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pro vyhledávání: '"Timothy Linhardt"'
Autor:
Timothy Linhardt, Ananya Sen Gupta
Publikováno v:
The Journal of the Acoustical Society of America. 153:A178-A178
Feature representation in the littoral sonar space is a complicated field due to prevalent channel noise from sound reflections as well as diffraction. The response of a sound wave as it interacts with an object provides insight into the nature of th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8ad7459e465f9fd50a1ef3e3b10c2ecb
https://doi.org/10.1121/10.0018583
https://doi.org/10.1121/10.0018583
Autor:
Timothy Linhardt, Ananya Sen Gupta
Publikováno v:
The Journal of the Acoustical Society of America. 152:A296-A296
Convolutional autoencoders have been used in an effort to learn latent encodings of littoral accoustic backscatter, but previous work did not explore a wide range of metavariable variation. Only the dimension of the encoding space, and the learning r
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0b8796c88bda837acad0747b33516e17
https://doi.org/10.1121/10.0016336
https://doi.org/10.1121/10.0016336
Empirical analysis of latent space encodings for submerged small target acoustic backscattering data
Autor:
Timothy Linhardt, Ananya Sen Gupta
Publikováno v:
The Journal of the Acoustical Society of America. 151:A102-A102
With future sights on specialized classification methods, we work to generalize the acoustic backscattering data from sonar measurements of small targets submerged in water by learning a non-invertible mapping (encoding) to a low-dimensional vector s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::098bb4cd00e9a40a73dfa56e908b4746
https://doi.org/10.1121/10.0010792
https://doi.org/10.1121/10.0010792
Publikováno v:
The Journal of the Acoustical Society of America. 151:A102-A102
Autonomous target recognition has been a long-standing problem with complementary techniques based on classic subspace-based methods and recent machine cognition techniques proposed across several decades. Despite some success in both approaches, rob
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::394b886b508c699bf013a089907e66e7
https://doi.org/10.1121/10.0010790
https://doi.org/10.1121/10.0010790
Autor:
Madison Kemerling, Ryan A. McCarthy, Bernice Kubicek, Timothy Linhardt, Luke Hermann, Ananya Sen Gupta
Publikováno v:
The Journal of the Acoustical Society of America. 149:A36-A37
Explainable artificial intelligence is gaining wider traction within the machine learning community and its application domains at large for its inherent motivation to explain and interpret large-scale machine interpretation of experimental datasets.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::78ab6d05d5d8a546ac55cd25e239e032
https://doi.org/10.1121/10.0004451
https://doi.org/10.1121/10.0004451