A state-of-the-art review on graph characterization and automated detection of road underground targets using ground-penetrating radar
W Liu, X Yang, Y Yan, J Zhang, R Heikkilä - Measurement, 2024 - Elsevier
The existing studies were summarized by the state-of-the-art review of the basic principle of
ground-penetrating radar (GPR), GPR atlas characterization of underground road targets …
ground-penetrating radar (GPR), GPR atlas characterization of underground road targets …
[PDF][PDF] The effectiveness of deep learning methods on groundnut disease detection
Early detection of plant diseases in the agricultural sector is considered an important goal to
increase productivity and minimize damage. This study deals with the use of deep learning …
increase productivity and minimize damage. This study deals with the use of deep learning …
Research on Rapeseed Seedling Counting Based on an Improved Density Estimation Method
Q Wang, C Li, L Huang, L Chen, Q Zheng, L Liu - Agriculture, 2024 - mdpi.com
The identification of seedling numbers is directly related to the acquisition of seedling
information, such as survival rate and emergence rate. It indirectly affects detection efficiency …
information, such as survival rate and emergence rate. It indirectly affects detection efficiency …
CNN-Based Classification of Acute Myeloid Leukemia Blood Samples
AR Ahmad, NA Zainudin, MDIM Radzi… - 2024 IEEE 14th …, 2024 - ieeexplore.ieee.org
Acute Myeloid Leukaemia (AML) diagnosis is often hampered by a lack of technology and
time-consuming procedures. Manual interpretation of blood sample images by radiologists …
time-consuming procedures. Manual interpretation of blood sample images by radiologists …
Classification of Rupiah Banknote for the Visually Impaired using Convolutional Neural Network with Custom Architecture and RMSProp Optimizer
Visual impairment is a condition that affects the sense of sight. In Indonesia, around 1.5% of
the 4 million people are blind. In their daily activities, the visually impaired rely on their …
the 4 million people are blind. In their daily activities, the visually impaired rely on their …
ED-YOLO: A Deep Learning and Edge Detection Based Turnout Switch Gap Monitor Method
A real-time monitoring method for turnout switch gaps based on deep learning and edge
detection, named EDYOLO, is proposed to accurately monitor the fastening status of …
detection, named EDYOLO, is proposed to accurately monitor the fastening status of …
[HTML][HTML] Dynamics of Lemon Crop Production in Tambo Grande, Piura: Implementation of Convolutional Neural Networks and Analysis of Risk Management …
L Meneses, M Ortega, M Rivas, P Fernández… - Engineering …, 2025 - mdpi.com
Lemon production in Piura, Peru faces climatic challenges such as droughts and El Niño.
This study uses satellite indices (NDVI and NDWI) and convolutional neural networks …
This study uses satellite indices (NDVI and NDWI) and convolutional neural networks …
[PDF][PDF] Efficient detection of tomato leaf diseases using optimized Compact Convolutional Transformers (CCT) Model
Tomato crops are highly susceptible to various leaf diseases, posing a significant threat to
agricultural yield and economic viability. Traditional disease detection methods, reliant on …
agricultural yield and economic viability. Traditional disease detection methods, reliant on …
Selective Kernel Spatial Feature Extraction based Deep Learning Approach for Identification and Classification of Archaeological Sites
SL Sajja, Z Alsalami, G Sunil, S Kumar… - 2024 International …, 2024 - ieeexplore.ieee.org
Deep Learning (DL) based identification and classification of archaeological sites are being
used progressively from satellite images obtained from Geographic Information System …
used progressively from satellite images obtained from Geographic Information System …