Beibei Li

Title: Beibei Li: Innovator in Convolutional Neural Networks

Introduction

Beibei Li is a prominent inventor based in Yantai, China. He has made significant contributions to the field of technology, particularly in the area of convolutional neural networks. His innovative approach has led to the development of a unique method for identifying individuals of the species oplegnathus punctatus.

Latest Patents

Beibei Li holds a patent titled "Method for identifying individuals of oplegnathus punctatus based on convolutional neural network." This patent describes a method that utilizes a convolutional neural network to identify individual fish. The process involves three continuous convolutional layers and an average pooling layer for target initial positioning. A region of feature interest point is obtained, and a hyperparameter candidate box is set to determine the region, thus approximating the target object's position. The II_Net backbone convolutional neural network consists of six convolutional layers and four pooling layers, incorporating a LeakyReLU activation function in the first convolutional layer. The model also employs a genetic algorithm to enhance data transmission between layers, allowing for effective identification of the oplegnathus punctatus using test data.

Career Highlights

Beibei Li is affiliated with Ludong University, where he continues to advance his research and innovation in the field of neural networks. His work has garnered attention for its practical applications in identifying marine species, showcasing the intersection of technology and biology.

Collaborations

Beibei Li has collaborated with notable colleagues, including Jun Yue and Shixiang Jia. Their combined expertise contributes to the advancement of research in convolutional neural networks and their applications.

Conclusion

Beibei Li's contributions to the field of convolutional neural networks exemplify the potential of technology in biological identification. His innovative methods and collaborative efforts continue to push the boundaries of research and application in this exciting area.