Critical insights into modern hyperspectral image applications through deep learning
Hyperspectral imaging has shown tremendous growth over the past three decades.
Hyperspectral imaging was evolved through remote sensing. Along, with the technological …
Hyperspectral imaging was evolved through remote sensing. Along, with the technological …
Deep face recognition for biometric authentication
M Zulfiqar, F Syed, MJ Khan… - … conference on electrical …, 2019 - ieeexplore.ieee.org
Face is one of the most widely used biometrics for human identity authentication. Facial
recognition has remained an interesting and active research area in the past several …
recognition has remained an interesting and active research area in the past several …
Automatic target detection from satellite imagery using machine learning
Object detection is a vital step in satellite imagery-based computer vision applications such
as precision agriculture, urban planning and defense applications. In satellite imagery …
as precision agriculture, urban planning and defense applications. In satellite imagery …
A deep learning classification approach using high spatial satellite images for detection of built-up areas in rural zones: Case study of Souss-Massa region-Morocco
The buildings in the rural areas of Morocco exist in various shapes and sizes. They are
randomly distributed and are generally constructed of primary materials such as clay, wood …
randomly distributed and are generally constructed of primary materials such as clay, wood …
Deep learning for automated forgery detection in hyperspectral document images
Deep learning is revolutionizing the already rapidly develo** field of computer vision. The
convolutional neural network (CNN) is a state-of-the-art deep learning tool that learns high …
convolutional neural network (CNN) is a state-of-the-art deep learning tool that learns high …
Recent progress in object detection in satellite imagery: A review
K Bhil, R Shindihatti, S Mirza, S Latkar, YS Ingle… - … : Select Proceedings of …, 2022 - Springer
Algorithms based on deep learning are taking off as solutions to several problems in
numerous fields. Numerous deep learning architectures like convolutional neural networks …
numerous fields. Numerous deep learning architectures like convolutional neural networks …
Generalization of U-Net semantic segmentation for forest change detection in South Korea using airborne imagery
JC Pyo, K Han, Y Cho, D Kim, D ** - Forests, 2022 - mdpi.com
Forest change detection is essential to prevent the secondary damage occurring by
landslides causing profound results to the environment, ecosystem, and human society. The …
landslides causing profound results to the environment, ecosystem, and human society. The …
Machine vision inspection of electrical connectors based on improved Yolo v3
W Wu, Q Li - Ieee Access, 2020 - ieeexplore.ieee.org
Aiming at the problems of electrical connector defect detection, such as low automation, low
detection accuracy, slow detection speed, and poor robustness, an improved Yolo v3 …
detection accuracy, slow detection speed, and poor robustness, an improved Yolo v3 …
[책][B] Meta-heuristic optimization techniques: applications in engineering
This book is motivated by the fact that meta-heuristic optimization techniques have become
very popular among researchers and engineers over the last two decades. The widespread …
very popular among researchers and engineers over the last two decades. The widespread …
An automated and efficient convolutional architecture for disguise-invariant face recognition using noise-based data augmentation and deep transfer learning
Face recognition is diversely used in modern biometric and security applications. Most of the
current face recognition techniques show good results in a constrained environment …
current face recognition techniques show good results in a constrained environment …