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Full-Text Articles in Physical Sciences and Mathematics
Dataset And Evaluation Of Self-Supervised Learning For Panoramic Depth Estimation, Ryan Nett
Dataset And Evaluation Of Self-Supervised Learning For Panoramic Depth Estimation, Ryan Nett
Master's Theses
Depth detection is a very common computer vision problem. It shows up primarily in robotics, automation, or 3D visualization domains, as it is essential for converting images to point clouds. One of the poster child applications is self driving cars. Currently, the best methods for depth detection are either very expensive, like LIDAR, or require precise calibration, like stereo cameras. These costs have given rise to attempts to detect depth from a monocular camera (a single camera). While this is possible, it is harder than LIDAR or stereo methods since depth can't be measured from monocular images, it has to …
Using Current-Voltage Characteristics To Probe The Transport Mechanism In Carbon Nanotube Networks, Alejandro Jimenez
Using Current-Voltage Characteristics To Probe The Transport Mechanism In Carbon Nanotube Networks, Alejandro Jimenez
Physics
Carbon nanotube (CNT) random networks have shown great promise in electronic applications. For example, they have been used as the active layer in thin film transistor biosensors and as electrodes in supercapacitors (Hu, 2010). Although CNT networks applications are numerous, some of the key details of their electrical behavior are not fully understood. In particular, it is known that the junctions between tubes in CNT networks play a key role in determining the sensing properties of the network (Thanihaichelvana, et al., 2018), however, the mechanism by which metallic-semiconducting (m-s) tube junctions affect the electrical sensing properties of the network is …