57 citations · 108 across the 26 of their papers we have counts for
9 papers · 1 filter
Targeted Self Supervision for Classification on a Small COVID-19 CT Scan Dataset
Nicolas Ewen, Naimul Khan
Traditionally, convolutional neural networks need large amounts of data labelled by humans to train. Self supervision has been proposed as a method of dealing with small amounts of…
CNN based Multistage Gated Average Fusion (MGAF) for Human Action Recognition Using Depth and Inertial Sensors
Zeeshan Ahmad, Naimul khan
Convolutional Neural Network (CNN) provides leverage to extract and fuse features from all layers of its architecture. However, extracting and fusing intermediate features from dif…
Interpreting Uncertainty in Model Predictions For COVID-19 Diagnosis
Gayathiri Murugamoorthy, Naimul Khan
COVID-19, due to its accelerated spread has brought in the need to use assistive tools for faster diagnosis in addition to typical lab swab testing. Chest X-Rays for COVID cases te…
Multidomain Multimodal Fusion For Human Action Recognition Using Inertial Sensors
Zeeshan Ahmad, Naimul Khan
One of the major reasons for misclassification of multiplex actions during action recognition is the unavailability of complementary features that provide the semantic information…
Towards Improved Human Action Recognition Using Convolutional Neural Networks and Multimodal Fusion of Depth and Inertial Sensor Data
Zeeshan Ahmad, Naimul Khan
This paper attempts at improving the accuracy of Human Action Recognition (HAR) by fusion of depth and inertial sensor data. Firstly, we transform the depth data into Sequential Fr…
An Efficient Confidence Measure-Based Evaluation Metric for Breast Cancer Screening Using Bayesian Neural Networks
Anika Tabassum, Naimul Khan
Screening mammograms is the gold standard for detecting breast cancer early. While a good amount of work has been performed on mammography image classification, especially with dee…