435 citations · 744 across the 18 of their papers we have counts for
22 papers
EnergyFormer: Energy Attention with Fourier Embedding for Hyperspectral Image Classification
Saad Sohail, Muhammad Usama, Usman Ghous +3
Hyperspectral imaging (HSI) provides rich spectral-spatial information across hundreds of contiguous bands, enabling precise material discrimination in applications such as environ…
Hybrid State-Space and GRU-based Graph Tokenization Mamba for Hyperspectral Image Classification
Muhammad Ahmad, Muhammad Hassaan Farooq Butt, Muhammad Usama +4
Hyperspectral image (HSI) classification plays a pivotal role in domains such as environmental monitoring, agriculture, and urban planning. However, it faces significant challenges…
DiffFormer: a Differential Spatial-Spectral Transformer for Hyperspectral Image Classification
Muhammad Ahmad, Manuel Mazzara, Salvatore Distefano +2
Hyperspectral image classification (HSIC) has gained significant attention because of its potential in analyzing high-dimensional data with rich spectral and spatial information. I…
Transformer-Driven Active Transfer Learning for Cross-Hyperspectral Image Classification
Muhammad Ahmad, Francesco Mauro, Manuel Mazzara +3
Hyperspectral image (HSI) classification presents inherent challenges due to high spectral dimensionality, significant domain shifts, and limited availability of labeled data. To a…
Multi-head Spatial-Spectral Mamba for Hyperspectral Image Classification
Muhammad Ahmad, Muhammad Hassaan Farooq Butt, Muhammad Usama +3
Spatial-Spectral Mamba (SSM) improves computational efficiency and captures long-range dependencies, addressing Transformer limitations. However, traditional Mamba models overlook…
Spatial and Spatial-Spectral Morphological Mamba for Hyperspectral Image Classification
Muhammad Ahmad, Muhammad Hassaan Farooq Butt, Adil Mehmood Khan +6
Recent advancements in transformers, specifically self-attention mechanisms, have significantly improved hyperspectral image (HSI) classification. However, these models often suffe…
WaveMamba: Spatial-Spectral Wavelet Mamba for Hyperspectral Image Classification
Muhammad Ahmad, Muhammad Usama, Manuel Mazzara +1
Hyperspectral Imaging (HSI) has proven to be a powerful tool for capturing detailed spectral and spatial information across diverse applications. Despite the advancements in Deep L…
Transformers Fusion across Disjoint Samples for Hyperspectral Image Classification
Muhammad Ahmad, Manuel Mazzara, Salvatore Distifano
3D Swin Transformer (3D-ST) known for its hierarchical attention and window-based processing, excels in capturing intricate spatial relationships within images. Spatial-spectral Tr…
Pyramid Hierarchical Transformer for Hyperspectral Image Classification
Muhammad Ahmad, Muhammad Hassaan Farooq Butt, Manuel Mazzara +1
The traditional Transformer model encounters challenges with variable-length input sequences, particularly in Hyperspectral Image Classification (HSIC), leading to efficiency and s…
Importance of Disjoint Sampling in Conventional and Transformer Models for Hyperspectral Image Classification
Muhammad Ahmad, Manuel Mazzara, Salvatore Distifano
Disjoint sampling is critical for rigorous and unbiased evaluation of state-of-the-art (SOTA) models. When training, validation, and test sets overlap or share data, it introduces…
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…
3D/2D regularized CNN feature hierarchy for Hyperspectral image classification
Muhammad Ahmad, Manuel Mazzara, Salvatore Distefano
Convolutional Neural Networks (CNN) have been rigorously studied for Hyperspectral Image Classification (HSIC) and are known to be effective in exploiting joint spatial-spectral in…
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…
Hyperspectral Image Classification-Traditional to Deep Models: A Survey for Future Prospects
Muhammad Ahmad, Sidrah Shabbir, Swalpa Kumar Roy +7
Hyperspectral Imaging (HSI) has been extensively utilized in many real-life applications because it benefits from the detailed spectral information contained in each pixel. Notably…
An Open Source Solution for Smart Contract-based Parking
Nikolay Buldakov, Timur Khalilev, Salvatore Distefano +1
This paper discusses an open source solution to smart-parking in highly urbanized areas. Interviews have been conducted with domain experts, user stories defined and a system archi…
From DevOps to DevDataOps: Data Management in DevOps processes
Antonio Capizzi, Salvatore Distefano, Manuel Mazzara
DevOps is a quite effective approach for managing software development and operation, as confirmed by plenty of success stories in real applications and case studies. DevOps is now…
Anomaly Detection in DevOps Toolchain
Antonio Capizzi, Salvatore Distefano, Manuel Mazzara +3
The tools employed in the DevOps Toolchain generates a large quantity of data that is typically ignored or inspected only in particular occasions, at most. However, the analysis of…
A Reference Architecture for Smart and Software-defined Buildings
Manuel Mazzara, Ilya Afanasyev, Smruti R. Sarangi +2
The vision encompassing Smart and Software-defined Buildings (SSDB) is becoming more and more popular and its implementation is now more accessible due to the widespread adoption o…
Seeking Optimum System Settings for Physical Activity Recognition on Smartwatches
Muhammad Ahmad, Adil Mehmood Khan, Manuel Mazzara +1
Physical activity recognition (PAR) using wearable devices can provide valued information regarding an individual's degree of functional ability and lifestyle. In this regards, sma…
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…
Towards Anthropo-inspired Computational Systems: the Model
Michael W. Bridges, Salvatore Distefano, Manuel Mazzara +3
This paper proposes a model which aim is providing a more coherent framework for agents design. We identify three closely related anthropo-centered domains working on separate func…
A Cognitive Architecture for the Implementation of Emotions in Computing Systems
Jordi Vallverdú, Max Talanov, Salvatore Distefano +3
In this paper we present a new neurobiologically-inspired affective cognitive architecture: NEUCOGAR (NEUromodulating COGnitive ARchitecture). The objective of NEUCOGAR is the iden…