this paper proposes a framework for automated object detection and annotation, specifically designed for surveillance applications. The framework incorporates both manual and automatic modes, offering ...

Faster R-CNN is a two-stage object detection model that uses a Region Proposal Network (RPN) to generate high-quality region proposals, followed by a classifier to detect objects. Vision Transformers ...

This project applies machine learning techniques to classify Iris flower species based on sepal and petal measurements. It explores multiple classification algorithms, including Random Forest, SVM, ...

But there’s a big problem with the report. The data is old. Pre-abortion-ban old. It looks at deaths in 2020, before Texas’ near-total abortion ban took effect in 2022. Texas’ Maternal ...

This article introduces a streamlined UWB radar-based respiration detection application designed for operation on IoT processors, emphasizing that when executed on conventional IoT processors, the ...

A complete and local NVR designed for Home Assistant with AI object detection. Uses OpenCV and Tensorflow to perform realtime object detection locally for IP cameras. Use of a Google Coral Accelerator ...

2021) established a basic line for underwater object detection based on the YOLO v5 algorithm ... fishing vessels were used as original dataset to train the YOLO model. The pre-processing module of ...

Results: On the test set, the YOLOv3 achieved average fracture detection ... the training data) did not decrease for 10 consecutive epochs. The training was stopped when the validation set loss did ...