Self-supervised Dense Representation Learning for Live-Cell Microscopy with Time Arrow Prediction

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The proliferation of microscopy methods for live-cell imaging offers many new possibilities for users but can also be challenging to navigate. The prevailing challenge in live-cell fluorescence microscopy is capturing intra-cellular dynamics while preservi ...

Volume electron microscopy is the method of choice for the in situ interrogation of cellular ultrastructure at the nanometer scale, and with the increase in large raw image datasets generated, improving computational strategies for image segmentation and s ...

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Monitoring forests, in particular their response to climate and land use change, requires studying long time scales. While efficient deep learning methods have been developed to process short time series of satellite imagery, leveraging long time series of ...

Turning pass-through network architectures into iterative ones, which use their own output as input, is a well-known approach for boosting performance. In this paper, we argue that such architectures offer an additional benefit: The convergence rate of the ...

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Given a sequence of functions

f_1,\ldots,f_n

with

f_i:\mathcal{D}\mapsto \mathbb{R}

, finite-sum minimization seeks a point

{x}^\star \in \mathcal{D}

minimizing

\sum_{j=1}^nf_j(x)/n

. In this work, we propose a key twist into the finite-sum minimizat ...

Fluorescence confocal laser-scanning microscopy (LSM) is one of the most popular tools for life science research. This popularity is expected to grow thanks to single-photon array detectors tailored for LSM. These detectors offer unique single-photon spati ...

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Traditional cell cultures have long been fundamental to biological research, offering an alternative to animal models burdened by ethical constraints and procedural intricacies, often lacking relevance to human physiology and disease. Moreover, their inabi ...

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The upcoming Square Kilometre Array Observatory will produce images of neutral hydrogen distribution during the epoch of reionization by observing the corresponding 21-cm signal. However, the 21-cm signal will be subject to instrumental limitations such as ...

Living photovoltaics are microbial electrochemical devices that use whole cell–electrode interactions to convert solar energy to electricity. The bottleneck in these technologies is the limited electron transfer between the microbe and the electrode surfac ...

The performance of machine learning algorithms is conditioned by the availability of training datasets, which is especially true for the field of nondestructive evaluation. Here we propose one reconfigurable specimen instead of numerous reference specimens ...

Self-supervised Dense Representation Learning for Live-Cell Microscopy with Time Arrow Prediction

Chattez avec Graph Search

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