Diabetic retinopathy using image processing and deep learning

Swain, Debabrata; Bijawe, Sanket; Akolkar, Prasanna; Shinde, Aditya; Mahajani, Mihir

doi:10.1504/ijcsm.2021.120686

Cited by 7 publications

(2 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The development of FL has experienced three stages: traditional privacy protection, FL and security FL. Basically, all kinds of commonly used machine learning algorithms can adopt FL method for model training, support structured, text, image and other types of data sources, and can be applied in sample classification, path programming [164], regression prediction, image recognition [165,166], gene analysis, natural language and other tasks. In recent years, FL has played an important role in health care, finance, Internet of things, urban services and other fields where there is a strictly requirement for privacy protection.…”

Section: Discussionmentioning

confidence: 99%

A survey on federated learning: challenges and applications

Zhang

Lan

et al. 2022

Int. J. Mach. Learn. & Cyber.

View full text Add to dashboard Cite

y impact on human life [1][2][3]. As great progress has been made in AI technology in recent years, various application fields have stepped into intelligence [4,5]. On the road of AI development, models, computing power, chip performance, and other technical issues have been the focus of academic research, so that AI technology can continue to evolve. For machines to truly approach the level of human thought, they need to be trained with vast amounts of real data [6,7]. However, cloud computing power, data security, data silos and other risks will inevitably become constraints for AI to win user trust, collect private data, and achieve largescale implementation [8]. Therefore, it is an urgent need for a practical and effective technique to alleviate the above problems and make the AI full of vitality again. Under this background, the concept of "federated learning (FL) " came into being.The notion of FL is first proposed by Google in 2016, mainly to make android mobile phone users update models locally without revealing private personal data [9]. After then, Google implemented an application-oriented FL system. The designed FL system, which focused on running federated average (FedAvg) algorithms on mobile phones, can perform federated analytics and be applied to monitor statistics for large-scale cluster equipment without recording raw device data to the cloud server. FL is one of the most Zhihua Cui

show abstract

Section: Discussionmentioning

confidence: 99%

A survey on federated learning: challenges and applications

Zhang

Lan

et al. 2022

Int. J. Mach. Learn. & Cyber.

View full text Add to dashboard Cite

show abstract

“…The learning rate used here was 0.001. One of the main reasons for its popularity is it can handle sparse gradients on noisy problems easily [20,21] which we can observe from equation 4.…”

Section: Adammentioning

confidence: 99%

An Intelligent Fashion Object Classification Using CNN

Swain,

Pandya,

Sanghvi

et al. 2023

EAI Endorsed Trans Ind Net Intel Syst

Self Cite

View full text Add to dashboard Cite

Every year the count of visually impaired people is increasing drastically around the world. At present time, approximately 2.2 billion people are suffering from visual impairment. One of the major areas where our model will affect public life is the area of house assistance for specially-abled persons. Because of visual improvement, these people face lots of issues. Hence for this group of people, there is a high need for an assistance system in terms of object recognition. For specially-abled people sometimes it becomes really difficult to identify clothing-related items from one another because of high similarity. For better object classification we use a model which includes computer vision and CNN. Computer vision is the area of AI that helps to identify visual objects. Here a CNN-based model is used for better classification of clothing and fashion items. Another model known as Lenet is used which has a stronger architectural structure. Lenet is a multi-layer convolution neural network that is mainly used for image classification tasks. For model building and validation MNIST fashion dataset is used.

show abstract