Deep learning in controlled environment agriculture: A review of recent advancements, challenges and prospects
Controlled environment agriculture (CEA) is an unconventional production system that is
resource efficient, uses less space, and produces higher yields. Deep learning (DL) has …
resource efficient, uses less space, and produces higher yields. Deep learning (DL) has …
Deep CNN-LSTM with self-attention model for human activity recognition using wearable sensor
Human Activity Recognition (HAR) systems are devised for continuously observing human
behavior-primarily in the fields of environmental compatibility, sports injury detection, senior …
behavior-primarily in the fields of environmental compatibility, sports injury detection, senior …
Climate Change impacts on Vegetable crops: a systematic review
Agriculture is a fundamental aspect of our society, providing food and resources for a
growing population. However, climate change is putting this sector at risk through rising …
growing population. However, climate change is putting this sector at risk through rising …
Interaction-enhanced and time-aware graph convolutional network for successive point-of-interest recommendation in traveling enterprises
Extensive user check-in data incorporating user preferences for location is collected through
Internet of Things (IoT) devices, including cell phones and other sensing devices in location …
Internet of Things (IoT) devices, including cell phones and other sensing devices in location …
Analysis of environmental factors using AI and ML methods
The main goal of this research paper is to apply a deep neural network model for time series
forecasting of environmental variables. Accurate forecasting of snow cover and NDVI are …
forecasting of environmental variables. Accurate forecasting of snow cover and NDVI are …
Bidirectional GRU networks‐based next POI category prediction for healthcare
Abstract The Corona Virus Disease 2019 has a great impact on public health and public
psychology. People stay at home for a long time and rarely go out. With the improvement of …
psychology. People stay at home for a long time and rarely go out. With the improvement of …
Prediction of ultimate bearing capacity of shallow foundations on cohesionless soil using hybrid lstm and rvm approaches: An extended investigation of …
This research presents the optimum performance model for predicting the shallow
foundation ultimate bearing capacity (UBC). Twenty-one models are employed, trained …
foundation ultimate bearing capacity (UBC). Twenty-one models are employed, trained …
A generative adversarial network for synthetization of regions of interest based on digital mammograms
Deep learning (DL) models are becoming pervasive and applicable to computer vision,
image processing, and synthesis problems. The performance of these models is often …
image processing, and synthesis problems. The performance of these models is often …
BMAE-Net: A data-driven weather prediction network for smart agriculture
Weather is an essential component of natural resources that affects agricultural production
and plays a decisive role in deciding the type of agricultural production, planting structure …
and plays a decisive role in deciding the type of agricultural production, planting structure …
A pavement distresses identification method optimized for YOLOv5s
K Guo, C He, M Yang, S Wang - Scientific Reports, 2022 - nature.com
Automatic detection and recognition of pavement distresses is the key to timely repair of
pavement. Repairing the pavement distresses in time can prevent the destruction of road …
pavement. Repairing the pavement distresses in time can prevent the destruction of road …