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

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

Deep learning has brought incredible progress in areas where traditional algorithms struggle. It can be because they need rules that are sometimes hard to conceptualize, it can also be that the number and manner of combining these rules are too complex to ...

Determining whether a molecule can be synthesized is crucial in chemistry and drug discovery, as it guides experimental prioritization and molecule ranking in de novo design tasks. Existing scoring approaches to assess synthetic feasibility struggle to ext ...

Recent advancements in deep learning have found compelling applications in the image-based inspection of infrastructure systems. However, the efficacy of these models hinges significantly on the quality and diversity of the input data used for training. In ...

Cell segmentation is a critical step for quantitative single-cell analysis in microscopy images. Existing cell segmentation methods are often tailored to specific modalities or require manual interventions to specify hyper-parameters in different experimen ...

Nodal properties are of particular importance when investigating patterns in brain networks. Nodal information is usually studied by comparing a few nodal measurements (up to three), resulting in analyses in three-dimensional spaces, at maximum. We offer a ...

This manuscript is the lecture notes of B. Barak’s course in the Les Houches ‘Statistical Physics and Machine Learning’ summer school in 2022. It surveys various proxies for computational hardness in random planted problems, from the low-degree likelihood ...

We demonstrate the use of both pixelated differential phase contrast (DPC) scanning transmission electron microscopy (STEM) and off-axis electron holography (EH) for the measurement of electric fields and assess the advantages and limitations of each techn ...

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 ...

Deep learning has revolutionized the field of computer vision, a success largely attributable to the growing size of models, datasets, and computational power. Simultaneously, a critical pain point arises as several computer vision applications are deploye ...

Photometric stereo, a computer vision technique for estimating the 3D shape of objects through images captured under varying illumination conditions, has been a topic of research for nearly four decades. In its general formulation, photometric stereo is an ...

In this thesis we explore the applications of projective geometry, a mathematical theory of the relation between 3D scenes and their 2D images, in modern learning-based computer vision systems. This is an interesting research question which contradicts the ...

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 ...

Heterostructures consisting of SmNiO3 and NdNiO3 alternating layers with additional LaAlO3 spacer layers were grown and fully characterized by means of x-ray diffraction, atomic force microscopy, and scanning transmission electron microscopy. A change in t ...

The invention of 3D atomic force microscopy (3D-AFM) has enabled visualizing subnanoscale 3D hydration structures. Meanwhile, its applications to imaging flexible molecular chains have started to be experimentally explored. However, the validity and princi ...

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 ...

Non-Bayesian social learning is a framework for distributed hypothesis testing aimed at learning the true state of the environment. Traditionally, the agents are assumed to receive observations conditioned on the same true state, although it is also possib ...

Pulmonary nodules and masses are crucial imaging features in lung cancer screening that require careful management in clinical diagnosis. Despite the success of deep learning-based medical image segmentation, the robust performance on various sizes of lesi ...

State-of-the-art object detection and segmentation methods for microscopy images rely on supervised machine learning, which requires laborious manual annotation of training data. Here we present a self-supervised method based on time arrow prediction pre-t ...

Advancing quantum technologies depends on the precise control of individual quantum systems, the so-called qubits, and the exploitation of their quantum properties. Nowadays, expanding the number of qubits to be entangled is at the core of the developments ...

The capabilities of deep learning systems have advanced much faster than our ability to understand them. Whilst the gains from deep neural networks (DNNs) are significant, they are accompanied by a growing risk and gravity of a bad outcome. This is troubli ...

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

Chat with Graph Search

Extending Capabilities of Attention-based Models

FSscore: A Personalized Machine Learning-Based Synthetic Feasibility Score

Uncertainty quantification for a deep learning models for image-based crack segmentation

The multimodality cell segmentation challenge: toward universal solutions

Connectome embedding in multidimensional graph spaces

Computational complexity of deep learning: fundamental limitations and empirical phenomena

Measuring electrical properties in semiconductor devices by pixelated STEM and off-axis electron holography (or convergent beams vs. plane waves)

Modular segmentation, spatial analysis and visualization of volume electron microscopy datasets

Fast and Future: Towards Efficient Forecasting in Video Semantic Segmentation

Aggregating Spatial and Photometric Context for Photometric Stereo

Incorporating Projective Geometry into Deep Learning

Polydopamine-coated photoautotrophic bacteria for improving extracellular electron transfer in living photovoltaics

Structural study of nickelate based heterostructures

Revealing the Mechanism Underlying 3D-AFM Imaging of Suspended Structures by Experiments and Simulations

Compact and effective photon-resolved image scanning microscope

Detection of Malicious Agents in Social Learning

Scale-Aware Test-Time Click Adaptation for Pulmonary Nodule and Mass Segmentation

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

Electron-beam based nanoscale quantum controls

Safe Deep Neural Networks