This paper focuses on the needs of automation professional talent cultivation in the context of the construction of new engineering disciplines, and takes the course “Freshman Engineering Experience” as the research object, and carries out a systematic exploration of teaching reform in response to the problems of insufficient professional cognition and disconnection between theory and practice that exist in the current engineering education. By restructuring the curriculum system, innovating teaching methods and optimizing the practice platform, a progressive cultivation mode of “Cognition-Practice-Innovation” has been constructed. In curriculum design, the combination of professiona... More >

With the progressive advancement of remote sensing image technology, its application in the agricultural domain is becoming increasingly prevalent. Both cultivation and transportation processes can greatly benefit from utilizing remote sensing images to ensure adequate food supply. However, such images often exist in harsh environments with many gaps and dense distribution, which poses major challenges to traditional target detection methods. The frequent missed detections and inaccurate bounding boxes severely constrain the further analysis and application of remote sensing images within the agricultural sector. This study presents an enhanced version of the YOLO algorithm, specifically tai... More >

Frontiers in Educational Innovation and Research (FEIR) journal marks a significant milestone in educational change and development, particularly in the context of digital transformation and technology’s pervasive impact on daily life. FEIR is dedicated to fostering a community of scholarly inquiry and innovation within the educational sector. The journal focuses on pioneering research and innovative practices that have the potential to enhance educational outcomes and experiences. By addressing challenges such as personalized learning, educational technology integration, lifelong learning, and accommodating diverse student needs, FEIR aims to provide a diverse platform for expert insight... More >

Maneuvering target tracking, as a core task in multi-sensor information fusion, is widely used in unmanned vehicles, missile navigation, and underwater ship localization, where real-time and robust state estimation is critical. Due to the uncertainty of the moving characteristics of maneuvering targets and the low sensor measurement accuracy, trajectory tracking has always been an open research problem and challenging work. This paper proposes a Bayesian-inspired stacked LSTM fusion network (SLSTM) for uncertain motion characteristics. The network consists of two LSTM fusion networks with stacked serial relationships, one of which is used to predict the movement dynamics, and the other is us... More >