Hongxiao Shi

Dr. Hongxiao Shi


Research Focus & Metrics

Academic Career Length

5Years (2022-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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5 June 2022 in Animals
Verified
Journal Article
Open access
PDF file
SSShuang Song
Shuang Song
TLtonghai hai Liu
tonghai hai Liu
HWHai Wang
Hai Wang
BHBagen Hasi
Bagen Hasi
CYChuangchuang Yuan
Chuangchuang Yuan
HSHongxiao Shi
Hongxiao Shi
Accurate identification of sheep is important for achieving precise animal management and welfare farming in large farms. In this study, a sheep face detection method based on YOLOv3 model pruning is proposed, abbreviated as YOLOv3-P in the text. The method is used to identify sheep in pastures, reduce stress and achieve welfare farming. Specifically, in this study, we chose to collect Sunit sheep face images from a certain pasture in Xilin Gol League Sunit Right Banner, Inner Mongolia, and used YOLOv3, YOLOv4, Faster R-CNN, SSD and other classical target recognition algorithms to train and compare the recognition results, respectively. Ultimately, the choice was made to optimize YOLOv3. The mAP was increased from 95.3% to 96.4% by clustering the anchor frames in YOLOv3 using the sheep face dataset. The mAP of the compressed model was also increased from 96.4% to 97.2%. The model size was also reduced to 1/4 times the size of the original model. In addition, we restructured the original dataset and performed a 10-fold cross-validation experiment with a value of 96.84% for mAP. The results show that clustering the anchor boxes and compressing the model using this dataset is an effective method for identifying sheep. The method is characterized by low memory requirement, high-recognition accuracy and fast recognition speed, which can accurately identify sheep and has important applications in precision animal management and welfare farming.

27 January 2022 in Plants
Verified
Journal Article
Open access
PDF file
HSHongxiao Shi
Hongxiao Shi
XWXinhong Wu
Xinhong Wu
HWHai Wang
Hai Wang
SHSibagen Ha
Sibagen Ha
TYTingting Yang
Tingting Yang
WLWen-hui Liu
Wen-hui Liu
Poa alpigena is a dominant grass species in alpine meadows, which is sensitive to environmental conditions. In this study, we analyzed the characteristics of the anatomical structure of the stems and leaves of Poa alpigena in overgrazed and enclosed conditions in order to determine the dwarfing morphological mechanism associated with overgrazing. The results show that leaf thickness, leaf epidermal thickness, epidermal cell area, and phloem thickness increased with increased grazing intensity (p < 0.05). In contrast, xylem thickness, mesophyll cell area, and guide wall thickness decreased with an increase in grazing intensity (p < 0.05). Mesophyll cell density was relatively unaffected by grazing intensity. Additionally, the plasticity indices of leaf area, upper epidermal cutin layer thickness, and leaf xylem thickness were higher than 0.5. The plasticity indices of stem tube diameter, epidermal cell size, and epidermal cuticle thickness were greater than 0.4. The results of our study indicate that the structural stem and leaf changes in Poa alpigena are induced by the water and mechanical stresses that occur under grazing conditions. Thus, plateau plants adapt to grazing stress by increasing the thickness of their leaves, cuticles, and phloem. The mesophyll cell area, as well as the stem epidermal cell area of Poa alpigena decreased in response to minor variations in grazing intensity, yet overgrazing did not change its density. However, overgrazing induced a shortening of the leaves and stems, indicating that overgrazing has a dwarfing effect on Poa alpigena.