[HTML][HTML] Review of image classification algorithms based on convolutional neural networks
L Chen, S Li, Q Bai, J Yang, S Jiang, Y Miao - Remote Sensing, 2021 - mdpi.com
Image classification has always been a hot research direction in the world, and the
emergence of deep learning has promoted the development of this field. Convolutional …
emergence of deep learning has promoted the development of this field. Convolutional …
A comprehensive survey of visual slam algorithms
Simultaneous localization and map** (SLAM) techniques are widely researched, since
they allow the simultaneous creation of a map and the sensors' pose estimation in an …
they allow the simultaneous creation of a map and the sensors' pose estimation in an …
Object detection and image segmentation with deep learning on earth observation data: A review-part i: Evolution and recent trends
Deep learning (DL) has great influence on large parts of science and increasingly
established itself as an adaptive method for new challenges in the field of Earth observation …
established itself as an adaptive method for new challenges in the field of Earth observation …
Identifying facemask-wearing condition using image super-resolution with classification network to prevent COVID-19
The rapid worldwide spread of Coronavirus Disease 2019 (COVID-19) has resulted in a
global pandemic. Correct facemask wearing is valuable for infectious disease control, but …
global pandemic. Correct facemask wearing is valuable for infectious disease control, but …
A review of convolutional neural network applied to fruit image processing
Agriculture has always been an important economic and social sector for humans. Fruit
production is especially essential, with a great demand from all households. Therefore, the …
production is especially essential, with a great demand from all households. Therefore, the …
Deterministic local interpretable model-agnostic explanations for stable explainability
Local Interpretable Model-Agnostic Explanations (LIME) is a popular technique used to
increase the interpretability and explainability of black box Machine Learning (ML) …
increase the interpretability and explainability of black box Machine Learning (ML) …
Deep learning meets hyperspectral image analysis: A multidisciplinary review
Modern hyperspectral imaging systems produce huge datasets potentially conveying a great
abundance of information; such a resource, however, poses many challenges in the …
abundance of information; such a resource, however, poses many challenges in the …
Object detection and image segmentation with deep learning on Earth observation data: A review—Part II: Applications
In Earth observation (EO), large-scale land-surface dynamics are traditionally analyzed by
investigating aggregated classes. The increase in data with a very high spatial resolution …
investigating aggregated classes. The increase in data with a very high spatial resolution …
Deep learning in forestry using uav-acquired rgb data: A practical review
Forests are the planet's main CO 2 filtering agent as well as important economical,
environmental and social assets. Climate change is exerting an increased stress, resulting …
environmental and social assets. Climate change is exerting an increased stress, resulting …