چکیده مقاله
The rapid evolution of logistics automation and freight transportation management has been propelled by image processing and deep learning technology advancements These tools enable real time analysis, optimization, and decision making, addressing complex challenges such as cargo classification, route optimization, vehicle monitoring, and anomaly detection This paper explores the application of cutting edge image processing techniques and deep learning algorithms to improve operational efficiency, reduce costs, and enhance accuracy across logistics and freight transportation systems Key methodologies include object detection, semantic segmentation, and predictive modeling, with applications ranging from automated inventory tracking to intelligent transportation networks The integration of these technologies transforms traditional logistics paradigms, laying the foundation for next generation intelligent supply chains Logistics automation, freight transportation, image processing, deep learning, object detection, semantic segmentation, intelligent transportation, and supply chain optimization
کلیدواژهها
نویسندگان
Sarah Barzegar
Vice President, Business Development Department, Avesta Company, Tehran, Iran, ۱۴۹۵۹۱۳۳۹۸
Aliasghar Mehrad
Founder, Management Department, Avesta Company, Tehran, Iran, ۱۴۹۵۹۱۳۳۹۸
شیوه ارجاع
Barzegar, Sarah and Mehrad, Aliasghar,1403,Application of Image Processing and Deep Learning in Logistics Automation and Freight Transportation Management,3nd International Conference and 8th National Conference on Computers, information technology and applications of artificial intelligence,Ahvaz
ارائهشده در
مجموعه مقالات سومین کنفرانس بین المللی و هشتمین کنفرانس ملی کامپیوتر، فناوری اطلاعات و کاربردهای هوش مصنوعی30 بهمن 1403 · اهواز