Analysis of the Weibull Distribution Function

Chang, Kangkang

doi:10.1115/1.3162114

Cited by 4 publications

(1 citation statement)

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“…The proposed research assumes that the brightness distribution follows the Weibull distribution. The probability density function (pdf) of the Weibull distribution is provided by recognizing an image [31]. In the suggested work, the plant's redgreen-blue (RGB) picture is first transformed into a hue-saturation-value (HSV) image.…”

Section: Image Enhancementmentioning

confidence: 99%

A Hybrid Approach for Plant Disease Detection Using E-GAN and CapsNet

Vasudevan¹,

Karthick²

2023

Computer Systems Science and Engineering

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Crop protection is a great obstacle to food safety, with crop diseases being one of the most serious issues. Plant diseases diminish the quality of crop yield. To detect disease spots on grape leaves, deep learning technology might be employed. On the other hand, the precision and efficiency of identification remain issues. The quantity of images of ill leaves taken from plants is often uneven. With an uneven collection and few images, spotting disease is hard. The plant leaves dataset needs to be expanded to detect illness accurately. A novel hybrid technique employing segmentation, augmentation, and a capsule neural network (CapsNet) is used in this paper to tackle these challenges. The proposed method involves three phases. First, a graph-based technique extracts leaf area from a plant image. The second step expands the dataset using an Efficient Generative Adversarial Network E-GAN. Third, a CapsNet identifies the illness and stage.The proposed work has experimented on real-time grape leaf images which are captured using an SD1000 camera and PlantVillage grape leaf datasets. The proposed method achieves an effective classification of accuracy for disease type and disease stages detection compared to other existing models.

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Section: Image Enhancementmentioning

confidence: 99%

A Hybrid Approach for Plant Disease Detection Using E-GAN and CapsNet

Vasudevan¹,

Karthick²

2023

Computer Systems Science and Engineering

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Effect of Thermocycling on Flexural Strength and Weibull Statistics of Machinable Glass–Ceramic and Composite Resin

Peampring

Sanohkan

2013

J Indian Prosthodont Soc

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To evaluate the durability of machinable dental restorative materials, this study performed an experiment to evaluate the flexural strength and Weibull statistics of a machinable lithium disilicate glass-ceramic and a machinable composite resin after being thermocycled for certain cycles. A total of 40 bar-shape specimens of were prepared with the dimension of 20 mm × 4 mm × 2 mm, which were divided into four groups of 10 specimens. Ten specimens of machinable lithium disilicate glass-ceramic (IPS e.max CAD, Ivoclar Vivadent, Liechtenstein) and 10 specimens of machinable composite resin (Paradigm MZ 100, 3M ESPE, USA) were subjected to 3-point flexural strength test. Other 10 specimens of each material were thermocycled between water temperature of 5 and 55 °C for 10,000 cycles. After that, they were tested using 3-point flexural strength test. Statistical analysis was performed using two-way analysis of variance and Tukey multiple comparisons. Weibull analysis was performed to evaluate the reliability of the strength. Means of strength and their standard deviation were: thermocycled IPS e.max CAD 389.10 (50.75), non-thermocycled IPS e.max CAD 349.96 (38.34), thermocycled Paradigm MZ 100 157.51 (12.85), non-thermocycled Paradigm MZ 100 153.33 (19.97). Within each material group, there was no significant difference in flexural strength between thermocycled and non-thermocycled specimens. Considering the Weibull analysis, there was no statistical difference of Weibull modulus in all experimental groups. Within the limitation of this study, the results showed that there was no significant effect of themocycling on flexural strength and Weibull modulus of a machinable glass-ceramic and a machinable composite resin.

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