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Deep Reinforcement Learning Based Path-Planning For Multi-Agent Systems In Advection-Diffusion Field Reconstruction Tasks, Deepak Talwar
Deep Reinforcement Learning Based Path-Planning For Multi-Agent Systems In Advection-Diffusion Field Reconstruction Tasks, Deepak Talwar
Master's Theses
Many environmental processes can be represented mathematically using spatial-temporal varying partial-differential equations. Timely estimation and prediction of processes such as wildfires is critical for disaster management response, but is difficult to accomplish without the availability of a dense network of stationary sensors. In this work, we propose a deep reinforcement learning-based real-time path-planning algorithm for mobile sensor networks traveling in a formation through a spatial-temporal varying advection-diffusion field for the task of field reconstruction. A deep Q-network (DQN) agent is trained on simulated advection-diffusion fields to direct the mobile sensor network to travel along information-rich trajectories. The field measurements made …
Lstm-Enabled Level Curve Tracking In Scalar Fields Using Multiple Mobile Robots, Kunj J. Parikh
Lstm-Enabled Level Curve Tracking In Scalar Fields Using Multiple Mobile Robots, Kunj J. Parikh
Master's Theses
Autonomous mobile sensor networks are ideal candidates for exploring large-scaleunknown fields with tasks ranging from source seeking, level curve tracking, mapping an unknown field, and many more. In this work, we investigate the problem of level curve tracking in unknown scalar fields using a limited number of mobile sensors. The level curve tracking problem has been studied in many applications such as monitoring the propagation of fire boundaries and the algae blooms. We design and implement a long short term memory (LSTM) enabled control strategy for a mobile sensor network to detect and track the desired level curve. We develop …
Influence Of Social Circles On User Recommendations, Chaitanya Krishna Kasaraneni
Influence Of Social Circles On User Recommendations, Chaitanya Krishna Kasaraneni
Master's Theses
Recommender systems are powerful tools that filter and recommend content relevant to a user. One of the most popular techniques used in recommender systems is collaborative filtering. Collaborative filtering has been successfully incorporated in many applications. However, these recommendation systems require a minimum number of users, items, and ratings in order to provide effective recommendations. This results in the infamous cold start problem where the system is not able to produce effective recommendations for new users. In recent times, with escalation in the popularity and usage of social networks, people tend to share their experiences in the form of reviews …
Adaptive Learning Technique For Facial Recognition, Rachana Dineshkumar Bumb
Adaptive Learning Technique For Facial Recognition, Rachana Dineshkumar Bumb
Master's Theses
This research describes the adaptive learning technique for facial recognition. It is a common practice in convolutional neural network(CNN) based facial recognition to save its trained result on a large dataset and then load and apply it to ongoing facial recognition tasks. This generally used method lacks adaptation, and the ongoing evolution of new knowledge poses a key technical challenge. In this research, we propose a continued learning technique to incorporate new knowledge derived in each facial recognition process. A positive recognition with confidence score is assigned, and the image associated with this confidence is added to the image dataset …
Auto-Landing System For Fixed-Wing Unmanned Aerial Vehicle, Dan Dermer
Auto-Landing System For Fixed-Wing Unmanned Aerial Vehicle, Dan Dermer
Master's Theses
Unmanned aerial vehicle systems, or any kind or autonomous system, are relevant to many applications today. However, they are complex and sophisticated systems that require a deep understanding of multiple technologies. In addition, the mathematical rigor, computer modelling, and programming applications involved make t¬his a challenging field of study. This thesis explores the possibility of achieving the automated landing of a fixed-wing unmanned aerial vehicle. Auto-landing systems can resolve the challenges for the novice user and make aerial vehicle platforms accessible and dependable. A wide spectrum of applications such as agriculture, aerial photography, and security, to name a few, can …
A Code Reputation System Using Ai And Blockchain Technology, Jeremy Chau
A Code Reputation System Using Ai And Blockchain Technology, Jeremy Chau
Master's Theses
Open source development is a method of development in which source code is developed using the combined skills of the public. A few examples of this sort of development would be the Chromium and Linux kernel projects hosted on GitHub. Open source development offers a wide variety of benefits and disadvantages. A main concern is when many people blindly trust developers without second thought. There is a lack of a rating system that judges those who develop code through open source means. This can call into question the quality of the code being written by the individual as well as …