This project provides the image datasets and codes used in the paper “Deep learning for three-dimensional segmentation of electron microscopy images of complex ...
Deep learning architectures for the classification of images have shown outstanding results in a variety of disciplines, including dermatology. The expectations generated by deep learning for, e.g., ...
Classification of histopathological images of cancer is challenging even for well-trained professionals, due to the fine-grained variability of the disease. Deep Convolutional Neural Networks (CNNs) ...
P. Ambrosini, D. Ruijters, W.J. Niessen, A. Moelker and T. van Walsum: Fully Automatic and Real-Time Catheter Segmentation in X-Ray Fluoroscopy. The 20th International Conference on Medical Image ...
Construction sites are dangerous due to the complex interaction of workers with equipment, building materials, vehicles, etc. As a kind of protective gear, hardhats are crucial for the safety of ...
Computational drug discovery provides an efficient tool for helping large-scale lead molecule screening. One of the major tasks of lead discovery is identifying molecules with promising binding ...
I finished my postdoc study at June 30, 2018. After that I joined Pennsylvania State University as an assistant professor. My current website is here. My research interests lie in algorithm design and ...
Popular neural networks for image-processing problems often contain many different operations, multiple layers of connections, and a large number of trainable parameters, often exceeding several ...
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