Loyola University Maryland Hauber Research Fellowship Program records

Collection

Identifier: LUMD-012-008

Staff Only

An Overview of Optical Absorption Spectroscopy with a Focus on Thulium-Doped YAG

Digital Record

Identifier: 35f483dd-c8af-4aa2-a34a-050b0eccf926

Found in: Loyola University Maryland Archives / Loyola University Maryland Hauber Research Fellowship Program records / An Overview of Optical Absorption Spectroscopy with a Focus on Thulium-Doped YAG, 2020

Detecting Clandestine Graves Using White Dutch Clover; Plant Growth & Germination in Response to High Cadaverine Levels

Digital Record

Identifier: ddbc4d92-8989-4dff-b314-7b0e958f98b8

Found in: Loyola University Maryland Archives / Loyola University Maryland Hauber Research Fellowship Program records / Detecting Clandestine Graves Using White Dutch Clover; Plant Growth & Germination in Response to High Cadaverine Levels, 2020

External and Internal Environmental Conditions and Their Critical Impact on the Quality of 3D Printed Parts and Components

Digital Record

Identifier: cbf5e52d-7af9-4d48-82f8-1f928b8c23c4

Found in: Loyola University Maryland Archives / Loyola University Maryland Hauber Research Fellowship Program records / External and Internal Environmental Conditions and Their Critical Impact on the Quality of 3D Printed Parts and Components, 2020

Going Deep with Neural Networks: An Investigation into Deep Learning Methods for Efficient Image Recognition

Digital Record

Identifier: bfdbffeb-8398-40bd-9670-94d52963ac7e

Found in: Loyola University Maryland Archives / Loyola University Maryland Hauber Research Fellowship Program records / Going Deep with Neural Networks: An Investigation into Deep Learning Methods for Efficient Image Recognition, 2020

Patterns in Weakly Complete Sequences

Digital Record

Identifier: 5fd3f74c-09ae-44d1-95e4-97f076ab8fb3

Found in: Loyola University Maryland Archives / Loyola University Maryland Hauber Research Fellowship Program records / Patterns in Weakly Complete Sequences, 2020

Testing Deep Neural Network Models for Autonomous Vehicles

Digital Record

Identifier: d33bb75f-ee6d-41fc-b45c-be257ad6c9df

Found in: Loyola University Maryland Archives / Loyola University Maryland Hauber Research Fellowship Program records / Testing Deep Neural Network Models for Autonomous Vehicles, 2020