Existing algorithms can partially reconstruct the shape of a single tree from a clean point-cloud dataset acquired by ...

Ice detection technology developed by researchers at the University of Toronto could speed up the de-icing process for ...

Event-based cameras are sensors inspired by the human eye, offering advantages such as high-speed robustness and low power consumption. Established deep learning techniques have proven effective in ...

This research aims to reactivate object-oriented databases using intelligent tools to improve performance and accuracy in modern work environments that require processing large amounts of complex data ...

Pull requests help you collaborate on code with other people. As pull requests are created, they’ll appear here in a searchable and filterable list. To get started, you should create a pull request.

Traffic monitoring plays a vital role in smart city infrastructure, road safety, and urban planning. Traditional detection systems, including earlier deep learning models, often struggle with ...

Abstract: Object detection forms an important area of research where the efforts are still being put forth to improve the accuracy of detection. Several approaches have been made which also include ...

I tried to run the object detection using tensorflow example on macOS and it did not compile. The compilation errors are because of conflicting usage of conditions in ...

Abstract: Traditional methods in machine learning for detecting traffic lights and classification are replaced by the recent enhancements of deep learning object detection methods by success of ...