57 citations · 108 across the 26 of their papers we have counts for
6 papers · 2 filters
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…
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…
Facial Expression Recognition Under Partial Occlusion from Virtual Reality Headsets based on Transfer Learning
Bita Houshmand, Naimul Khan
Facial expressions of emotion are a major channel in our daily communications, and it has been subject of intense research in recent years. To automatically infer facial expression…
Multi-level Stress Assessment Using Multi-domain Fusion of ECG Signal
Zeeshan Ahmad, Naimul Khan
Stress analysis and assessment of affective states of mind using ECG as a physiological signal is a burning research topic in biomedical signal processing. However, existing litera…
Locality Guided Neural Networks for Explainable Artificial Intelligence
Randy Tan, Naimul Khan, Ling Guan
In current deep network architectures, deeper layers in networks tend to contain hundreds of independent neurons which makes it hard for humans to understand how they interact with…