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Rapid and explosive growth of digital libraries due to the invention of Web cameras, digital cameras, and mobile phones equipped with such devices is making the database management by human annotation an extremely tedious and clumsy task. Image indexing and retrieval is very important research topic that has gained more attention in the current scenario. So in the present situation content based image retrieval is becoming necessary for exact and fast image retrieval. Content Based Image Retrieval (CBIR) is one of the image retrieval techniques which use visual features of an image such as color, shape, and texture features etc. In this paper presents techniques for extracting low level features, various distance measures for measuring the similarity of image and performance measures.

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The paper is on the detection of keratoconus a corneal progressive disorder leading to the thinning and also protrusion of the cornea associated with symptoms like astigmatism, increased sensitivity to bright light, glare, clouded vision, eye irritation, and others, In recent times there has been increasing in a number of keratoconus cases. Keratoconus is normally described as a non-inflammatory pathology. The main contribution of the paper is to facilitate detection and also classification of the keratoconus based on the progression using Convolution neural networks. The paper is about the implementation of different CNN algorithms which will classify the disorder based on the progression into 4 different classes. The CNN algorithms analyze the corneal topography of the eye and classify based on the severity of the disorder. We introduce an effective CNN model called CON-KER for the detection and classification of the disorder. Further CNN algorithms like Alexnet and Vgg 19 were implemented for the same. The results show that the CON-KER model has yielded an accuracy of 96.26% compared to other algorithms like vgg19 which yielded 94.76% and AlexNet with 86% accuracy. This work can help by assisting the ophthalmologist in reducing diagnostic errors and also help in the rapid screening of the patients.

Because of the rapid development progress of Power natural philosophy strategies, applications with electrical phenomenon (PV) power and wind generation are swollen basically the employment of sun supercharged And wind energies severally wouldn't offer an immersed yield voltage that the solar power and Wind energy square measure consolidated can improve the characteristics of every alternative. To diminish the ability demand on the normal power age space, we have a tendency to propose this method. Various ways square measure by and by for age of intensity utilizing Solar-Wind Hybrid System with most electrical outlet pursuit (MPPT). Steady voltage strategy is used for much extreme power exchange. This strategy has to be compelled to have some key highlights to create the potency. Above all this article proposes a completely unique technique for implementing MPPT controller in our hybrid renewable energy generation system known as FLC rule for higher potency than alternative strategies. The higher than explained system is intended and modeled for output results were obtained.