- Tytuł:
- An AI & ML based detection & identification in remote imagery: state-of-the-art
- Autorzy:
-
Hashmi, Hina
Dwivedi, Rakesh
Kumar, Anil - Powiązania:
- https://bibliotekanauki.pl/articles/2141786.pdf
- Data publikacji:
- 2021
- Wydawca:
- Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
- Tematy:
-
convolutional neural network
remote sensed imagery
object detection
artificial intelligence
feature extraction
deep learning
machine learning - Opis:
- Remotely sensed images and their allied areas of application have been the charm for a long time among researchers. Remote imagery has a vast area in which it is serving and achieving milestones. From the past, after the advent of AL, ML, and DL-based computing, remote imagery is related techniques for processing and analyzing are continuously growing and offering countless services like traffic surveillance, earth observation, land surveying, and other agricultural areas. As Artificial intelligence has become the charm of researchers, machine learning and deep learning have been proven as the most commonly used and highly effective techniques for object detection. AI & ML-based object segmentation & detection makes this area hot and fond to the researchers again with the opportunities of enhanced accuracy in the same. Several researchers have been proposed their works in the form of research papers to highlight the effectiveness of using remotely sensed imagery for commercial purposes. In this article, we have discussed the concept of remote imagery with some preprocessing techniques to extract hidden and fruitful information from them. Deep learning techniques applied by various researchers along with object detection, object recognition are also discussed here. This literature survey is also included a chronological review of work done related to detection and recognition using deep learning techniques.
- Źródło:
-
Journal of Automation Mobile Robotics and Intelligent Systems; 2021, 15, 4; 3-17
1897-8649
2080-2145 - Pojawia się w:
- Journal of Automation Mobile Robotics and Intelligent Systems
- Dostawca treści:
- Biblioteka Nauki
Artykuł