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Full-Text Articles in Engineering
Efficient End-To-End Autonomous Driving, Hesham Eraqi
Efficient End-To-End Autonomous Driving, Hesham Eraqi
Theses and Dissertations
Steering a car through traffic is a complex task that is difficult to cast into algorithms. Therefore, researchers turn to train artificial neural networks from front-facing camera data stream along with the associated steering angles. Nevertheless, most existing solutions consider only the visual camera frames as input, thus ignoring the temporal relationship between frames. In this work, we propose a Convolution Long Short-Term Memory Recurrent Neural Network (C-LSTM), which is end-to-end trainable, to learn both visual and dynamic temporal dependencies of driving. Additionally, We introduce posing the steering angle regression problem as classification while imposing a spatial relationship between the …
Palmprint Gender Classification Using Deep Learning Methods, Minou Khayami
Palmprint Gender Classification Using Deep Learning Methods, Minou Khayami
Graduate Theses, Dissertations, and Problem Reports
Gender identification is an important technique that can improve the performance of authentication systems by reducing searching space and speeding up the matching process. Several biometric traits have been used to ascertain human gender. Among them, the human palmprint possesses several discriminating features such as principal-lines, wrinkles, ridges, and minutiae features and that offer cues for gender identification. The goal of this work is to develop novel deep-learning techniques to determine gender from palmprint images. PolyU and CASIA palmprint databases with 90,000 and 5502 images respectively were used for training and testing purposes in this research. After ROI extraction and …