Abstract: The Region-based Convolutional Neural Network (R-CNN), which is more rapid, has been recognized as the best detection algorithm. With our design basis for Faster RCNN (FRCNN), the designers ...

We are a group of students working on graph algorithms, and we would like to contribute by implementing the Louvain community detection algorithm in JGraphT for detecting communities in large networks ...

To achieve autonomous vehicle (AV) operation, sensing techniques include radar, LiDAR, and cameras, as well as infrared (IR) and/or ultrasonic sensors, among others. No single sensing technique is ...

ABSTRACT: The study adapts several machine-learning and deep-learning architectures to recognize 63 traditional instruments in weakly labelled, polyphonic audio synthesized from the proprietary Sound ...

Scientists at Tarim University of China have proposed a way to address the challenging problem of pose recognition for photovoltaic panel cleaning robots. Their novel ...

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 ...

Maritime mobile edge computing (MMEC) technology facilitates the deployment of computationally intensive object detection tasks on Maritime Internet of Things (MIoT) devices with limited computing ...

Small object detection is a critical task in applications like autonomous driving and ship black smoke detection. While Deformable DETR has advanced small object detection, it faces limitations due to ...

Faster R-CNN is a Object Detection Model based on the Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks paper.

The Peoria City Council unanimously approved a 1% local grocery tax to offset the loss of a soon-to-expire state tax. Councilmember Zach Oyler voted in favor to enable a reconsideration of the tax at ...