Anchor Retouching via Model Interaction for Robust Object Detection in Aerial Images

Object detection has made tremendous strides in computer vision. Small object detection with appearance degradation is a prominent challenge, especially for aerial observations. To collect sufficient positive/negative samples for heuristic training, most object detectors preset region anchors in order to calculate Intersection-over-Union (IoU) against the ground-truthed data. In this case, small objects are frequently abandoned or mislabeled. In this paper, we present an effective Dynamic Enhancement Anchor (DEA) network to construct a novel training sample generator. Different from the other state-of-the-art techniques, the proposed network leverages a sample discriminator to realize interactive sample screening between an anchor-based unit and an anchor-free unit to generate eligible samples. Besides, multi-task joint training with a conservative anchor-based inference scheme enhances the performance of the proposed model while reducing computational complexity. The proposed scheme supports both oriented and horizontal object detection tasks. Extensive experiments on two challenging aerial benchmarks (i.e., DOTA and HRSC2016) indicate that our method achieves state-of-the-art performance in accuracy with moderate inference speed and computational overhead for training. On DOTA, our DEA-Net which integrated with the baseline of RoI-Transformer surpasses the advanced method by 0.40% mean-Average-Precision (mAP) for oriented object detection with a weaker backbone network (ResNet-101 vs ResNet-152) and 3.08% mean-Average-Precision (mAP) for horizontal object detection with the same backbone. Besides, our DEA-Net which integrated with the baseline of ReDet achieves the state-of-the-art performance by 80.37%. On HRSC2016, it surpasses the previous best model by 1.1% using only 3 horizontal anchors

Understanding the Efforts of Cross-Border Search and Knowledge Co-Creation on Manufacturing Enterprises’ Service Innovation Performance

Based on the enterprise knowledge-based view, this study follows the basic logic of “knowledge acquisition-knowledge transformation-knowledge creation” to explore the effects of cross-border search and knowledge co-creation on the service innovation performance of manufacturing enterprises. Furthermore, compositional capability is introduced to investigate the moderator in the connection of knowledge co-recreation and service innovation performance. We collected 378 samples from the organizations that are taking servicizing transformation in China’s manufacturing industry. Then we applied structural equation modeling (SEM) to test our research model. The results reveal that both cross-border technological knowledge search and cross-border market knowledge search can significantly improve embedded knowledge co-creation and alliance-based knowledge creation of manufacturing enterprises, and then, directly and indirectly, boost service innovation performance. Compositional capability positively moderates the relationship between embedded knowledge co-creation and service innovation performance. This study provides theoretical and practical guidance for knowledge-based service innovation in China’s manufacturing industry

Research on the Relationship between Network Insight, Supply Chain Integration and Enterprise Performance

Based on the resource orchestration theory, this study built a research model to understand the effect of supply chain network insight and supply chain integration on enterprise performance. We also involved the contingency theory to investigate the moderating effect of environmental uncertainty on supply chain integration and enterprise performance. We collected the data samples from 405 enterprises and used the SEM approach to verify the model. Results demonstrated the direct path of network insight to promote enterprise performance, the indirect path of supply chain integration as a mediating factor, and the role of environmental uncertainty as a boundary condition for the relationship between supply chain integration and enterprise performance, thus making theoretical and practical contributions to the management of supply chain resources and relationships and the performance enhancement of manufacturing

Monitoring result analyses of high slope of five-step ship lock in the Three Gorges Project

AbstractThe construction of the double-lane five-step ship lock of the Three Gorges Project (TGP) was commenced in 1994, the excavation of the ship lock was completed by the end of 1999, and the ship lock was put in operation in June 2003. The side slopes of the ship lock are characterized by great height (170 m), steepness (70 m in height of upright slope), and great length (over 7000 m in total length). In association with the ship lock, the surrounding rocks in slope have a high potential to deform, with which the magnitude of deformation is restricted. Monitoring results show that the deformation of the five-step ship lock high slopes of the TGP primarily occurred in excavation period, and deformation tended to be stable and convergent during operation period, suggesting the allowable ranges of deformation. At present, the slopes and lock chambers are stable, and the ship lock works well under normal operation condition, enabling the social and economic benefits of the TGP

Genome-wide identification of the bHLH transcription factor family in Rosa persica and response to low-temperature stress

Background Basic helix-loop-helix (bHLH) transcription factors are involved in plant growth and development, secondary metabolism, and abiotic stress responses have been studied in a variety of plants. Despite their importance in plant biology, the roles and expression patterns of bHLH family genes in Rosa persica have not been determined. Methods In this study, the RbebHLH family genes were systematically analyzed using bioinformatics methods, and their expression patterns under low-temperature stress were analyzed by transcriptome and related physiological index measurements. Results In total, 142 RbebHLHs were identified in the genome of R. persica, distributed on seven chromosomes. Phylogenetic analysis including orthologous genes in Arabidopsis divided RbebHLHs into 21 subfamilies, with similar structures and motifs within a subfamily. A collinearity analysis revealed seven tandem duplications and 118 segmental duplications in R. persica and 127, 150, 151, 172, and 164 segmental duplications between R. persica and Arabidopsis thaliana, Prunus mume, Fragaria vesca, Rosa chinensis, and Prunus persica, respectively. A number of cis-regulatory elements associated with abiotic stress response and hormone response were identified in RbebHLHs, and 21 RbebHLHs have potential interactions with the CBF family. In addition, the expression results showed that part of bHLH may regulate the tolerance of R. persica to low-temperature stress through the jasmonic acid and pathway. Transcriptomic data showed that the expression levels of different RbebHLHs varied during overwintering, and the expression of some RbebHLHs was significantly correlated with relative conductivity and MDA content, implying that RbebHLHs play important regulatory roles in R. persica response to low-temperature stress. Overall, this study provides valuable insights into the study of RbebHLHs associated with low-temperature stress