A Novel Growth Evaluation System for Tobacco Planting Based on Image Classification

2019 ◽  
Vol 23 (6) ◽  
pp. 1004-1011
Author(s):  
Yonghua Xiong ◽  
Shuangqing Yu ◽  
◽  
Keyword(s):  
Image Processing ◽  
Image Classification ◽  
Mobile Application ◽  
Evaluation System ◽  
Mobile App ◽  
Growth Evaluation ◽  
Image Processing Algorithms ◽  
Processing Algorithms ◽  
The Web ◽  
Tobacco Growth

A novel growth evaluation system for tobacco planting (GESTP) based on a B/S architecture is introduced in this paper. It mainly consists of three parts: a mobile application (mobile app), a browser terminal and a server terminal. The GESTP system is used to evaluate the growth of tobacco and give farmers planting guidance instead them having to rely on personal judgment. Once the photos of the tobacco leaf and plant are uploaded to the web server via the mobile app or the browser terminal, the application program of the server terminal is called to process the tobacco images with image processing algorithms. The results including the grade of the tobacco growth and planting guidance will be provided to the client within a 2-second timeframe, which greatly help farmers understand the growth of tobacco and take planting measures. The running result indicates that the GESTP system provides an effective and straightforward way to evaluate the growth of tobacco and provides cultivation guidance to tobacco farmers.

scholarly journals Plataforma para apoio a modelagem de próteses com base em Processamento Digital de Imagens e Deep Learning

2021 ◽  
Author(s):  
Bianka Tallita Passos ◽  
Moira Cristina Cubas Fatiga Tillmann ◽  
Anita Maria da Rocha Fernandes
Keyword(s):  
Image Processing ◽  
Deep Learning ◽  
High Resolution ◽  
Image Classification ◽  
Digital Image Processing ◽  
Medical Practice ◽  
Digital Image ◽  
Image Processing Algorithms ◽  
Processing Algorithms ◽  
Specific Label

Medical practice in general, and dentistry in particular, generatesdata sources, such as high-resolution medical images and electronicmedical records. Digital image processing algorithms takeadvantage of the datasets, enabling the development of dental applicationssuch as tooth, caries, crown, prosthetic, dental implant, andendodontic treatment detection, as well as image classification. Thegoal of image classification is to comprehend it as a whole and classifythe image by assigning it to a specific label. This work presentsthe proposal of a tool that helps the dental prosthesis specialist toexchange information with the laboratory. The proposed solutionuses deep learning to classify image, in order to improve the understandingof the structure required for modeling the prosthesis. Theimage database used has a total of 1215 images. Of these, 60 wereseparated for testing. The prototype achieved 98.33% accuracy.

Otoconia perfect/imperfect crystals

1994 ◽  
Vol 52 ◽  
pp. 42-43
Author(s):  
César D. Fermin ◽  
Dale Martin
Keyword(s):  
Image Processing ◽  
Room Temperature ◽  
Phosphotungstic Acid ◽  
Gallus Domesticus ◽  
Crystal Matrix ◽  
Organic Templates ◽  
Image Processing Algorithms ◽  
Processing Algorithms ◽  
Diffraction Patterns

Otoconia of higher vertebrates are interesting biological crystals that display the diffraction patterns of perfect crystals (e.g., calcite for birds and mammal) when intact, but fail to produce a regular crystallographic pattern when fixed. Image processing of the fixed crystal matrix, which resembles the organic templates of teeth and bone, failed to clarify a paradox of biomineralization described by Mann. Recently, we suggested that inner ear otoconia crystals contain growth plates that run in different directions, and that the arrangement of the plates may contribute to the turning angles seen at the hexagonal faces of the crystals.Using image processing algorithms described earlier, and Fourier Transform function (2FFT) of BioScan Optimas®, we evaluated the patterns in the packing of the otoconia fibrils of newly hatched chicks (Gallus domesticus) inner ears. Animals were fixed in situ by perfusion of 1% phosphotungstic acid (PTA) at room temperature through the left ventricle, after intraperitoneal Nembutal (35mg/Kg) deep anesthesia. Negatives were made with a Hitachi H-7100 TEM at 50K-400K magnifications. The negatives were then placed on a light box, where images were filtered and transferred to a 35 mm camera as described.

Elastic Graph-based Semi-supervised Embedding with Adaptive Loss Regression

2020 ◽  
Keyword(s):  
Image Processing ◽  
International Symposium ◽  
Fast Track ◽  
Electronic Imaging ◽  
Image Processing Algorithms ◽  
Processing Algorithms

Fast track article for IS&T International Symposium on Electronic Imaging 2020: Image Processing: Algorithms and Systems proceedings.

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