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Articles 91 - 120 of 906

Full-Text Articles in Electrical and Electronics

Outdoor Operations Of Multiple Quadrotors In Windy Environment, Deepan Lobo May 2022

Outdoor Operations Of Multiple Quadrotors In Windy Environment, Deepan Lobo

Dissertations

Coordinated multiple small unmanned aerial vehicles (sUAVs) offer several advantages over a single sUAV platform. These advantages include improved task efficiency, reduced task completion time, improved fault tolerance, and higher task flexibility. However, their deployment in an outdoor environment is challenging due to the presence of wind gusts. The coordinated motion of a multi-sUAV system in the presence of wind disturbances is a challenging problem when considering collision avoidance (safety), scalability, and communication connectivity. Performing wind-agnostic motion planning for sUAVs may produce a sizeable cross-track error if the wind on the planned route leads to actuator saturation. In a multi-sUAV …

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Automated Robotic Light Bulb Testing Platform, Agha I. Akram, Muhammad Ali Ummy May 2022

Automated Robotic Light Bulb Testing Platform, Agha I. Akram, Muhammad Ali Ummy

Publications and Research

The main purpose of this project is to create a functional prototype of a multilayered system that incorporates aspects of electrical, mechanical, and computer engineering technology. The main objective of the system is to be able to determine whether a light bulb is working or not. The building blocks of this system are a robotic arm that is able to slide along a rail (for added mobility), a conveyor belt, and an electromechanical device that holds and tests light bulbs. Initially, the robot arm picks up a light bulb and places it into the holder which then tests it. A …

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Development Of An Automated Electronic Prototyping System, Cesar Yahir Sanchez Zambrano May 2022

Development Of An Automated Electronic Prototyping System, Cesar Yahir Sanchez Zambrano

Open Access Theses & Dissertations

Prototyping systems with interconnected components can be a time and resource expensive process. The process consists of three main phases (design, build and analysis) with each having their own associated cost. For the case of electronic circuits, the building phase is the costliest phase among the three, being prone to human errors which causes the circuit to fail. All three phases of the prototyping process are important. However, often a disproportionate amount of time is spent on the build phase due to the difficulty of making and troubleshooting circuits by hand. In this thesis we will discuss a system that …

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Design And Implementation Of I2c Bus Protocol On Master And Slave Data Transfer Based On Fpga, Mohamad Khairi Ishak, Meenal Pradeep Kumar Apr 2022

Design And Implementation Of I2c Bus Protocol On Master And Slave Data Transfer Based On Fpga, Mohamad Khairi Ishak, Meenal Pradeep Kumar

Makara Journal of Technology

This paper presents the design of the inter-integrated circuit (I2C) protocol with different types of features, such as combined messages, addressing modes, different data patterns and start addresses, clock frequencies, and types of modes between the field-programmable gate array (FPGA) and test card. Moreover, all these features can be randomized and run for long hours. The FPGA and the test card respectively act as master and slave. The design architecture comprises master and slave. The master generates a START condition, in which the serial data will transact between high to low levels and the serial clock will remain high. Then, …

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Enhancement Of Biogas Production Through Solid-State Anaerobic Co-Digestion Of Food Waste And Corn Cobs, Lukhi Mulia Shitophyta, Anisa Salsabila, Firanita Angraini Putri, Siti Jamilatun Apr 2022

Enhancement Of Biogas Production Through Solid-State Anaerobic Co-Digestion Of Food Waste And Corn Cobs, Lukhi Mulia Shitophyta, Anisa Salsabila, Firanita Angraini Putri, Siti Jamilatun

Makara Journal of Technology

Although biogas has been primarily produced through liquid anaerobic digestion, this method leads to the floating and stratification of fibers and non-homogeneous mixing, which can reduce the biogas yield. Alternatively, biogas can be produced by the solid-state anaerobic digestion (SS-AD) of organic material with a high solid content, such as corn cobs. We investigated the co-digestion of food waste and corn cobs as a biomass feedstock for SS-AD in biogas production. We measured the effects of the total solid (TS) content, percentage of food waste, and reduction in volatile solids (VS), from which we determined its appropriate kinetic model. We …

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Control Strategy For Solar Energy-Saving Lamps For Optimized Energy Utilization And Sustainability Of Operation Durability: Indonesia Case, Burhanuddin Halimi, Agus Purwadi, Nana Heryana Apr 2022

Control Strategy For Solar Energy-Saving Lamps For Optimized Energy Utilization And Sustainability Of Operation Durability: Indonesia Case, Burhanuddin Halimi, Agus Purwadi, Nana Heryana

Makara Journal of Technology

To solve the electrification ratio issue, the Indonesian government has promoted the use of solar energy-saving lamps. This study proposes a control strategy that adopts current reference time-based profiling for solar energy-saving lamps. For optimal energy consumption, the current reference profile is determined according to users’ daily energy requirements. From the aspect of user comfort, a gradual step reference profile is also introduced to provide a subtle change in lighting intensity level. The proposed control strategy can minimize energy consumption and optimize the operation durability of the system. The concept is verified by simulating four scenarios, the results of which …

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Autonomous Navigator Mobile Robot Upgrade, David Sansoucy Apr 2022

Autonomous Navigator Mobile Robot Upgrade, David Sansoucy

Thinking Matters Symposium

The mobile robot platform has been developed over the course of 10 years at USM. In Spring 2020, Belle-Isle and Werner updated the previous framework by rewriting the software to use the ROS framework running on an on-board Raspberry Pi 3. They also implemented navigation using an A* motion planning algorithm and image processing. In Summer 2021, Ames incorporated Lidar and Kinect sensors onto the robot to improve its real-time navigation capabilities. He also made improvements to the power distribution systems. This project aimed to build on the ROS frameworks developed by the previous 2 teams with the main goal …

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A Low-Cost, Arduino-Based Platform For Emulating Energy Harvesting In Wireless Sensor Networks, Braden A. Miller Apr 2022

A Low-Cost, Arduino-Based Platform For Emulating Energy Harvesting In Wireless Sensor Networks, Braden A. Miller

ONU Student Research Colloquium

This paper presents an Arduino-based platform for emulating energy harvesting in Wireless Sensor Networks (WSNs) as a form of hardware-in-the-loop simulation. The platform makes use of a battery monitoring circuit and code implemented on the Arduino as an alternative to using significantly more expensive fully equipped energy harvesting nodes. Using embedded code to emulate the energy harvesting process allows for various energy harvesting models and processes to be tested using the same platform. The main contributions of this paper are the experimental data and analyses demonstrating the energy use characterization of the Arduino-based platform in a three-node relay network using …

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Microscopic Nuclei Classification, Segmentation, And Detection With Improved Deep Convolutional Neural Networks (Dcnn), Md Zahangir Alom, Vijayan K. Asari, Anil Parwani, Tarek M. Taha Apr 2022

Microscopic Nuclei Classification, Segmentation, And Detection With Improved Deep Convolutional Neural Networks (Dcnn), Md Zahangir Alom, Vijayan K. Asari, Anil Parwani, Tarek M. Taha

Electrical and Computer Engineering Faculty Publications

Background Nuclei classification, segmentation, and detection from pathological images are challenging tasks due to cellular heterogeneity in the Whole Slide Images (WSI). Methods In this work, we propose advanced DCNN models for nuclei classification, segmentation, and detection tasks. The Densely Connected Neural Network (DCNN) and Densely Connected Recurrent Convolutional Network (DCRN) models are applied for the nuclei classification tasks. The Recurrent Residual U-Net (R2U-Net) and the R2UNet-based regression model named the University of Dayton Net (UD-Net) are applied for nuclei segmentation and detection tasks respectively. The experiments are conducted on publicly available datasets, including Routine Colon Cancer (RCC) classification and …

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Towards Improved Inertial Navigation By Reducing Errors Using Deep Learning Methodology, Hua Chen, Tarek M. Taha, Vamsy P. Chodavarapu Apr 2022

Towards Improved Inertial Navigation By Reducing Errors Using Deep Learning Methodology, Hua Chen, Tarek M. Taha, Vamsy P. Chodavarapu

Electrical and Computer Engineering Faculty Publications

Autonomous vehicles make use of an Inertial Navigation System (INS) as part of vehicular sensor fusion in many situations including GPS-denied environments such as dense urban places, multi-level parking structures, and areas with thick tree-coverage. The INS unit incorporates an Inertial Measurement Unit (IMU) to process the linear acceleration and angular velocity data to obtain orientation, position, and velocity information using mechanization equations. In this work, we describe a novel deep-learning-based methodology, using Convolutional Neural Networks (CNN), to reduce errors from MEMS IMU sensors. We develop a CNN-based approach that can learn from the responses of a particular inertial sensor …

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Design And Implementation Of Photovoltaic Energy Harvesting Automaton, Iskandar Askarov Jan 2022

Design And Implementation Of Photovoltaic Energy Harvesting Automaton, Iskandar Askarov

Theses

Global domestic electricity consumption has been rapidly increasing in the past three decades. In fact, from 1990 to 2020, consumption has more than doubled from 10,120 TWh to 23,177 TWh [1]. Moreover, consumers have been turning more towards clean, renewable energy sources such as Photovoltaic. According to International Energy Agency, global Solar power generation alone in 2019 has reached almost 3% [4] of the electricity supply. Even though the efficiency of photovoltaic panels has been growing, presently, the highest efficiency solar panels available to an average consumer range only from 20%-22% [14]. Many research papers have been published to increase …

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A Deep Neural Network For Early Detection And Prediction Of Chronic Kidney Disease, Vijendra Singh, Vijayan K. Asari, Rajkumar Rajasekaran Jan 2022

A Deep Neural Network For Early Detection And Prediction Of Chronic Kidney Disease, Vijendra Singh, Vijayan K. Asari, Rajkumar Rajasekaran

Electrical and Computer Engineering Faculty Publications

Diabetes and high blood pressure are the primary causes of Chronic Kidney Disease (CKD). Glomerular Filtration Rate (GFR) and kidney damage markers are used by researchers around the world to identify CKD as a condition that leads to reduced renal function over time. A person with CKD has a higher chance of dying young. Doctors face a difficult task in diagnosing the different diseases linked to CKD at an early stage in order to prevent the disease. This research presents a novel deep learning model for the early detection and prediction of CKD. This research objectives to create a deep …

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A Progressive Learning Strategy For Large-Scale Glacier Mapping, Zhiyuan Xie, Umesh K. Haritashya, Vijayan K. Asari Jan 2022

A Progressive Learning Strategy For Large-Scale Glacier Mapping, Zhiyuan Xie, Umesh K. Haritashya, Vijayan K. Asari

Electrical and Computer Engineering Faculty Publications

In recent years, the worldwide temperature increase has resulted in rapid deglaciation and a higher risk of glacier-related natural hazards such as flooding and debris flow. Due to the severity of these hazards, continuous observation and detailed analysis of glacier fluctuations are crucial. Many such analyses require an accurately delineated glacier boundary. However, the complexity and heterogeneity of glaciers, particularly debris-covered glaciers (DCGs), poses a challenge for glacier mapping when using conventional remote sensing or machine-learning techniques. Some examples exist about small-scale automated glacier mapping, but large or regional-scale mapping is challenging. Previously, a deep-learning-based approach named GlacierNet2 had been …

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Removing Physical Presence Requirements For A Remote And Automated World - Api Controlled Patch Panel For Conformance Testing, Hunter George Wells Jan 2022

Removing Physical Presence Requirements For A Remote And Automated World - Api Controlled Patch Panel For Conformance Testing, Hunter George Wells

Honors Theses and Capstones

Quality assurance test engineers at the UNH-InterOperability Lab must run tests that require driving and monitoring a selection of DC signals. While the number of signals is numerous, there are limited ports on the test equipment, and only a few signals need patching for any given test. The selection of signals may vary between the 209 different tests and must be re-routed frequently. Currently, testers must leave their desk to manually modify the test setup in another room. This posed a considerable issue at the onset of the COVID-19 Pandemic when physical access was not possible. In order to enable …

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Biomimetic Design, Modeling, And Adaptive Control Of Robotic Gripper For Optimal Grasping, Mushtaq Al-Mohammed Jan 2022

Biomimetic Design, Modeling, And Adaptive Control Of Robotic Gripper For Optimal Grasping, Mushtaq Al-Mohammed

Electronic Theses and Dissertations, 2020-2023

Grasping is an essential skill for almost every assistive robot. Variations in shape and/or weight of different objects involved in Activities of Daily Living (ADL) lead to complications, especially, when the robot is trying to grip novel objects for which it has no prior information –too much force will deform or crush the object while too little force will lead to slipping and possibly dropped objects. Thus, successful grasping requires the gripper to immobilize an object with the minimal force. In Chapter 2, we present the design, analysis, and experimental implementation of an adaptive control to facilitate 1-click grasping of …

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Meltpondnet: A Swin Transformer U-Net For Detection Of Melt Ponds On Arctic Sea Ice, Ivan Sudakow, Vijayan K. Asari, Ruixu Liu, Denis Demchev Jan 2022

Meltpondnet: A Swin Transformer U-Net For Detection Of Melt Ponds On Arctic Sea Ice, Ivan Sudakow, Vijayan K. Asari, Ruixu Liu, Denis Demchev

Electrical and Computer Engineering Faculty Publications

High-resolution aerial photographs of Arctic region are a great source for different sea ice feature recognition, which are crucial to validate, tune, and improve climate models. Melt ponds on the surface of melting Arctic sea ice are of particular interest as they are sensitive and valuable indicators and are proxy to the processes in the Arctic climate system. Manual analysis of this remote sensing data is extremely difficult and time-consuming due to the complex shapes and unpredictable boundaries of the melt ponds, and that leads to the necessity for automatizing the processes. In this study, we propose a robust and …

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Circuit Optimization Techniques For Efficient Ex-Situ Training Of Robust Memristor Based Liquid State Machine, Alex Henderson, Christopher Yakopcic, Cory Merkel, Steven Harbour, Tarek M. Taha, Hananel Hazan Jan 2022

Circuit Optimization Techniques For Efficient Ex-Situ Training Of Robust Memristor Based Liquid State Machine, Alex Henderson, Christopher Yakopcic, Cory Merkel, Steven Harbour, Tarek M. Taha, Hananel Hazan

Electrical and Computer Engineering Faculty Publications

Spiking neural network hardware offers a high performance, power-efficient and robust platform for the processing of complex data. Many of these systems require supervised learning, which poses a challenge when using gradient-based algorithms due to the discontinuous properties of SNNs. Memristor based hardware can offer gains in portability, power reduction, and throughput efficiency when compared to pure CMOS. This paper proposes a memristor-based spiking liquid state machine (LSM). The inherent dynamics of the LSM permit the use of supervised learning without backpropagation for weight updates. To carry out the design space evaluation of the LSM for optimal hardware performance, several …

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Garden Bot: Autonomous Home Garden Weed Removal Robot, Brendon Lovejoy, Robert Connolly, Isaac Lucas, Stevan Veselinov Jan 2022

Garden Bot: Autonomous Home Garden Weed Removal Robot, Brendon Lovejoy, Robert Connolly, Isaac Lucas, Stevan Veselinov

Williams Honors College, Honors Research Projects

With frequent weeding being a tedious chore and an essential task for a successful garden, there is need for an automated method of handling this routine. Existing technologies utilize computer vision, GPS, multiple units and other tools to remove weeds from garden plots. However, these solutions are often complex and expensive, suited for large agricultural plots in contrast to small-scale home gardens. In addition, many of these technologies, along with manual tillers and cultivators suited for home use, are unable to perform weeding within rows of crops in a process known as intra-row weeding. The Garden Bot is an autonomous, …

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Smart Uv-C Disinfectant Module, Nicole Baldy, Luke Rogers, Haitham Saleh Jan 2022

Smart Uv-C Disinfectant Module, Nicole Baldy, Luke Rogers, Haitham Saleh

Williams Honors College, Honors Research Projects

The Smart UV Disinfectant device shall sanitize objects which are 18”x14”x8” or smaller and less than 20 lbs. using UV-C light. This device should contain many safety measures to prevent human and animal exposure to the UV-C light and have no public touchpoints to operate the interface. In order to achieve the first objective, this device shall contain a "sanitizing chamber" which completely encloses the object to be sanitized to prevent outside exposure with detection of any lifeforms inside of the chamber; for the second objective, it will contain a wireless interface to an Android application which can be used …

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Magic: The Gathering Card Virtualizer, Vincent Garbonick, Jacen C. Conlan, Jaret A. Varn Jan 2022

Magic: The Gathering Card Virtualizer, Vincent Garbonick, Jacen C. Conlan, Jaret A. Varn

Williams Honors College, Honors Research Projects

Any well-versed Magic: The Gathering (MTG) player or collector knows how difficult it can be to keep track of all cards in their collection. Some spend hours searching for that one specific card, and others are constantly scouring the internet for how much their collection costs. However, this issue does not only affect casual fans. Resale companies spend hours a day determining the costs of cards, and tournament judges painstakingly check players’ decks to ensure they are not cheating. To assist with these struggles, the design team proposed to create the MTG Card Virtualizer. This device scans MTG playing cards …

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High Energy And Power Density Peptidoglycan Musclesthrough Super-Viscous Nanoconfined Water, Haozhen Wang, Zhi-Lun Liu, Jianpei Lao, Sheng Zhang, Rinat Abzalimov, Tong Wang, Xi Chen Jan 2022

High Energy And Power Density Peptidoglycan Musclesthrough Super-Viscous Nanoconfined Water, Haozhen Wang, Zhi-Lun Liu, Jianpei Lao, Sheng Zhang, Rinat Abzalimov, Tong Wang, Xi Chen

Advanced Science Research Center

Water-responsive (WR) materials that reversibly deform in response to humidity changes show great potential for developing muscle-like actuators for miniature and biomimetic robotics. Here, it is presented that Bacillus (B.) subtilis’ peptidoglycan (PG) exhibits WR actuation energy and power densities reaching 72.6 MJ m−3 and 9.1 MW m−3, respectively, orders of magnitude higher than those of frequently used actuators, such as piezoelectric actuators and dielectric elastomers. PG can deform as much as 27.2% within 110 ms, and its actuation pressure reaches ≈354.6 MPa. Surprisingly, PG exhibits an energy conversion efficiency of ≈66.8%, which can be attributed to its super-viscous nanoconfined …

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Scalable Scientific Data Management On High-Performance Computing Systems, Zhenbo Qiao Dec 2021

Scalable Scientific Data Management On High-Performance Computing Systems, Zhenbo Qiao

Dissertations

As high-performance computing (HPC) is being scaled up to exascale to accommodate new modeling and simulation needs, I/O has continued to be a major bottleneck in the end-to-end scientific processes. To bridge the widening gap between compute and I/O, and enable data to be more efficiently stored and analyzed, simulation outputs need to be refactored, reduced, and appropriately mapped to storage tiers. Also, a major question that the community is striving to answer is how to co-design data storage and complex physics-rich analytics in a way that the time to knowledge can be minimized in post-processing. As HPC storage systems …

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Enhanced Security Utilizing Side Channel Data Analysis, Michael Taylor Dec 2021

Enhanced Security Utilizing Side Channel Data Analysis, Michael Taylor

Computer Science and Engineering Theses and Dissertations

The physical state of a system is affected by the activities and processes in which it is tasked with carrying out. In the past there have been many instances where such physical changes have been exploited by bad actors in order to gain insight into the operational state and even the data being held on a system. This method of side channel exploitation is very often effective due to the relative difficulty of obfuscating activity on a physical level. However, in order to take advantage of side channel data streams one must have a detailed working knowledge of how a …

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Autonomous Control And Signal Acquisition System, Rion Cadell Krampe Dec 2021

Autonomous Control And Signal Acquisition System, Rion Cadell Krampe

Honors College Theses

Our goal is to continue a previous teams project to build a NDE autonomous control and signal acquisition system that is more precise, more customizable with both code and mechanical parts, and cheaper than a similar system bought by the school. This goal has two stages to it. First, to repair the system from considerable damage it received during transportation. Secondly, to continue designing and developing the system to make considerable progress towards the goal of a fully functional NDE system. Along with making progress we must consider the team after us and create an easy stepping off point for …

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Evaluating Deep-Learning Models For Debris-Covered Glacier Mapping, Zhiyuan Xie, Vijayan K. Asari, Umesh K. Haritashya Dec 2021

Evaluating Deep-Learning Models For Debris-Covered Glacier Mapping, Zhiyuan Xie, Vijayan K. Asari, Umesh K. Haritashya

Electrical and Computer Engineering Faculty Publications

In recent decades, mountain glaciers have experienced the impact of climate change in the form of accelerated glacier retreat and other glacier-related hazards such as mass wasting and glacier lake outburst floods. Since there are wide-ranging societal consequences of glacier retreat and hazards, monitoring these glaciers as accurately and repeatedly as possible is important. However, the accurate glacier boundary, especially the debriscovered glacier (DCG) boundary, which is one of the primary inputs in many glacier analyses, remains a challenge even after many years of research using conventional remote sensing methods or machine-learning methods. The GlacierNet, a deep-learning-based approach, utilized the …

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Augmented Communications : A Solution For Overcoming High Spatial Correlation Of The Massive-Miso Vlc Channel, Monette Khadr Dec 2021

Augmented Communications : A Solution For Overcoming High Spatial Correlation Of The Massive-Miso Vlc Channel, Monette Khadr

Legacy Theses & Dissertations (2009 - 2024)

A key challenge for future wireless networks is to come upon a riveting compromise between spectral efficiency, complexity, and energy efficiency. The challenge is also intensified due to the pace at which the Internet-of-Things (IoT) technology is arriving, causing an upheaval to pre-existing network infrastructures in terms of elevating spectrum scarcity. To keep pace with the exploding data demand forecasts, a circumvention is required. One realization is by utilizing the high-band spectrum and the rich body of knowledge on multiple-input multiple-output (MIMO) technologies. One of the prominent high frequency technologies is visible light communications (VLC). VLC provide a large unregulated …

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Network Management, Optimization And Security With Machine Learning Applications In Wireless Networks, Mariam Nabil Dec 2021

Network Management, Optimization And Security With Machine Learning Applications In Wireless Networks, Mariam Nabil

Theses and Dissertations

Wireless communication networks are emerging fast with a lot of challenges and ambitions. Requirements that are expected to be delivered by modern wireless networks are complex, multi-dimensional, and sometimes contradicting. In this thesis, we investigate several types of emerging wireless networks and tackle some challenges of these various networks. We focus on three main challenges. Those are Resource Optimization, Network Management, and Cyber Security. We present multiple views of these three aspects and propose solutions to probable scenarios. The first challenge (Resource Optimization) is studied in Wireless Powered Communication Networks (WPCNs). WPCNs are considered a very promising approach towards sustainable, …

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Collaborative Human-Machine Interfaces For Mobile Manipulators., Shamsudeen Olawale Abubakar Dec 2021

Collaborative Human-Machine Interfaces For Mobile Manipulators., Shamsudeen Olawale Abubakar

Electronic Theses and Dissertations

The use of mobile manipulators in service industries as both agents in physical Human Robot Interaction (pHRI) and for social interactions has been on the increase in recent times due to necessities like compensating for workforce shortages and enabling safer and more efficient operations amongst other reasons. Collaborative robots, or co-bots, are robots that are developed for use with human interaction through direct contact or close proximity in a shared space with the human users. The work presented in this dissertation focuses on the design, implementation and analysis of components for the next-generation collaborative human machine interfaces (CHMI) needed for …

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Machine Learning For Unmanned Aerial System (Uas) Networking, Jian Wang Dec 2021

Machine Learning For Unmanned Aerial System (Uas) Networking, Jian Wang

Doctoral Dissertations and Master's Theses

Fueled by the advancement of 5G new radio (5G NR), rapid development has occurred in many fields. Compared with the conventional approaches, beamforming and network slicing enable 5G NR to have ten times decrease in latency, connection density, and experienced throughput than 4G long term evolution (4G LTE). These advantages pave the way for the evolution of Cyber-physical Systems (CPS) on a large scale. The reduction of consumption, the advancement of control engineering, and the simplification of Unmanned Aircraft System (UAS) enable the UAS networking deployment on a large scale to become feasible. The UAS networking can finish multiple complex …

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Resampling And Super-Resolution Of Hexagonally Sampled Images Using Deep Learning, Dylan Flaute, Russell C. Hardie, Hamed Elwarfalli Oct 2021

Resampling And Super-Resolution Of Hexagonally Sampled Images Using Deep Learning, Dylan Flaute, Russell C. Hardie, Hamed Elwarfalli

Electrical and Computer Engineering Faculty Publications

Super-resolution (SR) aims to increase the resolution of imagery. Applications include security, medical imaging, and object recognition. We propose a deep learning-based SR system that takes a hexagonally sampled low-resolution image as an input and generates a rectangularly sampled SR image as an output. For training and testing, we use a realistic observation model that includes optical degradation from diffraction and sensor degradation from detector integration. Our SR approach first uses non-uniform interpolation to partially upsample the observed hexagonal imagery and convert it to a rectangular grid. We then leverage a state-of-the-art convolutional neural network (CNN) architecture designed for SR …

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