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Detection of curvilinear structures in images has long been of interest. One of the most challenging aspects of this problem is inferring the graph representation of the curvilinear network. Most existing delineation approaches first perform binary segment ...
Recent advances have shown the great power of deep convolutional neural networks (CNN) to learn the relationship between low and high-resolution image patches. However, these methods only take a single-scale image as input and require large amount of data ...
Though deep learning (DL) algorithms are very powerful for image processing tasks, they generally require a lot of data to reach their full potential. Furthermore, there is no straightforward way to impose various properties, given by the prior knowledge a ...
Imaging the inner ear microanatomy is of great importance for the assessment of the state of the cells responsible for sound detection. Hearing disorders are mainly due to a malfunction of the cochlea, the bone containing the cells inside the inner ear. Un ...
Ongoing advances in imaging techniques create new demands regarding the analysis of images in medicine and biology. Image segmentation is a key step of many image analysis pipelines and its proper execution is a particularly challenging task. This thesis i ...
Due to their wide field of view, omnidirectional cameras are frequently used by autonomous vehicles, drones and robots for navigation and other computer vision tasks. The images captured by such cameras, are often analyzed and classified with techniques de ...
We propose a low-power image sensor with a motion-based triggering feature for the Internet of Things (IoT) applications. The sensor supports the near-pixel [within analog-to-digital converter (ADC)] motion-detection mode run on a heavily subsampled frame ...
Semantic segmentation algorithms that can robustly segment objects across multiple camera viewpoints are crucial for assuring navigation and safety in emerging applications such as autonomous driving. Existing algorithms treat each image in isolation, but ...
As IoT is increasingly integrated into our everyday life, the demand for different sensor modalities, especially imaging, is rising. IoT imagers are often compact and have small form-factor batteries and thus must be designed with both low power (improving ...
Objective quality assessment of compressed images is very useful in many applications. In this paper we present an objective quality metric that is better tuned to evaluate the quality of images distorted by compression artifacts. A deep convolutional neur ...
