1.9k citations · 3.2k across the 26 of their papers we have counts for
5 papers · 2 filters
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…
How to Learn More? Exploring Kolmogorov-Arnold Networks for Hyperspectral Image Classification
Ali Jamali, Swalpa Kumar Roy, Danfeng Hong +2
Convolutional Neural Networks (CNNs) and vision transformers (ViTs) have shown excellent capability in complex hyperspectral image (HSI) classification. However, these models requi…
Multi-dimension Transformer with Attention-based Filtering for Medical Image Segmentation
Wentao Wang, Xi Xiao, Mingjie Liu +5
The accurate segmentation of medical images is crucial for diagnosing and treating diseases. Recent studies demonstrate that vision transformer-based methods have significantly imp…
Reliable or Deceptive? Investigating Gated Features for Smooth Visual Explanations in CNNs
Soham Mitra, Atri Sukul, Swalpa Kumar Roy +2
Deep learning models have achieved remarkable success across diverse domains. However, the intricate nature of these models often impedes a clear understanding of their decision-ma…
GLFNET: Global-Local (frequency) Filter Networks for efficient medical image segmentation
Athanasios Tragakis, Qianying Liu, Chaitanya Kaul +5
We propose a novel transformer-style architecture called Global-Local Filter Network (GLFNet) for medical image segmentation and demonstrate its state-of-the-art performance. We re…