18552628. Systems and Methods for Compact and Low-Cost Vibrational Spectroscopy Platforms simplified abstract (The Board of Trustees of the Leland Stanford Junior University)
Contents
- 1 Systems and Methods for Compact and Low-Cost Vibrational Spectroscopy Platforms
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 Systems and Methods for Compact and Low-Cost Vibrational Spectroscopy Platforms - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Original Abstract Submitted
Systems and Methods for Compact and Low-Cost Vibrational Spectroscopy Platforms
Organization Name
The Board of Trustees of the Leland Stanford Junior University
Inventor(s)
Jennifer A. Dionne of Menlo Park CA (US)
Ahmed Shuaibi of Stanford CA (US)
Amr A. E. Saleh of Stanford CA (US)
Systems and Methods for Compact and Low-Cost Vibrational Spectroscopy Platforms - A simplified explanation of the abstract
This abstract first appeared for US patent application 18552628 titled 'Systems and Methods for Compact and Low-Cost Vibrational Spectroscopy Platforms
Simplified Explanation
The patent application describes systems and methods for compact and low-cost vibrational spectroscopy platforms that utilize deep learning processes for efficient data analysis. By reducing the spectral data to a subset of spectral bands, the hardware incorporation in spectroscopic platforms becomes more compact and cost-effective.
- Efficient data analysis through deep learning processes
- Reduction of spectral data to a subset of spectral bands for compact and low-cost hardware incorporation
Potential Applications
The technology can be applied in various fields such as material identification, chemical analysis, environmental monitoring, and quality control processes.
Problems Solved
1. Cost-effective vibrational spectroscopy platforms 2. Efficient data analysis for element identification
Benefits
1. Compact and low-cost hardware incorporation 2. Improved data analysis processes 3. Enhanced element identification capabilities
Potential Commercial Applications
"Compact and Low-Cost Vibrational Spectroscopy Platforms for Efficient Element Identification"
Possible Prior Art
There may be prior art related to vibrational spectroscopy platforms, deep learning processes for data analysis, and hardware incorporation in spectroscopic devices.
What are the limitations of the compact and low-cost vibrational spectroscopy platforms described in the patent application?
The patent application does not specify any limitations or drawbacks of the described technology.
How does the deep learning process in the compact and low-cost vibrational spectroscopy platforms differ from traditional data analysis methods?
The patent application does not provide a detailed comparison between deep learning processes and traditional data analysis methods.
Original Abstract Submitted
Systems and methods for compact and low-cost vibrational spectroscopy platforms are described. Many embodiments implement deep learning processes to identify the relevant optical spectral features for the identification of an element from a set of elements. Several embodiments provide that resolution reduction and feature selection render efficient data analysis processes. By reducing the spectral data from the full wide-band high-resolution spectrum to a subset of spectral bands, a number of embodiments provide compact and low-cost hardware incorporation in spectroscopic platforms for element identification functions.
