CNN

(M)SLAe-Net: Multi-Scale Multi-Level Attention embedded Network for Retinal Vessel Segmentation

Segmentation plays a crucial role in diagnosis. Studying the retinal vasculatures from fundus images help identify early signs of many crucial illnesses such as diabetic retinopathy. Due to the varying shape, size, and patterns of retinal vessels, …

B-SegNet: branched-SegMentor network for skin lesion segmentation

Melanoma is the most common form of cancer in the world. Early diagnosis of the disease and an accurate estimation of its size and shape are crucial in preventing its spread to other body parts. Manual segmentation of these lesions by a radiologist …

M2SLAe-Net: Multi-Scale Multi-Level Attention embedded Network for Retinal Vessel Segmentation(Abstract Presentation)

Segmentation plays a crucial role in diagnosis. Studying the retinal vasculatures from fundus images help identify early signs of many crucial illnesses such as diabetic retinopathy. Due to the varying shape, size, and patterns of retinal vessels, …

Variational AutoEncoder

In deep learning, Variational autoencoders (VAEs) is a technique for learning latent representations. They are also used in a number of semi supervised tasks such as to draw/generate images.

Detector-SegMentor Network for Skin Lesion Localization and Segmentation

Melanoma is a life-threatening form of skin cancer when left undiagnosed at the early stages. Although there are more cases of non-melanoma cancer than melanoma cancer, melanoma cancer is more deadly. Early detection of melanoma is crucial for the …

PixISegNet:Pixel Level Iris Segmentation Network using Convolutional Encoder-Decoder with Stacked Hourglass Bottleneck

Robust Iris Segmentation network