4 citations · 8 across the 5 of their papers we have counts for
7 papers
Towards Continual, Online, Self-Supervised Depth
Muhammad Umar Karim Khan
Although depth extraction with passive sensors has seen remarkable improvement with deep learning, these approaches may fail to obtain correct depth if they are exposed to environm…
Increased-Range Unsupervised Monocular Depth Estimation
Saad Imran, Muhammad Umar Karim Khan, Sikander Bin Mukarram +1
Unsupervised deep learning methods have shown promising performance for single-image depth estimation. Since most of these methods use binocular stereo pairs for self-supervision,…
Self-Supervised Representation Learning for Visual Anomaly Detection
Rabia Ali, Muhammad Umar Karim Khan, Chong Min Kyung
Self-supervised learning allows for better utilization of unlabelled data. The feature representation obtained by self-supervision can be used in downstream tasks such as classific…
Fine-Tuning DARTS for Image Classification
Muhammad Suhaib Tanveer, Muhammad Umar Karim Khan, Chong-Min Kyung
Neural Architecture Search (NAS) has gained attraction due to superior classification performance. Differential Architecture Search (DARTS) is a computationally light method. To li…
Global Feature Aggregation for Accident Anticipation
Mishal Fatima, Muhammad Umar Karim Khan, Chong Min Kyung
Anticipation of accidents ahead of time in autonomous and non-autonomous vehicles aids in accident avoidance. In order to recognize abnormal events such as traffic accidents in a v…
Plug-and-Play Anomaly Detection with Expectation Maximization Filtering
Muhammad Umar Karim Khan, Mishal Fatima, Chong-Min Kyung
Anomaly detection in crowds enables early rescue response. A plug-and-play smart camera for crowd surveillance has numerous constraints different from typical anomaly detection: th…
Efficient Neural Network Compression
Hyeji Kim, Muhammad Umar Karim Khan, Chong-Min Kyung
Network compression reduces the computational complexity and memory consumption of deep neural networks by reducing the number of parameters. In SVD-based network compression, the…