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State of the art content-based image retrieval algorithms owe their excellent performance to the rich semantics encoded in the deep activations of a convolutional neural network. The difference between these algorithms lies mostly in how activations are co ...
This study aimed to explore the value of synchrotron-based phase-contrast microcomputed tomography (micro-CT) in pulmonary vascular pathobiology. The microanatomy of the lung is complex with intricate branching patterns. Tissue sections are therefore diffi ...
Thanks to recent advancements in image processing and deep learning techniques, visual surface inspection in production lines has become an automated process as long as all the defects are visible in a single or a few images. However, it is often necessary ...
In this work, we resolve a big challenge that most current image quality metrics (IQMs) are unavailable across different image contents, especially simultaneously coping with natural scene (NS) images or screen content (SC) images. By comparison with exist ...
Modern machine learning methods and their applications in computer vision are known to crave for large amounts of training data to reach their full potential. Because training data is mostly obtained through humans who manually label samples, it induces a ...
Ecological surveys increasingly rely on large‐scale image datasets, typically terabytes of imagery for a single survey. The ability to collect this volume of data allows surveys of unprecedented scale, at the cost of expansive volumes of photo‐interpretati ...
Convolutional neural networks (CNNs) based approaches for semantic alignment and object landmark detection have improved their performance significantly. Current efforts for the two tasks focus on addressing the lack of massive training data through weakly ...
This report presents the software tools that will be available online to help users accurately segment ultra-thin sections of brain tissue in a large image to determine the section’s coordinates. In order to predict these coordinates, the goal was to use a ...
Recovering a person's height from a single image is important for virtual garment fitting, autonomous driving and surveillance. However, it is also very challenging without absolute scale information. Here, we examine the rarely addressed case, where camer ...
Achieving robust multi-person 2D body landmark localization and pose estimation is essential for human behavior and interaction understanding as encountered for instance in HRI settings. Accurate methods have been proposed recently, but they usually rely o ...