Search Results - "Sharp PF"

ADRGS: an automatic diabetic retinopathy grading system through machine learning.

Authors: Devi, Y. Aruna Suhasini Chari, K. Manjunatha

Source: Multimedia Tools & Applications; Jul2025, Vol. 84 Issue 24, p28467-28491, 25p

Multimodal imaging in neuro-ophthalmology.

Authors: Kumar, Mahesh Shah, Krutin Saravanan, Veerappan R et al.

Source: Indian Journal of Ophthalmology. Aug2026, Vol. 74 Issue 8, p1129-1150. 22p.

Cobalt‐Induced Strong Anharmonicity Coupled With Hierarchical Defect and Band Structure Engineering for Enhanced n‐ and p‐Type Thermoelectric Performance in ZrFe0.5Ni0.5Sb Double Half‐Heuslers.

Authors: Kahiu, Joseph Ngugi Shin, Donghyun Kihoi, Samuel Kimani et al.

Source: Small Structures. Jun2026, Vol. 7 Issue 6, p1-18. 18p.

Machine and deep learning techniques for the prediction of diabetics: a review.

Authors: Modak, Sandip Kumar Singh Jha, Vijay Kumar

Source: Multimedia Tools & Applications; May2025, Vol. 84 Issue 18, p19425-19549, 125p

Variation in Egg Quality Traits among Indigenous Chicken Ecotypes of Uganda.

Authors: Kiggundu, Muhammad Odaru, Zulaikah Nampijja, Zainah et al.

Source: Journal of Poultry Sciences & Avian Diseases (JPSAD). Oct2025, Vol. 3 Issue 4, p22-31. 10p.

An automatic AVR biomarker assessment system in retinal imaging.

Authors: Relan, Devanjali Mokan, Monika Relan, Rishi

Source: Multimedia Tools & Applications; Sep2023, Vol. 82 Issue 23, p36553-36575, 23p

VISTA: vision improvement via split and reconstruct deep neural network for fundus image quality assessment.

Authors: Khalid, Saif Abdulwahab, Saddam Stanchi, Oscar Agustín et al.

Source: Neural Computing & Applications; Dec2024, Vol. 36 Issue 36, p23149-23168, 20p

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Advances in retinal microaneurysms detection, segmentation and datasets for the diagnosis of diabetic retinopathy: a systematic literature review.

Authors: Tahir, Muhammad Zeeshan Nasir, Muhammad Zhang, Sanyuan

Source: Multimedia Tools & Applications; Sep2024, Vol. 83 Issue 30, p74897-74935, 39p

A survey on recent developments in diabetic retinopathy detection through integration of deep learning.

Authors: Agarwal, Shalini Bhat, Aruna

Source: Multimedia Tools & Applications; May2023, Vol. 82 Issue 11, p17321-17351, 31p

One year of hyperglycemia in the Ins2Akita mouse does not impart changes in retinal vascular patterning.

Authors: Shang, Fei Dholakia, Kosha Schallek, Jesse

Source: PLoS ONE. 5/28/2026, Vol. 21 Issue 5, p1-23. 23p.

Exudate and drusen classification in retinal images using bagged colour vector angles and inter colour local binary patterns.

Authors: Omar, Mohamed Albashir Khelifi, Fouad Tahir, Muhammad Atif

Source: Multimedia Tools & Applications; May2024, Vol. 83 Issue 17, p51809-51833, 25p

Application of deep learning approaches for classification of diabetic retinopathy stages from fundus retinal images: a survey.

Authors: Mukherjee, N. Sengupta, S.

Source: Multimedia Tools & Applications; Apr2024, Vol. 83 Issue 14, p43115-43175, 61p

Deep learning and classic machine learning models in the automatic diagnosis of multiple sclerosis using retinal vessels.

Authors: Yaghoubi, Neda Masumi, Hassan Fatehi, Mohammad Hossein et al.

Source: Multimedia Tools & Applications; Apr2024, Vol. 83 Issue 13, p37483-37504, 22p

CTNet: convolutional transformer network for diabetic retinopathy classification.

Authors: Bala, Ruchika Sharma, Arun Goel, Nidhi

Source: Neural Computing & Applications; Mar2024, Vol. 36 Issue 9, p4787-4809, 23p

Automated Computationally Intelligent Methods for Ocular Vessel Segmentation and Disease Detection: A Review.

Authors: Preity Bhandari, Ashish Kumar Shahnawazuddin, Syed

Source: Archives of Computational Methods in Engineering; Mar2024, Vol. 31 Issue 2, p701-724, 24p

Comparative Analysis of Diabetic Retinopathy Classification Approaches Using Machine Learning and Deep Learning Techniques.

Authors: Bala, Ruchika Sharma, Arun Goel, Nidhi

Source: Archives of Computational Methods in Engineering; Mar2024, Vol. 31 Issue 2, p919-955, 37p

Red lesion in fundus image with hexagonal pattern feature and two-level segmentation.

Authors: Latha, D. Bell, T. Beula Sheela, C. Jaspin Jeba

Source: Multimedia Tools & Applications; Jul2022, Vol. 81 Issue 18, p26143-26161, 19p

Intraretinal Microvascular Abnormalities in Eyes with Advanced Stages of Nonproliferative Diabetic Retinopathy: Comparison Between UWF-FFA, CFP, and OCTA—The RICHARD Study.

Authors: Santos, Ana R. Lopes, Marta Santos, Torcato et al.

Source: Ophthalmology & Therapy. Dec2024, Vol. 13 Issue 12, p3161-3173. 13p.

Challenges for ocular disease identification in the era of artificial intelligence.

Authors: Gour, Neha Tanveer, M. Khanna, Pritee

Source: Neural Computing & Applications; Nov2023, Vol. 35 Issue 31, p22887-22909, 23p