54 citations · 88 across the 11 of their papers we have counts for
7 papers · 1 filter
TransWeather: Transformer-based Restoration of Images Degraded by Adverse Weather Conditions
Jeya Maria Jose Valanarasu, Rajeev Yasarla, Vishal M. Patel
Removing adverse weather conditions like rain, fog, and snow from images is an important problem in many applications. Most methods proposed in the literature have been designed to…
SPIN Road Mapper: Extracting Roads from Aerial Images via Spatial and Interaction Space Graph Reasoning for Autonomous Driving
Wele Gedara Chaminda Bandara, Jeya Maria Jose Valanarasu, Vishal M. Patel
Road extraction is an essential step in building autonomous navigation systems. Detecting road segments is challenging as they are of varying widths, bifurcated throughout the imag…
Image Fusion Transformer
Vibashan VS, Jeya Maria Jose Valanarasu, Poojan Oza +1
In image fusion, images obtained from different sensors are fused to generate a single image with enhanced information. In recent years, state-of-the-art methods have adopted Convo…
Over-and-Under Complete Convolutional RNN for MRI Reconstruction
Pengfei Guo, Jeya Maria Jose Valanarasu, Puyang Wang +3
Reconstructing magnetic resonance (MR) images from undersampled data is a challenging problem due to various artifacts introduced by the under-sampling operation. Recent deep learn…
Brain Tumor Segmentation and Survival Prediction using 3D Attention UNet
Mobarakol Islam, Vibashan VS, V Jeya Maria Jose +3
In this work, we develop an attention convolutional neural network (CNN) to segment brain tumors from Magnetic Resonance Images (MRI). Further, we predict the survival rate using v…
Glioma Prognosis: Segmentation of the Tumor and Survival Prediction using Shape, Geometric and Clinical Information
Mobarakol Islam, V Jeya Maria Jose, Hongliang Ren
Segmentation of brain tumor from magnetic resonance imaging (MRI) is a vital process to improve diagnosis, treatment planning and to study the difference between subjects with tumo…
Medical Transformer: Gated Axial-Attention for Medical Image Segmentation
Jeya Maria Jose Valanarasu, Poojan Oza, Ilker Hacihaliloglu +1
Over the past decade, Deep Convolutional Neural Networks have been widely adopted for medical image segmentation and shown to achieve adequate performance. However, due to the inhe…