other in Israel, coordinated their research efforts on different aspects of each objective utilizing both melons and tomatoes as case studies. At Purdue: An expert system was developed to measure variances in human grading. Data were acquired from eight sensors: vision, two firmness sensors (destructive and nondestructive), chlorophyll from fluorescence, color sensor, electronic sniffer for odor detecti
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Galili, Naftali, Roger P. Rohrbach, Itzhak Shmulevich, Yoram Fuchs, and Giora Zauberman. Non-Destructive Quality Sensing of High-Value Agricultural Commodities Through Response Analysis. United States Department of Agriculture, 1994. http://dx.doi.org/10.32747/1994.7570549.bard.

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The objectives of this project were to develop nondestructive methods for detection of internal properties and firmness of fruits and vegetables. One method was based on a soft piezoelectric film transducer developed in the Technion, for analysis of fruit response to low-energy excitation. The second method was a dot-matrix piezoelectric transducer of North Carolina State University, developed for contact-pressure analysis of fruit during impact. Two research teams, one in Israel and the other in North Carolina, coordinated their research effort according to the specific objectives of the proj
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Health hazard evaluation report: HETA-2008-0293-3132, ergonomic evaluation of automatic flat sorting machines - Colorado. U.S. Department of Health and Human Services, Public Health Service, Centers for Disease Control and Prevention, National Institute for Occupational Safety and Health, 2011. http://dx.doi.org/10.26616/nioshheta200802933132.

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