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What is Hybrid Approaches

Approaches and Applications of Deep Learning in Virtual Medical Care
Hybrid techniques are a combination of two or more computational techniques which provide more advantage to detect components than any other individual technique. It helps to improve data analysis. The hybrid technique helps qualitative research to be effective.
Published in Chapter:
Overview and Analysis of Present-Day Diabetic Retinopathy (DR) Detection Techniques
Smita Das (MBB College, India) and Swanirbhar Majumder (Tripura University, India)
DOI: 10.4018/978-1-7998-8929-8.ch003
Diabetic retinopathy (DR) detection techniques is a biometric modality that deserves systematic review and analysis of the connected algorithms for further improvement. The ophthalmologist uses retinal fundus images for the early detection of DR by segmenting the images. There are several segmentation algorithms reported as earlier. This chapter presents a comprehensive review of the methodology associated with retinal blood vessel extraction presented to date. The vessel segmentation techniques are divided into four main categories depending on their underlying methodology as pattern recognition, vessel tracking, model based, and hybrid approaches. A few of these methods are further classified into subsections. Finally, a comparative analysis of a few of the DR detection techniques will be presented here based on their merits, demerits, and other parameters like sensitivity, specificity, and accuracy and provide detailed information about its significance, present status, limitations, and future scope.
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E-Commerce Recommendation Systems
It combines various methods to produce recommendations in order to combine the robustness and eliminate the drawbacks of the individual techniques.
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