Technological revolutions in smart farming: Current trends, challenges & future directions
With increasing population, the demand for agricultural productivity is rising to meet the goal
of “Zero Hunger”. Consequently, farmers have optimized the agricultural activities in a …
of “Zero Hunger”. Consequently, farmers have optimized the agricultural activities in a …
Adventures in data analysis: A systematic review of Deep Learning techniques for pattern recognition in cyber-physical-social systems
Abstract Machine Learning (ML) and Deep Learning (DL) have achieved high success in
many textual, auditory, medical imaging, and visual recognition patterns. Concerning the …
many textual, auditory, medical imaging, and visual recognition patterns. Concerning the …
[PDF][PDF] CNN based automated weed detection system using UAV imagery.
MA Haq - Computer Systems Science & Engineering, 2022 - researchgate.net
The problem of weeds in crops is a natural problem for farmers. Machine Learning (ML),
Deep Learning (DL), and Unmanned Aerial Vehicles (UAV) are among the advanced …
Deep Learning (DL), and Unmanned Aerial Vehicles (UAV) are among the advanced …
Deep embedded hybrid CNN–LSTM network for lane detection on NVIDIA Jetson Xavier NX
In recent years, lane detection has become one of the most important factors in the progress
of intelligent vehicles. To deal with the challenging problem of low detection precision and …
of intelligent vehicles. To deal with the challenging problem of low detection precision and …
Medical image analysis using deep learning algorithms
M Li, Y Jiang, Y Zhang, H Zhu - Frontiers in Public Health, 2023 - frontiersin.org
In the field of medical image analysis within deep learning (DL), the importance of
employing advanced DL techniques cannot be overstated. DL has achieved impressive …
employing advanced DL techniques cannot be overstated. DL has achieved impressive …
Ten years of generative adversarial nets (GANs): a survey of the state-of-the-art
Generative adversarial networks (GANs) have rapidly emerged as powerful tools for
generating realistic and diverse data across various domains, including computer vision and …
generating realistic and diverse data across various domains, including computer vision and …
A machine learning method to quantitatively predict alpha phase morphology in additively manufactured Ti-6Al-4V
Abstracts Quantitatively defining the relationship between laser powder bed fusion (LPBF)
process parameters and the resultant microstructures for LPBF fabricated alloys is one of …
process parameters and the resultant microstructures for LPBF fabricated alloys is one of …
A contemporary review on deep learning models for drought prediction
Deep learning models have been widely used in various applications, such as image and
speech recognition, natural language processing, and recently, in the field of drought …
speech recognition, natural language processing, and recently, in the field of drought …
Prediction of summer daytime land surface temperature in urban environments based on machine learning
Abstract Land Surface Temperature (LST) is an important indicator of urban heat
environments and can be largely influenced by the morphology factors of cities. However …
environments and can be largely influenced by the morphology factors of cities. However …
Optimal deep generative adversarial network and convolutional neural network for rice leaf disease prediction
A Stephen, A Punitha, A Chandrasekar - The Visual Computer, 2024 - Springer
Rice which is a staple food crop in most Asian countries mainly suffers from higher yield loss
due to different factors, and one of the common factors that affect rice yield is rice leaf …
due to different factors, and one of the common factors that affect rice yield is rice leaf …