Программный модуль распознавания образов для микрокомпьютеров на основе нейронных сетей семейства YOLOv5 компактный программный модуль на базе комбинации сети
YOLOv5 и ShuffleNet V2, размер и количество параметров
Tracking the flow of motor vehicles on the roads with YOLOv5 and deepsort algorithms is to count the flow of moving vehicles, in particular, using the
YOLOv5 and Deep SORT algorithms to perform
Integration of Deep Learning and Wireless Sensor Networks for Accurate Fire Detection in Indoor Environment and
decrease false alarms. Wi-Fi camera movies are analyzed using the
YOLOv5 deep learning model. This
model
Using the City's Surveillance Cameras to Create a Visual Sensor Network to Detect FiresDheyab, Omer A. Dheyab,
Chernikov, Dmitry Yu.,
Selivanov, Alexander S.,
Деяб, О. А.,
Черников, Д. Ю.,
Селиванов, А. С. for enhancing fire detection operations is the
YOLOv5 model. For precise and effective
fire detection, city
Применение компьютерного зрения для обнаружения и извлечения табличных данных из PDF-файловКрупкин, И. А.,
Лесив, А. А.,
Барская, Г. Б.,
Krupkin, I. A.,
Lesiv, A. A.,
Barskaya, G. B. экспериментов показали высокую точность и эффективность алгоритма
YOLOv8.
Buildroot для систем на кристалле семейства Allwinner F1CX00SSoftware module for pattern recognition for microcomputers based on neural networks of
Yolov5 Based on Weak Light YOLOv3 Multi-Target DetectionInside the real life scenarios, the
YOLOv3 target
detection model has achieved good results
An Improved Small Object Detection Method in Remote Sensing Images Based on YOLOv8 research, we conduct a comprehensive analysis and improvement of the
YOLOv8-n algorithm for object