UrbanWatch: A 1-meter resolution land cover and land use database for 22 major cities in the United States
Abstract Very-high-resolution (VHR) land cover and land use (LCLU) is an essential
baseline data for understanding fine-scale interactions between humans and the …
baseline data for understanding fine-scale interactions between humans and the …
HFENet: hierarchical feature extraction network for accurate landcover classification
D Wang, R Yang, H Liu, H He, J Tan, S Li, Y Qiao… - Remote Sensing, 2022 - mdpi.com
Landcover classification is an important application in remote sensing, but it is always a
challenge to distinguish different features with similar characteristics or large-scale …
challenge to distinguish different features with similar characteristics or large-scale …
A novel multi-module approach to predict crime based on multivariate spatio-temporal data using attention and sequential fusion model
Forecasting crime is complex since several complicated aspects contribute to a crime.
Predicting crime becomes more challenging because of the enormous number of everyday …
Predicting crime becomes more challenging because of the enormous number of everyday …
[PDF][PDF] A Hybrid Deep Learning Intrusion Detection Model for Fog Computing Environment.
K Kalaivani, M Chinnadurai - Intelligent Automation & Soft …, 2021 - cdn.techscience.cn
Fog computing extends the concept of cloud computing by providing the services of
computing, storage, and networking connectivity at the edge between data centers in cloud …
computing, storage, and networking connectivity at the edge between data centers in cloud …
[PDF][PDF] Remote sensing image scene classification using dilated convolutional neural networks
Remote sensing image (RSI) scene classification has received growing attention from the
research community in recent days. Over the past few decades, with the rapid development …
research community in recent days. Over the past few decades, with the rapid development …
Scene classification of remotely sensed images using ensembled machine learning models
Classification of remote sensing images (RSIs) is a challenging task and has become an
active research topic in the field of remote sensing community. Over the past six decades …
active research topic in the field of remote sensing community. Over the past six decades …
An Efficient Deep Learning Framework for Multimedia Big Data Analytics
GSP Ghantasala, LR Sudha, TV Priya… - … Systems and Virtual …, 2022 - taylorfrancis.com
The rapid growth in the computing and mobile technologies, the Internet, social media,
storage mediums and the user-generated e-content have a great propensity towards the …
storage mediums and the user-generated e-content have a great propensity towards the …
Scene classification of remotely sensed images using optimized rsisc-16 net deep convolutional neural network model
Abstract Remote Sensing Image (RSI) analysis has seen a massive increase in popularity
over the last few decades, due to the advancement of deep learning models. A wide variety …
over the last few decades, due to the advancement of deep learning models. A wide variety …
[PDF][PDF] Comparative analysis of scene classification methods for remotely sensed images using various convolutional neural network
Remote sensing image (RSI) scene classification has received growing attention from the
research community in recent days. Over the past few decades, with the rapid development …
research community in recent days. Over the past few decades, with the rapid development …
Deep learning algorithm and its applications to ioT and computer vision
P Deepan, LR Sudha - Artificial Intelligence and IoT: Smart Convergence …, 2021 - Springer
Deep learning, which is the next phase of machine learning in recent decades, has
significantly changed the way in which computer systems interpret human-centric content …
significantly changed the way in which computer systems interpret human-centric content …