Fulong Liang
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View article: TomaFDNet: A multiscale focused diffusion-based model for tomato disease detection
TomaFDNet: A multiscale focused diffusion-based model for tomato disease detection Open
Introduction Tomatoes are one of the most economically significant crops worldwide, with their yield and quality heavily impacted by foliar diseases. Effective detection of these diseases is essential for enhancing agricultural productivit…
View article: WPS-Dataset: A Benchmark for Wood Plate Segmentation in Bark Removal Processing
WPS-Dataset: A Benchmark for Wood Plate Segmentation in Bark Removal Processing Open
Wood plate bark removal processing is critical for ensuring the quality of wood processing and its products. To address the issue of lack of datasets available for the application of deep learning methods to this field, and to fill the res…
View article: Development and Testing of a Wood Panels Bark Removal Equipment Based on Deep Learning
Development and Testing of a Wood Panels Bark Removal Equipment Based on Deep Learning Open
Attempting to apply deep learning methods to wood panels bark removal equipment to enhance the quality and efficiency of bark removal is a significant and challenging endeavor. This study develops and tests a deep learning-based wood panel…
View article: DRR-YOLO: A Multiscale Wood Surface Defect Detection Method Based on Improved YOLOv8
DRR-YOLO: A Multiscale Wood Surface Defect Detection Method Based on Improved YOLOv8 Open
Wood surface defect detection technology offers the advantages of being non-destructive, rapid, accurate, and economical. It plays a crucial role in wood grade sorting, defect detection, improving the quality of sawn timber, and accelerati…
View article: SiM-YOLO: A Wood Surface Defect Detection Method Based on the Improved YOLOv8
SiM-YOLO: A Wood Surface Defect Detection Method Based on the Improved YOLOv8 Open
Wood surface defect detection is a challenging task due to the complexity and variability of defect types. To address these challenges, this paper introduces a novel deep learning approach named SiM-YOLO, which is built upon the YOLOv8 obj…
View article: An Efficient and Accurate Surface Defect Detection Method for Wood Based on Improved YOLOv8
An Efficient and Accurate Surface Defect Detection Method for Wood Based on Improved YOLOv8 Open
Accurate detection of wood surface defects plays a pivotal role in enhancing wood grade sorting precision, maintaining high standards in wood processing quality, and safeguarding forest resources. This paper introduces an efficient and pre…
View article: BPN-YOLO: A Novel Method for Wood Defect Detection Based on YOLOv7
BPN-YOLO: A Novel Method for Wood Defect Detection Based on YOLOv7 Open
The detection of wood defect is a crucial step in wood processing and manufacturing, determining the quality and reliability of wood products. To achieve accurate wood defect detection, a novel method named BPN-YOLO is proposed. The ordina…
View article: WPS-Dataset: A benchmark for wood plate segmentation in bark removal processing
WPS-Dataset: A benchmark for wood plate segmentation in bark removal processing Open
Using deep learning methods is a promising approach to improving bark removal efficiency and enhancing the quality of wood products. However, the lack of publicly available datasets for wood plate segmentation in bark removal processing po…
View article: WPS-Dataset: A benchmark for wood plate segmentation in bark removal processing
WPS-Dataset: A benchmark for wood plate segmentation in bark removal processing Open
Using deep learning methods is a promising approach to improving bark removal efficiency and enhancing the quality of wood products. However, the lack of publicly available datasets for wood plate segmentation in bark removal processing po…
View article: ODCA-YOLO: An Omni-Dynamic Convolution Coordinate Attention-Based YOLO for Wood Defect Detection
ODCA-YOLO: An Omni-Dynamic Convolution Coordinate Attention-Based YOLO for Wood Defect Detection Open
Accurate detection of wood defects plays a crucial role in optimizing wood utilization, minimizing corporate expenses, and safeguarding precious forest resources. To achieve precise identification of surface defects in wood, we present a n…
View article: Development of an Improved YOLOv7-Based Model for Detecting Defects on Strip Steel Surfaces
Development of an Improved YOLOv7-Based Model for Detecting Defects on Strip Steel Surfaces Open
The detection of defects on the surface is of great importance for both the production and the application of strip steel. In order to detect the defects accurately, an improved YOLOv7-based model for detecting strip steel surface defects …
View article: USP52 inhibits cell proliferation by stabilizing PTEN protein in non-small cell lung cancer
USP52 inhibits cell proliferation by stabilizing PTEN protein in non-small cell lung cancer Open
Non-small cell lung cancer (NSCLC) is the most common subtype of lung cancer. Ubiquitination is closely related to the development of lung cancer. However, the biological importance of newly discovered ubiquitin-specific peptidase (USP) 52…
View article: miR‑128‑3p serves as an oncogenic microRNA in osteosarcoma cells by downregulating ZC3H12D
miR‑128‑3p serves as an oncogenic microRNA in osteosarcoma cells by downregulating ZC3H12D Open
Osteosarcoma is the second leading cause of cancer-associated mortality worldwide in children and adolescents. ZC3H12D has been shown to negatively regulate Toll-like receptor signaling and serves as a possible tumor suppressor gene. Micro…