A Domain-Adaptive Two-Stream U-Net For Electron Microscopy Image Segmentation

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Probabilistic methods for neural combinatorial optimization

The monumental progress in the development of machine learning models has led to a plethora of applications with transformative effects in engineering and science. This has also turned the attention of the research community towards the pursuit of construc ...

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There is a growing recognition that electronic band structure is a local property of materials and devices, and there is steep growth in capabilities to collect the relevant data. New photon sources, from small-laboratory-based lasers to free electron lase ...

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Automated neuron tracking inside moving and deforming C. elegans using deep learning and targeted augmentation

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Reading out neuronal activity from three-dimensional (3D) functional imaging requires segmenting and tracking individual neurons. This is challenging in behaving animals if the brain moves and deforms. The traditional approach is to train a convolutional n ...

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Why is the winner the best?

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International benchmarking competitions have become fundamental for the comparative performance assessment of image analysis methods. However, little attention has been given to investigating what can be learnt from these competitions. Do they really gener ...

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The JPEG AI Standard: Providing Efficient Human and Machine Visual Data Consumption

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The Joint Photographic Experts Group (JPEG) AI learning-based image coding system is an ongoing joint standardization effort between International Organization for Standardization (ISO), International Electrotechnical Commission (IEC), and International Te ...

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Observing the fast dynamics of nanoscale systems is crucial in order to understand and ultimately control their behavior. Characterizing these dynamic processes requires techniques with atomic spatial resolution and a temporal resolution that matches the t ...

EPFL2023

Label-free plasmonic microarray for multiplexed analysis of cells and tumor organoids

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Investigating the dynamic activities of protein expression and signaling in living organisms is a crucial focus of intense research aimed at elucidating the processes that underlie disease progression and improving treatments and drug development. Resolvin ...

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Transformer Models for Vision

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The recent developments of deep learning cover a wide variety of tasks such as image classification, text translation, playing go, and folding proteins. All these successful methods depend on a gradient-based learning algorithm to train a model on massive ...

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MULTI-TASK CURRICULUM LEARNING FOR PARTIALLY LABELED DATA

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Incomplete labels are common in multi-task learning for biomedical applications due to several practical difficulties, e.g., expensive annotation efforts by experts, limit of data collection, different sources of data. A naive approach to enable joint lear ...

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Charge Dynamics Electron Microscopy Nanoscale Imaging of Femtosecond Plasma Dynamics

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Understanding and actively controlling the spatiotemporal dynamics of nonequilibrium electron clouds is fundamental for the design of light and electron sources, high power electronic devices, and plasma-based applications. However, electron clouds evolve ...

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Fractal Analysis of Four Xerogels Based on TEGylated Phenothiazine and Chitosan

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The present article describes novel massive materials (in the solid phase) based on TEGylated phenothiazine and chitosan that possess great capability to recover mercury ions from constituent aqueous solutions. These were produced by chitosan hydrogelation ...

MDPI2023

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