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Full-Text Articles in Engineering
Computer Aided Diagnosis System For Breast Cancer Using Deep Learning., Asma Baccouche
Computer Aided Diagnosis System For Breast Cancer Using Deep Learning., Asma Baccouche
Electronic Theses and Dissertations
The recent rise of big data technology surrounding the electronic systems and developed toolkits gave birth to new promises for Artificial Intelligence (AI). With the continuous use of data-centric systems and machines in our lives, such as social media, surveys, emails, reports, etc., there is no doubt that data has gained the center of attention by scientists and motivated them to provide more decision-making and operational support systems across multiple domains. With the recent breakthroughs in artificial intelligence, the use of machine learning and deep learning models have achieved remarkable advances in computer vision, ecommerce, cybersecurity, and healthcare. Particularly, numerous …
Automatic Testing Of Organic Strain Gauge Tactile Sensors., Brian P. Goulet
Automatic Testing Of Organic Strain Gauge Tactile Sensors., Brian P. Goulet
Electronic Theses and Dissertations
Human-Robot Interaction is a developing field of science, that is posed to augment everything we do in life. Skin sensors that can detect touch, temperature, distance, and other physical interaction parameters at the human-robot interface are very important to enhancing the collaboration between humans and machines. As such, these sensors must be efficiently tested and characterized to give accurate feedback from the sensor to the robot. The objective of this work is to create a diversified software testing suite that removes as much human intervention as possible. The tests and methodology discussed here provide multiple realistic scenarios that the sensors …
Heterogeneous Collaborative Mapping For Autonomous Mobile Systems, Sooraj Sunil
Heterogeneous Collaborative Mapping For Autonomous Mobile Systems, Sooraj Sunil
Electronic Theses and Dissertations
An accurate map of the environment is essential for autonomous robot navigation. During collaborative simultaneous localization and mapping, the individual robots usually represent the environment as probabilistic occupancy grid maps. These maps can be exchanged among robots and fused to reduce the overall exploration time, which is the main advantage of the collaborative systems. Such fusion is challenging due to the unknown initial correspondence problem. This thesis presents a novel feature-based map fusion approach through detecting, describing, and matching geometrically consistent features present in the overlapping region between the maps. The main drawback of usual feature-based approaches is the incapability …