Preprint Highlight: Learning orientation-invariant representations enables accurate and robust morphologic profiling of cells and organelles
Sign Up to like & getrecommendations! Published in 2023 at "Molecular Biology of the Cell"
DOI: 10.1091/mbc.p23-04-0013
Abstract: One application of deep learning in analysis of cell biological microscopy data is developing meaningful quantitative representations of cellular and/or molecular phenotypic signatures. Because image orientation has no relevance for shape and morphology, encoding orientation… read more here.
Keywords: preprint highlight; invariant representations; learning orientation; orientation invariant ... See more keywords
Orientation Invariant Sensorimotor Object Recognition Using Cortical Grid Cells
Sign Up to like & getrecommendations! Published in 2022 at "Frontiers in Neural Circuits"
DOI: 10.3389/fncir.2021.738137
Abstract: Grid cells enable efficient modeling of locations and movement through path integration. Recent work suggests that the brain might use similar mechanisms to learn the structure of objects and environments through sensorimotor processing. This work… read more here.
Keywords: sensorimotor object; orientation invariant; grid cells; sensorimotor ... See more keywords
Exploring Orientation Invariant Heuristic Features with Variant Window Length of 1D-CNN-LSTM in Human Activity Recognition
Sign Up to like & getrecommendations! Published in 2022 at "Biosensors"
DOI: 10.3390/bios12070549
Abstract: Many studies have explored divergent deep neural networks in human activity recognition (HAR) using a single accelerometer sensor. Multiple types of deep neural networks, such as convolutional neural networks (CNN), long short-term memory (LSTM), or… read more here.
Keywords: cnn lstm; orientation invariant; orientation; heuristic features ... See more keywords