6 citations · 9 across the 3 of their papers we have counts for
6 papers
Robust and Computationally-Efficient Anomaly Detection using Powers-of-Two Networks
Usama Muneeb, Erdem Koyuncu, Yasaman Keshtkarjahromi +3
Robust and computationally efficient anomaly detection in videos is a problem in video surveillance systems. We propose a technique to increase robustness and reduce computational…
Detecting Gas Vapor Leaks Using Uncalibrated Sensors
Diaa Badawi, Tuba Ayhan, Sule Ozev +3
Chemical and infra-red sensors generate distinct responses under similar conditions because of sensor drift, noise or resolution errors. In this work, we use different time-series…
Deep Layered LMS Predictor
Lubna Shibly Mokatren, Ahmet Enis Cetin, Rashid Ansari
In this study, we present a new approach to design a Least Mean Squares (LMS) predictor. This approach exploits the concept of deep neural networks and their supremacy in terms of…
EEG Classification by factoring in Sensor Configuration
Lubna Shibly Mokatren, Rashid Ansari, Ahmet Enis Cetin +4
Electroencephalography (EEG) serves as an effective diagnostic tool for mental disorders and neurological abnormalities. Enhanced analysis and classification of EEG signals can hel…
Deep Convolutional Generative Adversarial Networks Based Flame Detection in Video
Süleyman Aslan, Uğur Güdükbay, B. Uğur Töreyin +1
Real-time flame detection is crucial in video based surveillance systems. We propose a vision-based method to detect flames using Deep Convolutional Generative Adversarial Neural N…
EEG Classification based on Image Configuration in Social Anxiety Disorder
Lubna Shibly Mokatren, Rashid Ansari, Ahmet Enis Cetin +4
The problem of detecting the presence of Social Anxiety Disorder (SAD) using Electroencephalography (EEG) for classification has seen limited study and is addressed with a new appr…