The use of machine learning (ML) has been increasing rapidly in the medical imaging field,
including computer-aided diagnosis (CAD), radiomics, and medical image analysis …

Summary 16S rRNA-targeted oligonucleotide probes for eubacteria (EUB338), ammonium-
oxidizing bacteria (Nsm156) and nitrite-oxidizing bacteria (Nb1000) were used for the rapid …

Automated visual tracking of animals is rapidly becoming an indispensable tool for the study
of behavior. It offers a quantitative methodology by which organisms' sensing and decision …

This article addresses the connected-component labeling problem which consists in
assigning a unique label to all pixels of each connected component (ie, each object) in a …

A key solution to visual question answering (VQA) exists in how to fuse visual and language
features extracted from an input image and question. We show that an attention mechanism …

We report the application of machine learning methods for predicting the effective diffusivity
(D e) of two-dimensional porous media from images of their structures. Pore structures are …

Instance segmentation requires labor-intensive manual labeling of the contours of complex
objects in images for training. The labels can also be provided incrementally in practice to …

While cities around the world are increasingly promoting streets and public spaces that
prioritize pedestrians over vehicles, significant data gaps have made pedestrian map** …

The spatiotemporal monitoring of droughts is a complex task. In the past decades, drought
monitoring has been increasingly developed, while the consideration of its spatio-temporal …

This paper presents one feature-based detector to find sea-surface floating small targets. In
integration time of the order of seconds, target returns exhibit time-frequency (TF) …