Security is a significant issue for everyone due to new and creative ways to commit cybercrime.The Closed-Circuit Television(CCTV)systems are being installed in offices,houses,shopping malls,and on streets to protect ...Security is a significant issue for everyone due to new and creative ways to commit cybercrime.The Closed-Circuit Television(CCTV)systems are being installed in offices,houses,shopping malls,and on streets to protect lives.Operators monitor CCTV;however,it is difficult for a single person to monitor the actions of multiple people at one time.Consequently,there is a dire need for an automated monitoring system that detects a person with ammunition or any other harmful material Based on our research and findings of this study,we have designed a new Intelligent Ammunition Detection and Classification(IADC)system using Convolutional Neural Network(CNN).The proposed system is designed to identify persons carrying weapons and ammunition using CCTV cameras.When weapons are identified,the cameras sound an alarm.In the proposed IADC system,CNN was used to detect firearms and ammunition.The CNN model which is a Deep Learning technique consists of neural networks,most commonly applied to analyzing visual imagery has gained popularity for unstructured(images,videos)data classification.Additionally,this system generates an early warning through detection of ammunition before conditions become critical.Hence the faster and earlier the prediction,the lower the response time,loses and potential victims.The proposed IADC system provides better results than earlier published models like VGGNet,OverFeat-1,OverFeat-2,and OverFeat-3.展开更多
In recent years, microstrip antennas have been more widely applied in satellite communications, mobile phones, unmanned aerial vehicle （UAV）, and weapons. A micro-electro-mechanical systems-based （MEMS-based） high...In recent years, microstrip antennas have been more widely applied in satellite communications, mobile phones, unmanned aerial vehicle （UAV）, and weapons. A micro-electro-mechanical systems-based （MEMS-based） high-resistance silicon C-band microstrip antenna array has been designed for the intelligent ammunition. The center frequency is 4.5 GHz. A cavity has been designed in substrate to reduce the dielectric constant of silicon and high-resistance silicon has been used as the material of substrate to improve the gain of antenna. It is very easy to be manufactured by using MEMS technology because of the improved structure of the antenna. The results show that the gain of the antenna is 8 dB and voltage standing wave ratio （VSWR） is less than 2 by the analysis and simulation in high freauencv structure simulator （HFSS）.展开更多
文摘Security is a significant issue for everyone due to new and creative ways to commit cybercrime.The Closed-Circuit Television(CCTV)systems are being installed in offices,houses,shopping malls,and on streets to protect lives.Operators monitor CCTV;however,it is difficult for a single person to monitor the actions of multiple people at one time.Consequently,there is a dire need for an automated monitoring system that detects a person with ammunition or any other harmful material Based on our research and findings of this study,we have designed a new Intelligent Ammunition Detection and Classification(IADC)system using Convolutional Neural Network(CNN).The proposed system is designed to identify persons carrying weapons and ammunition using CCTV cameras.When weapons are identified,the cameras sound an alarm.In the proposed IADC system,CNN was used to detect firearms and ammunition.The CNN model which is a Deep Learning technique consists of neural networks,most commonly applied to analyzing visual imagery has gained popularity for unstructured(images,videos)data classification.Additionally,this system generates an early warning through detection of ammunition before conditions become critical.Hence the faster and earlier the prediction,the lower the response time,loses and potential victims.The proposed IADC system provides better results than earlier published models like VGGNet,OverFeat-1,OverFeat-2,and OverFeat-3.
基金supported by the Chinese PLA General Armament Department under Grant No.51318020305
文摘In recent years, microstrip antennas have been more widely applied in satellite communications, mobile phones, unmanned aerial vehicle （UAV）, and weapons. A micro-electro-mechanical systems-based （MEMS-based） high-resistance silicon C-band microstrip antenna array has been designed for the intelligent ammunition. The center frequency is 4.5 GHz. A cavity has been designed in substrate to reduce the dielectric constant of silicon and high-resistance silicon has been used as the material of substrate to improve the gain of antenna. It is very easy to be manufactured by using MEMS technology because of the improved structure of the antenna. The results show that the gain of the antenna is 8 dB and voltage standing wave ratio （VSWR） is less than 2 by the analysis and simulation in high freauencv structure simulator （HFSS）.
