# of Displayed Technologies: 4 / 4

Applied Category Filter (Click To Remove): Data Analysis


Categories

Unlocking Hidden Opportunities: The Power of Multi-Solution Spatial Aggregation
TS-067434 — The Need Spatial aggregation is crucial in numerous industries where data from low-level spatial units, such as census blocks, must be grouped into larger, meaningful regions. Traditional approaches often struggle with the computational complexity of these tasks and tend to focus on finding a singl…
  • College: College of Arts & Sciences
  • Inventors: Xiao, Ningchuan
  • Licensing Officer: Dahlman, Jason "Jay"

Visual Function Mapping Technology: Enhancing Vision Care and Diagnostics
TS-062335 — The Need: In the field of ophthalmology and vision care, there is a critical need for accurate and comprehensive measurements of visual function over the entire visual field. Conditions such as glaucoma, age-related macular degeneration (AMD), diabetes, stroke, pituitary disease, brain tumors, and n…
  • College: College of Arts & Sciences
  • Inventors: Lu, Zhong-Lin; Lesmes, Luis; Xu, Pengjing "PJ"; Yu, Deyue
  • Licensing Officer: Dahlman, Jason "Jay"

Machine-Learning Algorithm for Improved Speech Intelligibility in Noise
TS-042266 — A monaural machine-learning algorithm for classifying time-frequency units in an unknown signal, which results in marked speech-intelligibly improvements in noisy signals.
A primary complaint of hearing-impaired (HI) listeners is poor speech recognition in background noise. This issue can be quite debilitating and persists despite considerable efforts to improve hearing technology. Despite considerable effort, monaural (single-microphone) algorithms capable of incre…
  • College: College of Arts & Sciences
  • Inventors: Healy, Eric; Vasko, Jordan
  • Licensing Officer: Dahlman, Jason "Jay"

Machine-Learning Algorithm for Improved Speech Intelligibility in Noise
TS-038074 — A monaural machine-learning algorithm for classifying time-frequency units in an unknown signal, which results in marked speech-intelligibly improvements in noisy signals.
Wireless carriers receive daily complaints about poor speech recognition in background noise during calls and are constantly looking for methods to improve especially in light of recent forays into VOIP. The ability to discriminate between speech and noise in an audio signal then is an extremely i…
  • College: College of Arts & Sciences
  • Inventors: Healy, Eric; Vasko, Jordan
  • Licensing Officer: Dahlman, Jason "Jay"

Loading icon