Athanasios Tragakis
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View article: IGAF: Incremental Guided Attention Fusion for Depth Super-Resolution
IGAF: Incremental Guided Attention Fusion for Depth Super-Resolution Open
Accurate depth estimation is crucial for many fields, including robotics, navigation, and medical imaging. However, conventional depth sensors often produce low-resolution (LR) depth maps, making detailed scene perception challenging. To a…
View article: AI-Enabled Sensor Fusion of Time-of-Flight Imaging and mmWave for Concealed Metal Detection
AI-Enabled Sensor Fusion of Time-of-Flight Imaging and mmWave for Concealed Metal Detection Open
In the field of detection and ranging, multiple complementary sensing modalities may be used to enrich information obtained from a dynamic scene. One application of this sensor fusion is in public security and surveillance, where efficacy …
View article: AI-Enabled sensor fusion of time of flight imaging and mmwave for concealed metal detection
AI-Enabled sensor fusion of time of flight imaging and mmwave for concealed metal detection Open
In the field of detection and ranging, multiple complementary sensing modalities may be used to enrich the information obtained from a dynamic scene. One application of this sensor fusion is in public security and surveillance, whose effic…
View article: Is One GPU Enough? Pushing Image Generation at Higher-Resolutions with Foundation Models
Is One GPU Enough? Pushing Image Generation at Higher-Resolutions with Foundation Models Open
In this work, we introduce Pixelsmith, a zero-shot text-to-image generative framework to sample images at higher resolutions with a single GPU. We are the first to show that it is possible to scale the output of a pre-trained diffusion mod…
View article: Glfnet: Global-Local (Frequency) Filter Networks for Efficient Medical Image Segmentation
Glfnet: Global-Local (Frequency) Filter Networks for Efficient Medical Image Segmentation Open
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 replace the self-attention mechanism with a combination of gl…
View article: The Fully Convolutional Transformer for Medical Image Segmentation
The Fully Convolutional Transformer for Medical Image Segmentation Open
We propose a novel transformer model, capable of segmenting medical images of varying modalities. Challenges posed by the fine grained nature of medical image analysis mean that the adaptation of the transformer for their analysis is still…