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Automated harvesting systems rely heavily on precise and real-time fruit recognition, which is essential for improving efficiency and reducing labor costs. Strawberries, due to their delicate structure and complex growing environments, present unique challenges for automated recognition systems. Current methods predominantly utilize pixel-level and box-based approaches, which are insufficient for real-time applications due to their inability to accurately pinpoint strawberry locations. To address these limitations, this study proposes StrawSnake, a contour-based detection and segmentation network tailored for strawberries. By designing a strawberry-specific octagonal contour and employing deep snake convolution (DSConv) for boundary feature extraction, StrawSnake significantly enhances recognition accuracy and speed. The Multi-scale Feature Reinforcement Block (MFRB) further strengthens the model by focusing on crucial boundary features and aggregating multi-level contour information, which improves global context comprehension. The newly developed TongStraw_DB database and the public StrawDI_Db1 database, consisting of 1080 and 3100 high-resolution strawberry images with manually segmented ground truth contours, respectively, serves as a robust foundation for training and validation. The results indicate that StrawSnake achieves real-time recognition capabilities with high accuracy, outperforming existing methods in various comparative tests. Ablation studies confirm the effectiveness of the DSConv and MFRB modules in boosting performance. StrawSnake's integration into automated harvesting systems marks a substantial step forward in the field, promising enhanced precision and efficiency in strawberry recognition tasks. This innovation underscores the method's potential to transform automated harvesting technologies, making them more reliable and effective for practical applications. [ABSTRACT FROM AUTHOR]

This paper presents a novel unsupervised learning framework for estimating scene depth and camera pose from video sequences, fundamental to many high-level tasks such as 3D reconstruction, visual navigation, and augmented reality. Although existing unsupervised methods have achieved promising results, their performance suffers in challenging scenes such as those with dynamic objects and occluded regions. As a result, multiple mask technologies and geometric consistency constraints are adopted in this research to mitigate their negative impacts. Firstly, multiple mask technologies are used to identify numerous outliers in the scene, which are excluded from the loss computation. In addition, the identified outliers are employed as a supervised signal to train a mask estimation network. The estimated mask is then utilized to preprocess the input to the pose estimation network, mitigating the potential adverse effects of challenging scenes on pose estimation. Furthermore, we propose geometric consistency constraints to reduce the sensitivity of illumination changes, which act as additional supervised signals to train the network. Experimental results on the KITTI dataset demonstrate that our proposed strategies can effectively enhance the model's performance, outperforming other unsupervised methods. [ABSTRACT FROM AUTHOR]

Medical nitric oxide(NO)flow control system plays an important role in lowering pulmonary hypertension.The design requirements,overall scheme,delivery system and hardware circuits of a medical NO flow control system were introduced in this paper.Particularly,we proposed the design of NO delivery system and hardware circuits in detail.To deliver nitric oxide of a variable concentration,the designed system needs to work with a ventilator.The system can adjust and monitor the inhaled nitric oxide concentrations and send out sound and light alarms when the inhaled nitric oxide concentrations are out of the set range.To validate reliability and efficacy,we measured specifications such as linearity,stability and response time of the proposed NO flow control system by continuously administering nitric oxide into inspiratory circuit to deliver nitric oxide of variable concentrations to a test lung.The experiments showed that these specifications can meet the desired requirements.