Glaucoma Detection Using Image Channels and Discrete Wavelet Transform

Kirar, Bhupendra Singh; Agrawal, Dheeraj; Kirar, Seema

doi:10.1080/03772063.2020.1795934

Cited by 24 publications

(10 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Değirmencioğlu et al [30] also reported that supplementation of 30 g cumin seeds significantly (P < 0.01) increased mean daily milk production (0.85 kg) in Anatolian water buffaloes (Table 3). In these studies, CS and FS supplementation did not affect milk composition of buffalo and this result complies with the other studies [28,32] who reported that differences in SNF, protein and fat contents of buffalo milk fed ration supplemented with SC were not significant (Tables 4 and 5). Conversely, [25] showed that milk protein contents were significantly (P < 0.05) affected by CS supplementation.…”

Section: The Effects On Milk Productionsupporting

confidence: 92%

“…They have also proved their worth as component of herbal preparation to improve the lactation performance and health of dairy buffalo [29] found an improvement in milk yield (0.67 kg/day) through supplementation of grounded FS (50 g/kg in concentrate) in Anatolian water buffaloes (Table 2). Other researchers [28,32], like showed that supplementation of fenugreek seeds (100 g/day) and (% 1.5) on lactating Murrah buffaloes and surti buffaloes resulted in a increase in milk production although nonsignificant, no change in milk composition (Tables 4 and 5). With the progress of experiment, there appeared an improvement in the daily milk yield due to supplementation of soaked fenugreek seeds at both the dosage level.…”

Section: The Effects On Milk Productionmentioning

confidence: 84%

“…In another study, Kirar et al [32] 12 lactating Murrah buffaloes of 1st to3 parity were randomly selected and distributed into two different groups with six animals in each group. Animals in Group I were control without any supplementation and in Group II were supplemented with soaked fenugreek seeds 50 g per animal per day (Table 4) [32].…”

Section: Concentrate Feed Mixture (Cfm)mentioning

confidence: 99%

See 2 more Smart Citations

Use of Aromatic Seeds as Feed Additives to Improve the Production of Anatolian Water Buffaloes

Degirmencioglu¹

2021

Advanced Studies in the 21st Century Animal Nutrition

View full text Add to dashboard Cite

Buffaloes have a strong population of rumen microorganisms that can utilize different feeds. Other features that make this animal unique are its compatibility with nature, its ability to withstand difficulties, and the nutrient richness of animal products. Today, the emergence of residues such as animal origin diseases, pesticides and antibiotics in animal food products has led organic products to be preferred more by consumers. Due to the increase in consumption demand of natural products, the share of buffalo products in the world market is gradually increasing. Focusing on the use of natural additives in buffalo feeding is important for the diversity of healthy products. Examples of natural additives are cumin and fenugreek seeds. In addition to being natural products, these seeds are reported to have versatile functions in the animal body. The purpose of this chapter is to show how to use aromatic seeds as feed additives in the feeding of Anatolian water buffaloes. The chapter also includes various articles on the use of aromatic seeds in buffalo rations in international fields. This review focuses on the current research relating to the use of aromatic seeds as feed additives to improve the production of Anatolian water buffaloes. Based on the scientific results presented in this chapter, authors drew the following main conclusions: (1) The use of aromatic seeds as feed additives of Anatolian water buffaloes feeding enabled in enhancing milk production, without changing the taste and chemical composition of the milk. (2) Milk production can be improved up to 0.67 kg and 0.85 kg day-1 by adding 50 g Fenugreek seeds and 30 g Cumin seeds to the ration of buffaloes in the early lactation period. (3) The use of aromatic seeds in the feeding of water buffaloes has been proven therefore, their use in the buffalo sector should be encouraged.

show abstract

Section: The Effects On Milk Productionsupporting

confidence: 92%

Section: The Effects On Milk Productionmentioning

confidence: 84%

Section: Concentrate Feed Mixture (Cfm)mentioning

confidence: 99%

See 1 more Smart Citation

Use of Aromatic Seeds as Feed Additives to Improve the Production of Anatolian Water Buffaloes

Degirmencioglu¹

2021

Advanced Studies in the 21st Century Animal Nutrition

View full text Add to dashboard Cite

show abstract

“…The automated glaucoma CNN (AG-CNN) was used to classify the normal image as well as glaucoma infected image. Glaucoma detection used image channels (ICs) as well as the discrete wavelet transform (DWT) for the fundus image was suggested by Kirar BS et al [14]. Images were resized to the red channel, blue channel, green channel, and grayscale images, and CLAHE was used on ICs to eradicate the unnecessary lighting effect and improving image visibility.…”

Section: Related Workmentioning

confidence: 99%

“…The resized images are employed to extract the green channel, red channel, blue channel and grayscale images [30]. The fundus image consists of RGB color as shown in Fig 2 . The Pseudocode color representation is utilized to distinguish all the information channels more accurately.…”

Section: Image Extractionmentioning

confidence: 99%

FGS-HDNN: Fractional Gravitational Search based Hybrid Deep Neural Network for Glaucoma Detection using Fundus Images

Madhumalini

Devi

2021

Preprint

View full text Add to dashboard Cite

Glaucoma is a retinal disease that damages the eye's optic nerve, frequently causing an irreversible loss of vision. However, the accurate diagnosis of this disease is difficult but early-stage diagnosis may cure this retinal disease. The objective of this research is to diagnose glaucoma disease in the top of the eye's optical nerve. The proposed approach detects glaucoma via four major steps namely Data enhancement phase, segmentation phase, feature extraction phase, and classification phase by the fractional gravitational search-based hybrid deep neural network (FGSA-HDNN) classifier. The proposed classifier is used for the exact classification of glaucoma infected images and normal images. Here, the proposed approach utilizes the statistical, textural, and vessel features from the segmented output. Also, the proposed FGSO algorithm is used for testing the deep neural network. From the experimental results, it is observed that the proposed glaucoma detection has obtained a sensitivity of 99.64%, a specificity of 97.84%, and an accuracy of 98.75% that outperforms other state-of-art methods.

show abstract

Emperor penguin optimization algorithm- and bacterial foraging optimization algorithm-based novel feature selection approach for glaucoma classification from fundus images

et al. 2023

View full text Add to dashboard Cite

Glaucoma Detection Using Image Channels and Discrete Wavelet Transform

Cited by 24 publications

References 20 publications

Use of Aromatic Seeds as Feed Additives to Improve the Production of Anatolian Water Buffaloes

Use of Aromatic Seeds as Feed Additives to Improve the Production of Anatolian Water Buffaloes

FGS-HDNN: Fractional Gravitational Search based Hybrid Deep Neural Network for Glaucoma Detection using Fundus Images

Emperor penguin optimization algorithm- and bacterial foraging optimization algorithm-based novel feature selection approach for glaucoma classification from fundus images

Contact Info

Product

Resources

About