Kidney Cancer is one of the most prevalent diseases that is more common in men than in women. Detecting kidney tumors at an early stage has been found to increase survival rates of patients. It is therefore important to accurately segment tumors in Computed Tomography(CT) images. To assist in early detection of kidney tumors in CT images, we present a method for segmenting kidney tumors using deep convolutional neural networks. Predicted models using U-Net and Attention U-Net architectures are ensemble for effective tumor segmentation. Experimental and visual results obtained using the KiTS2019 dataset clearly demonstrate the enhanced Intersection Over Union(IoU) score of the ensemble model.

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The Western Ghats in India’s Deccan Plateau has been recognized as one of the eight “hottest hot-spots” of biological diversity in the world. UNESCO has identified this region as a World Heritage Site. In Maharashtra, this mountain range is known as ‘Sahyadri’, ‘Dang forests’ in Gujarat, ‘Nilgiris’ in Tamil Nadu and Kerala, and ‘Malnad’ in Karnataka. It stretches across the six Indian states of Gujrat, Maharashtra, Goa, Tamil Nadu, Kerala, Karnataka and two union territories including Daman and Diu and Pondicherry. These hills begin near the border of Gujarat and Maharashtra, south of the Tapti river, and end at Kanyakumari, at the southern tip of India, covering an incredible 1,60,000 sq.km. In the 18th and 19th centuries, most of the people who classified the flora of these regions are hobbyists. Very few British Officers who conduct survey of this landscape release their books. A complete scientific study of this biodiversity hot-spot is yet to be undertaken. Until now, only a handful of scientists have undertaken a study of the Western Ghats. So, this present article expains a brief scientific study of the forests of the Western Ghats.

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