Sowmya Kamath S

TL;DR: The challenges that need to be addressed in designing such effective, efficient, and robust algorithms for early DR diagnosis systems are discussed and also the ample scope for future research in this area is discussed.

TL;DR: This paper proposes a social framework, which extracts user's reviews, comments of restaurants and points of interest such as events and locations, to personalize and rank suggestions based on user preferences, which provides the user with quicker and more relevant data, thus avoiding irrelevant data and providing much needed personalization.

TL;DR: FarSight is presented, a long-term aggregation mechanism intended to recognize the onset of the disease with the earliest detected symptoms, and the superior performance of the proposed models built on unstructured data when compared to structured EHR based state-of-the-art model.

TL;DR: A novel multi-space approach to solve Zero-Shot Object Detection where predictions obtained in two different search spaces are combined and the problem of hubness is discussed and it is shown that the approach alleviates hubness with a performance superior to previously proposed methods.

TL;DR: In this paper , a CBIR system is proposed for the retrieval of medical images (CBMIR) for enabling the early detection and classification of lung diseases based on lung X-ray images.