ReSTiNet : On improving the performance of Tiny-YOLO-Based CNN architecture for applications in human detection

• Main Authors: Sumit, Shahriar Shakir, Awang Rambli, Dayang Rohaya, Mirjalili, Seyedali, Ejaz, Muhammad Mudassir, Miah, Md Saef Ullah
• Format: Article
• Language: English
• Published: MDPI 2022
• Subjects: QA75 Electronic computers. Computer science; QA76 Computer software; T Technology (General); TA Engineering (General). Civil engineering (General)
• Online Access: http://umpir.ump.edu.my/id/eprint/37442/1/ReSTiNet_On%20improving%20the%20performance%20of%20tiny-yolo-based%20cnn%20architecture%20for%20applications%20in%20human%20detection.pdf; http://umpir.ump.edu.my/id/eprint/37442/; https://doi.org/10.3390/app12189331; https://doi.org/10.3390/app12189331

Human detection is a special application of object recognition and is considered one of the greatest challenges in computer vision. It is the starting point of a number of applications, including public safety and security surveillance around the world. Human detection technologies have advanced sig...