activity
20172020
most citedA Comprehensive Study of Alzheimer's Disease Classification Using Convolutional Neural Networks

10 citations · 30 across the 6 of their papers we have counts for

collaborators

9 papers

cs.LG20201 cited

Structure Mapping for Transferability of Causal Models

Purva Pruthi, Javier González, Xiaoyu Lu +1

Human beings learn causal models and constantly use them to transfer knowledge between similar environments. We use this intuition to design a transfer-learning framework using obj…

cs.LG20194 cited

Personalized Student Stress Prediction with Deep Multitask Network

Abhinav Shaw, Natcha Simsiri, Iman Deznaby +2

With the growing popularity of wearable devices, the ability to utilize physiological data collected from these devices to predict the wearer's mental state such as mood and stress…

eess.IV20199 cited

Alzheimer's Disease Brain MRI Classification: Challenges and Insights

Yi Ren Fung, Ziqiang Guan, Ritesh Kumar +2

In recent years, many papers have reported state-of-the-art performance on Alzheimer's Disease classification with MRI scans from the Alzheimer's Disease Neuroimaging Initiative (A…

cs.LG20194 cited

Multi-resolution Networks For Flexible Irregular Time Series Modeling (Multi-FIT)

Bhanu Pratap Singh, Iman Deznabi, Bharath Narasimhan +4

Missing values, irregularly collected samples, and multi-resolution signals commonly occur in multivariate time series data, making predictive tasks difficult. These challenges are…

cs.CV201910 cited

A Comprehensive Study of Alzheimer's Disease Classification Using Convolutional Neural Networks

Ziqiang Guan, Ritesh Kumar, Yi Ren Fung +2

A plethora of deep learning models have been developed for the task of Alzheimer's disease classification from brain MRI scans. Many of these models report high performance, achiev…

cs.CV2019

Pedestrian Detection in Thermal Images using Saliency Maps

Debasmita Ghose, Shasvat Mukeshkumar Desai, Sneha Bhattacharya +3

Thermal images are mainly used to detect the presence of people at night or in bad lighting conditions, but perform poorly at daytime. To solve this problem, most state-of-the-art…