Project Grant R43AI184319

This federal Cooperative Agreement award from the National Science Foundation (NSF) under the NSF Technology, Innovation, and Partnerships (CFDA 47.084) program provides $999,479 to Vectech, Inc., a small disadvantaged business, to develop advanced artificial intelligence (AI) methods for automated identification of mosquito species from high-resolution images. The goal is to enable more accessible and scalable vector surveillance data collection to support public health institutions in their...

Vectech, Inc. received a $255,781 Project Grant award from the National Science Foundation on June 15, 2021 to fund research and development of advanced computer vision methods for mosquito surveillance through February 28, 2022. The award was made under the National Science Foundation's Engineering program (CFDA 47.041), which seeks to improve quality of life and economic strength through engineering innovation and excellence in research and education. Specifically, the grant supports Vectech's...

This Project Grant awarded by the National Institutes of Health (NIH) under the Research Infrastructure Programs (CFDA 93.351) provides $294,543 to Objective Biotechnology, Inc. to develop a machine vision guided robotic system for automating microinjections into fruit fly (Drosophila melanogaster) embryos. The goal is to eliminate the need for manual, labor-intensive microinjection protocols and accelerate the process of generating and maintaining transgenic fly lines, which are critical for...

The National Science Foundation (NSF) awarded a $981,168 Cooperative Agreement under its Technology, Innovation, and Partnerships (CFDA 47.084) program to Solarid Ar LLC, a minority-owned, veteran-owned, Asian-Pacific American-owned limited liability company. This 2-year project aims to develop an artificial intelligence (AI)-driven insect trapping and identification system that can detect, identify, and quantify insects entering insect control devices in real-time. The primary objective is to...

This Project Grant award from the National Science Foundation (NSF) Biological Sciences program (CFDA 47.074) provides $372,442 to Kansas State University to develop an automated bee identification and data sharing platform. The key objectives are: Creating a large, expertly-labeled image dataset of at least 1,000 North American bee species to train computer vision algorithms. Developing an AI-based classification model using convolutional neural networks to identify bee species from images....

The U.S. Department of Agriculture's (USDA) National Institute of Food and Agriculture (NIFA) awarded a $262,737.48 project grant to Colorado State University under the Agriculture and Food Research Initiative (AFRI) program. The goal of this 2-year project is to develop an AI-based decision support system that will allow farmers and other stakeholders to identify agricultural pests by uploading cellphone photos to a mobile application. This system will target pests of small grains in the Inland...

This $268,500 cooperative agreement from the Department of Agriculture Animal and Plant Health Inspection Service will support the development of artificial intelligence algorithms for the automatic detection of pests in high water content plants and fruits. Awarded to Stanford University on August 12, 2022 under the Plant and Animal Disease, Pest Control, and Animal Care program (CFDA #10.025), the project aims to modify an existing X-ray phase-contrast imaging system to enable continuous...

This $305,007 federal Project Grant award from the National Science Foundation's Biological Sciences (CFDA 47.074) program will support the development of a research hub for automated bee identification, data sharing, and citizen science using computer vision technology. The key products and services to be delivered under this 3-year award include: Creation of a large, expertly-labeled image dataset of at least 1,000 North American bee species to train an AI-based bee classification model...

This Project Grant award from the National Eye Institute (NEI), under the Vision Research program (CFDA 93.867), provides $459,286 to the University of Vermont & State Agricultural College to develop innovative machine learning-based image classifiers to detect trachoma, a leading infectious cause of vision loss worldwide. The key products and services to be delivered include: Developing a smartphone-based application to standardize and enhance tarsal plate imaging for trachoma...

This Project Grant award from the National Science Foundation Division of Information and Intelligent Systems under CFDA 47.070 Computer and Information Science and Engineering provides funding of $548,346 from July 15, 2023 to June 30, 2028 to the University of Connecticut. The key products and services to be delivered under this award are: Development of deep learning frameworks trained on highly variable biological image data, including non-model organisms collected from the wild and imaged...