Affiliations: | | Laboratory of Neurogenetics | NIAAA/NIH, Bethesda, MD, United States |
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High-probability grants
According to our matching algorithm, David Goldman is the likely recipient of the following grants.
Years |
Recipients |
Code |
Title / Keywords |
Matching score |
2001 — 2002 |
Goldman, David |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
Sttr Phase I: Intellistitch Ai: Intelligent Computerized Embroidery Design Automation For the Textile Industry
This Small Business Technology Transfer Research (STTR) Phase I project builds upon the technology and success of the company's software product, one of the industry's first embroidery design automation systems. It provides the textile industry with simplified mechanisms for converting scanned artwork into high quality embroidery design data. This data is then utilized by commercial sewing equipment to produce the embroidered artwork that has become quite common on all types of garments and woven goods. Unfortunately, embroidered artwork is often quite expensive to produce. In many cases, it may substantially exceed the costs of the actual garments being imprinted. These costs arise from a variety of factors including an embroidered design's size, layout, and complexity. Well-designed embroidered artwork permits efficient production with high yields (i.e. causing very few defective items to be produced). Automating this design creation process provides additional benefits by eliminating the time consuming manual process that must otherwise be undertaken by a human expert. With these factors as the primary motivation, this research will investigate advanced artificial intelligence and machine vision mechanisms, such as neural nets and structural indexes, to substantially improve capabilities and performance.
The advantages of a robust automation system to the textile industry are quite substantial. Creating sophisticated embroidery designs is a tedious, time-consuming activity requiring the skills of a human expert (called a digitizer). Even after this process has been completed, any miscalculations by the digitizer could substantially impede production on machinery. A well-designed expert system could inevitably eliminate these costs and perhaps even provide a level of quality that is not achievable by its human counterparts. Additionally, this research may also have broad application within other fields such as document processing or other areas where image understanding and interpretation is important.
|
0.903 |
2003 — 2005 |
Goldman, David |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
Sttr Phase Ii: Intellistitch Ai: Intelligent Computerized Embroidery Design Automation For the Textile Industry
This Small Business Technology Transfer (STTR) Phase II project will develop an automated means for embroidery design specification for use in the textile industry. This technology will provide simplified mechanisms for converting scanned artwork into high quality embroidery design data. This data will then be utilized by commercial sewing equipment to produce embroidered artwork that has become quite common on all types of garments and woven goods. Embroidered artwork is often quite expensive to produce and in many cases may substantially exceed the costs of the actual garments being imprinted. These costs arise from a variety of factors including an embroidered design's size and complexity. Well-designed embroidered artwork permits efficient production with high yields (i.e. minimal defects produced). Automating design creation provides additional benefits by eliminating the time consuming manual process that must otherwise be undertaken by a human expert.
The commercial and broader impacts of this technology facilitate lower manufacturing costs while allowing consistent production of high-quality goods. Additionally, this research may have broader applications within other fields such as document processing, image recognition, or other areas where image understanding and interpretation are important.
|
0.903 |