Face Recognition Entrance System
by Nero 錢振宇
PROJECT BY
Nero 錢振宇
Penang
Joined August 2018
About Me
畢業于馬來西亞理科大學機械工程系。21歲聯合創辦了校内自行車服務中心 Dr.Bike，為超過7000名學生提供騎行服務。25歲離開熟悉的機械領域進入視頻分析行業，為零售和廣告提供數據分析服務， 協助零售業和廣告業進圖大數據時代。同年創立了人工智能分享社群 Penang School of AI, 培養北馬區人工智能技術分享文化。 Graduated from USM, Bachelor of... See More
ABOUT PROJECT
Face Recognition Entrance System
Face recognition system is a technology capable of identifying or verifying a person from digital image or video frame.
By using deep learning technology, face recognition system compares selected facial features from the given image with faces within database. This can be used in security system and compared to other biometrics identification like fingerprint.
The benefit of face recognition is fast identifying and non-contact identification which fingerprint cannot do this.
Face Recognition System is built for personal verification. This first software includes Face Comparison, Face Detection and Face Tracking. Admin can preload an image from database and capture a customer photo using webcam.
This system can analysis the facial feature of the user and display the confidence in percentage. This can be two factor authorization process other than fingerprint.
We build entrance access system and apply face recognition technology. Face Recognition can verify identity of visitos in seconds with benefit of fast and no physical contact.
This can be widely use in entrance system, attendance system as well as train station entrance system.
What make us different from others
- The great product would be the combination between software, service and hardware. Thus, We build the whole system, from software to AI algorithm.
- We are not relied on the other API because we have our own Face Recognition API which can reach up to 99.67%
- Our system can be deployed to offline usage.
Our Team
Part of TimeLine
Budget Plan
50% for software and hardware integration
30% for technical support
20% for maintance
人脸识别门禁系统
人脸识别系统是一种能够在图像和视频中识别和验证个人身份的技术。通过使用深度学习，人脸识别系统会将所选择的图像的面部特征与数据库内的面部特征进行对比。这项技术可以应用于安全防护系统，甚至能媲美其他生物识别系统（比如指纹识别）。人脸识别的特点是快速辨别和无接触验证，而这些特点是指纹验证所无法达到的。
人脸识别技术广泛应用在个人验证里，其中的技术包括人脸对比，人脸检测以及人脸追踪。管理员可以使用电脑摄像头来获取方用户图像，然后将图像上载入数据库里。这系统将会比对访客的图像和数据库里的图像， 然后以百分比显示现实的程度。因此，人脸识别可以成为双重认证中的一项有效技术。
我们建立了个基于人脸识别技术的门禁系统。这项技术能有效的快速，并且无物理接触地识别访客的个人身份。我们相信这项技术能够应用在大多数的门禁系统，登入系统甚至火车乘客登入等等。
我们有什么与众不同
- 一套良好的产品需要统合软件，服务和硬件。因此，我们建立全栈系统设计，从人工智算法到软件数据库都是自助设计。
- 我们不依赖于其他网络人脸识别系统接口。我们拥有自己的云端接口，人脸识别准确可以达到 99.67%。
- 我们的系统可以不依赖于网络，安装于线下应用。
我们的团队
部分开发进度表
预算案
50% 用于整合硬件与软件
30% 用于技术支援
20% 用于系统维护
RISKS AND CHALLENGES
We have the technology and experience in doing the visionrecognition system but we need fund to do the integration between software and hardware.
我们拥有建立视觉识别系统的经验和技术，但是我们需要募资足够的基金去做软件与硬件的整合。
Nero 錢振宇
Nero 錢振宇
Penang
Joined August 2018
About Me
畢業于馬來西亞理科大學機械工程系。21歲聯合創辦了校内自行車服務中心 Dr.Bike，為超過7000名學生提供騎行服務。25歲離開熟悉的機械領域進入視頻分析行業，為零售和廣告提供數據分析服務， 協助零售業和廣告業進圖大數據時代。同年創立了人工智能分享社群 Penang School of AI, 培養北馬區人工智能技術分享文化。 Graduated from USM, Bachelor of Mechanical Engineering. When he was 21, he established first business in campus, Dr. Bike to provide cycling and repairing service for more than 7000 students. He established WyseTime when he was 25 to provide video analytic and facial recognition surveillance to promote AI and big data. Also, he organized Penang School of AI to build up AI knowledge sharing community in Northern Malaysia.
Rewards
Support RM100 or more
十分感谢您的支持，我们会寄一张感恩状予您，谢谢您的支持。
Support RM1,000 or more
十分感谢您的支持，我们将会赠予一份特别纪念品给您，以表谢您对我们的支持。
Support RM2,000 or more
万分感谢您的协助，我们会赠送一份感谢状以及一份特别纪念品给予您。谢谢您的慷慨解囊。
Support RM5,000 or more
万分感谢您的支持，我们将会赠送一份感恩状，一份特别纪念品以及一份秘密电子纪念品予您，以感谢您给予我们的大力支持。
PROJECT BY
Nero 錢振宇
Penang
Joined August 2018
About Me
畢業于馬來西亞理科大學機械工程系。21歲聯合創辦了校内自行車服務中心 Dr.Bike，為超過7000名學生提供騎行服務。25歲離開熟悉的機械領域進入視頻分析行業，為零售和廣告提供數據分析服務， 協助零售業和廣告業進圖大數據時代。同年創立了人工智能分享社群 Penang School of AI, 培養北馬區人工智能技術分享文化。 Graduated from USM, Bachelor of... See More
ABOUT PROJECT
Face Recognition Entrance System
Face recognition system is a technology capable of identifying or verifying a person from digital image or video frame.
By using deep learning technology, face recognition system compares selected facial features from the given image with faces within database. This can be used in security system and compared to other biometrics identification like fingerprint.
The benefit of face recognition is fast identifying and non-contact identification which fingerprint cannot do this.
Face Recognition System is built for personal verification. This first software includes Face Comparison, Face Detection and Face Tracking. Admin can preload an image from database and capture a customer photo using webcam.
This system can analysis the facial feature of the user and display the confidence in percentage. This can be two factor authorization process other than fingerprint.
We build entrance access system and apply face recognition technology. Face Recognition can verify identity of visitos in seconds with benefit of fast and no physical contact.
This can be widely use in entrance system, attendance system as well as train station entrance system.
What make us different from others
- The great product would be the combination between software, service and hardware. Thus, We build the whole system, from software to AI algorithm.
- We are not relied on the other API because we have our own Face Recognition API which can reach up to 99.67%
- Our system can be deployed to offline usage.
Our Team
Part of TimeLine
Budget Plan
50% for software and hardware integration
30% for technical support
20% for maintance
人脸识别门禁系统
人脸识别系统是一种能够在图像和视频中识别和验证个人身份的技术。通过使用深度学习，人脸识别系统会将所选择的图像的面部特征与数据库内的面部特征进行对比。这项技术可以应用于安全防护系统，甚至能媲美其他生物识别系统（比如指纹识别）。人脸识别的特点是快速辨别和无接触验证，而这些特点是指纹验证所无法达到的。
人脸识别技术广泛应用在个人验证里，其中的技术包括人脸对比，人脸检测以及人脸追踪。管理员可以使用电脑摄像头来获取方用户图像，然后将图像上载入数据库里。这系统将会比对访客的图像和数据库里的图像， 然后以百分比显示现实的程度。因此，人脸识别可以成为双重认证中的一项有效技术。
我们建立了个基于人脸识别技术的门禁系统。这项技术能有效的快速，并且无物理接触地识别访客的个人身份。我们相信这项技术能够应用在大多数的门禁系统，登入系统甚至火车乘客登入等等。
我们有什么与众不同
- 一套良好的产品需要统合软件，服务和硬件。因此，我们建立全栈系统设计，从人工智算法到软件数据库都是自助设计。
- 我们不依赖于其他网络人脸识别系统接口。我们拥有自己的云端接口，人脸识别准确可以达到 99.67%。
- 我们的系统可以不依赖于网络，安装于线下应用。
我们的团队
部分开发进度表
预算案
50% 用于整合硬件与软件
30% 用于技术支援
20% 用于系统维护
RISKS AND CHALLENGES
We have the technology and experience in doing the visionrecognition system but we need fund to do the integration between software and hardware.
我们拥有建立视觉识别系统的经验和技术，但是我们需要募资足够的基金去做软件与硬件的整合。
Nero 錢振宇
Nero 錢振宇
Penang
Joined August 2018
About Me
畢業于馬來西亞理科大學機械工程系。21歲聯合創辦了校内自行車服務中心 Dr.Bike，為超過7000名學生提供騎行服務。25歲離開熟悉的機械領域進入視頻分析行業，為零售和廣告提供數據分析服務， 協助零售業和廣告業進圖大數據時代。同年創立了人工智能分享社群 Penang School of AI, 培養北馬區人工智能技術分享文化。 Graduated from USM, Bachelor of Mechanical Engineering. When he was 21, he established first business in campus, Dr. Bike to provide cycling and repairing service for more than 7000 students. He established WyseTime when he was 25 to provide video analytic and facial recognition surveillance to promote AI and big data. Also, he organized Penang School of AI to build up AI knowledge sharing community in Northern Malaysia.
project.REWARDS
Support RM100 or more
十分感谢您的支持，我们会寄一张感恩状予您，谢谢您的支持。
Support RM1,000 or more
十分感谢您的支持，我们将会赠予一份特别纪念品给您，以表谢您对我们的支持。
Support RM2,000 or more
万分感谢您的协助，我们会赠送一份感谢状以及一份特别纪念品给予您。谢谢您的慷慨解囊。
Support RM5,000 or more
万分感谢您的支持，我们将会赠送一份感恩状，一份特别纪念品以及一份秘密电子纪念品予您，以感谢您给予我们的大力支持。
Contact Nero 錢振宇
- RM2,000
- RM5,000
- Just support