435 citations · 529 across the 13 of their papers we have counts for
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Attention Mechanism Meets with Hybrid Dense Network for Hyperspectral Image Classification
Muhammad Ahmad, Adil Mehmood Khan, Manuel Mazzara +3
Convolutional Neural Networks (CNN) are more suitable, indeed. However, fixed kernel sizes make traditional CNN too specific, neither flexible nor conducive to feature learning, th…
What augmentations are sensitive to hyper-parameters and why?
Ch Muhammad Awais, Imad Eddine Ibrahim Bekkouch
We apply augmentations to our dataset to enhance the quality of our predictions and make our final models more resilient to noisy data and domain drifts. Yet the question remains,…
Hyperspectral Image Classification: Artifacts of Dimension Reduction on Hybrid CNN
Muhammad Ahmad, Sidrah Shabbir, Rana Aamir Raza +3
Convolutional Neural Networks (CNN) has been extensively studied for Hyperspectral Image Classification (HSIC) more specifically, 2D and 3D CNN models have proved highly efficient…
Anomaly Detection based on Zero-Shot Outlier Synthesis and Hierarchical Feature Distillation
Adín Ramírez Rivera, Adil Khan, Imad E. I. Bekkouch +1
Anomaly detection suffers from unbalanced data since anomalies are quite rare. Synthetically generated anomalies are a solution to such ill or not fully defined data. However, synt…
Multi-label Class-imbalanced Action Recognition in Hockey Videos via 3D Convolutional Neural Networks
Konstantin Sozykin, Stanislav Protasov, Adil Khan +2
Automatic analysis of the video is one of most complex problems in the fields of computer vision and machine learning. A significant part of this research deals with (human) activi…
Segmented and Non-Segmented Stacked Denoising Autoencoder for Hyperspectral Band Reduction
Muhammad Ahmad, Asad Khan, Adil Mehmood Khan +1
Hyperspectral image analysis often requires selecting the most informative bands instead of processing the whole data without losing the key information. Existing band reduction (B…