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Building Brain Tumor Segmentation Networks with User-Assisted Filter Estimation and Selection
Brain tumor image segmentation is a challenging research topic in which deep-learning models have presented the best results.
CNN Filter Learning from Drawn Markers for the Detection of Suggestive Signs of COVID-19 in CT Images
Here we propose a method that does not require either large annotated datasets or backpropagation to estimate the filters of a convolutional neural network (CNN).
Hierarchical Learning Using Deep Optimum-Path Forest
Bag-of-Visual Words (BoVW) and deep learning techniques have been widely used in several domains, which include computer-assisted medical diagnoses.
Convolutional Neural Networks from Image Markers
A technique named Feature Learning from Image Markers (FLIM) was recently proposed to estimate convolutional filters, with no backpropagation, from strokes drawn by a user on very few images (e. g., 1-3) per class, and demonstrated for coconut-tree image classification.
Deploying machine learning to assist digital humanitarians: making image annotation in OpenStreetMap more efficient
Locating populations in rural areas of developing countries has attracted the attention of humanitarian mapping projects since it is important to plan actions that affect vulnerable areas.
Correcting rural building annotations in OpenStreetMap using convolutional neural networks
Rural building mapping is paramount to support demographic studies and plan actions in response to crisis that affect those areas.
An Iterative Spanning Forest Framework for Superpixel Segmentation
Superpixel segmentation has become an important research problem in image processing.
SEGMENT3D: A Web-based Application for Collaborative Segmentation of 3D images used in the Shoot Apical Meristem
SEGMENT3D is a comprehensive application that can be applied to other 3D imaging modalities and general objects.
Cell Segmentation in 3D Confocal Images using Supervoxel Merge-Forests with CNN-based Hypothesis Selection
Automated segmentation approaches are crucial to quantitatively analyze large-scale 3D microscopy images.
Video Human Segmentation using Fuzzy Object Models and its Application to Body Pose Estimation of Toddlers for Behavior Studies
Video object segmentation is a challenging problem due to the presence of deformable, connected, and articulated objects, intra- and inter-object occlusions, object motion, and poor lighting.
