The Image Recognition Elite Talent Training Class is led by Ma Xiurong, the director of the Integration of Industry and Education Research Institute, along with several practical lecturers from the institute. This elite class exempts students from the artificial intelligence industry chain courses. In simple terms, image recognition involves using classification backbone networks such as VGG, ResNet, and MobileNet to develop image classification algorithms for various business domains’ visual classification tasks.
The teaching team of the Image Recognition Elite Talent Training Class includes senior software development engineer Wang Jinqing, who has 14 years of practical experience and has worked at companies like StarNet and NetDragon, and Lin Hong, a senior algorithm engineer with 10 years of practical experience at multiple enterprises. Image recognition employs classification backbone networks like VGG, ResNet, and MobileNet to develop image classification algorithms. The elite class precisely targets the export end of artificial intelligence R&D engineers and application engineers, aiming to cultivate proficient algorithm engineers.
The course targets the actual artificial intelligence industry chain, adopting a theoretical and practical combination model. First, instructors teach theory and demonstrate, followed by students practicing in class with instructors providing guidance and answering questions. On one hand, students can learn software operations and algorithm applications related to artificial intelligence; on the other hand, they can learn mainstream classification backbone networks and image classification algorithms, mastering the skills required for visual classification tasks in different fields.
Since the class started, there have been continuous inquiries from new students, and a positive interaction has developed between teachers and students, with a class satisfaction rate exceeding 75%.
The Image Recognition Elite Class is a very satisfying program for me. When I joined the elite class, my goal was to learn new things. The teachers are attentive in answering your questions, and the classmates are enthusiastic in discussions, so I learned a lot about the practical applications of image recognition. The learning process was quite enjoyable, with deep learning, machine learning, convolutional networks, loss functions, and the mysteries of artificial intelligence being gradually unveiled. The secrets of image recognition were eloquently explained. You might ask what the Image Recognition Elite Class has brought us; it is not only knowledge but also the enthusiasm of the teachers that has been passed on to us. It is not only experience but also the discussions that have enabled us to develop teamwork skills. The Image Recognition Elite Class insists on the integration of industry and education, which has greatly improved my practical abilities.
—— Jiang Kaichang, Class 1, Computer Science, AI Academy
I feel very honored to participate in this Image Recognition Elite Class. Throughout this process, I have gained a lot. I have truly felt my improvement, the expansion of knowledge, and the broadening of my horizons. I thank every teacher for their wonderful teaching. The classroom atmosphere is very strong, and everyone is highly motivated to learn.
During my time in this elite class, I felt fulfilled and satisfied. Through interactions with teachers and classmates, I gained many insights and realizations, deepening my understanding of the relevant technologies in image recognition, which ignited my passion and confidence to pursue excellence. I believe this process will greatly help my future development.
—— Liu Huiping, Class 1, Telecommunications, AI Academy
I am a junior student, facing the pressures of study and employment, and I was confused. Before joining the elite class, I did not know how the knowledge and skills I had mastered would play a role in my future work. Later, to break this awkward reality, I joined the image recognition elite class offered by the school. Now that the elite class course is more than halfway through, my deepest realization is that the image recognition elite class has a systematic teaching and training plan, which differs from traditional tedious theoretical knowledge transfer, focusing more on practical learning. In this application-oriented teaching model, I have learned a lot, including some new knowledge and professional skills, but more importantly, it has clarified how the skills I have mastered will play a role in my future work. It has also made my understanding of my career path clearer.
—— Ning Pengxiang, Class 1, Artificial Intelligence, AI Academy
Contributed by: Image Recognition Elite Talent Training Class
Edited by: Lian Fangfei (Student)
Reviewed by: Chen Yangyang (Teacher)
