Efficient Deep Learning Modalities for Object Detection from Infrared Images  

作　　者：Naglaa F.Soliman E.A.Alabdulkreem Abeer D.Algarni Ghada M.El Banby Fathi E.Abd El-Samie Ahmed Sedik 

机构地区：[1]Department of Information Technology,College of Computer and Information Sciences,Princess Nourah Bint Abdulrahman University,Riyadh,84428,Saudi Arabia [2]Department of Electronics and Communications,Faculty of Engineering,Zagazig University,Zagazig,44519,Egypt [3]Department of Computer Sciences,College of Computer and Information Sciences,Princess Nourah Bint Abdulrahman University,Riyadh,84428,Saudi Arabia [4]Department of Industrial Electronics and Control Engineering,Faculty of Electronic Engineering,Menoufia University,Menouf,32952,Egypt [5]Department of Electronics and Electrical Communications,Faculty of Electronic Engineering,Menoufia University,Menouf,32952,Egypt [6]Department of the Robotics and Intelligent Machines,Faculty of Artificial Intelligence,KafrelSheikh University,Kafr el-sheikh,Egypt

出　　处：《Computers, Materials & Continua》2022年第8期2545-2563,共19页计算机、材料和连续体（英文）

基　　金：This research was funded by the Deanship of Scientific Research at Princess Nourah Bint Abdulrahman University through the Research Funding Program(Grant No#FRP-1440-23).

摘　　要：For military warfare purposes,it is necessary to identify the type of a certain weapon through video stream tracking based on infrared(IR)video frames.Computer vision is a visual search trend that is used to identify objects in images or video frames.For military applications,drones take a main role in surveillance tasks,but they cannot be confident for longtime missions.So,there is a need for such a system,which provides a continuous surveillance task to support the drone mission.Such a system can be called a Hybrid Surveillance System(HSS).This system is based on a distributed network of wireless sensors for continuous surveillance.In addition,it includes one or more drones to make short-time missions,if the sensors detect a suspicious event.This paper presents a digital solution to identify certain types of concealed weapons in surveillance applications based on Convolutional Neural Networks(CNNs)and Convolutional Long Short-Term Memory(ConvLSTM).Based on initial results,the importance of video frame enhancement is obvious to improve the visibility of objects in video streams.The accuracy of the proposed methods reach 99%,which reflects the effectiveness of the presented solution.In addition,the experimental results prove that the proposed methods provide superior performance compared to traditional ones.

关 键 词：Deep learning object detection military applications OFDM SPIHT IOT 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]