Large-scale analysis of high-speed atomic force microscopy data sets using adaptive image processing

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.

Increasing the scanning speed in Atomic Force Microscopy (AFM) relies on improving the tracking performance in the vertical direction of motion. The lightly damped resonances of piezo-actuators utilized in AFM nano-positioning stages hinder the maximum ach ...

We demonstrate the reversible control of interactions between a local molecular spin, hosted within an iron phthalocyanine (FePc) molecule, and the conduction electrons of a supporting Au(111) surface. Using the tip of a scanning tunneling microscope, we d ...

As one of the major threats to women's health worldwide, breast cancer requires early diagnosis and accurate classification, since they are key to optimizing therapeutic interventions and ensuring precise prognosis. Recently, deep learning has demonstrated ...

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 ...

While understanding the shear strength of stone masonry structures is important for the design and the mainte- nance, we still lack computational tools for predicting the strength as a function of the stone layout. Here we implement an end-to-end image bas ...

Controlled atomic patterning is an attractive tool to fine tune properties of graphitic lattice. Several O-functionalized derivatives of graphitic lattice have been widely studied, e.g., graphene oxide, reduced graphene oxide, and functionalized carbon nan ...

Recent advances in image compression have made it both possible and desirable for image quality to approach the visually lossless range. However, the most commonly used subjective visual quality assessment protocols, e.g. those reported in ITU-T Rec. BT.50 ...

To obtain a more complete understanding of material microstructure at the nanoscale and to gain profound insights into their properties, there is a growing need for more efficient and precise methods that can streamline the process of 3D imaging using a tr ...

Ultrafast ultrasound imaging, characterized by high frame rates, generates low-quality images. Convolutional neural networks (CNNs) have demonstrated great potential to enhance image quality without compromising the frame rate. However, CNNs have been most ...

We present a method that can recognize new objects and estimate their 3D pose in RGB images even under partial occlusions. Our method requires neither a training phase on these objects nor real images depicting them, only their CAD models. It relies on a s ...

Cross-resolution face recognition has become a challenging problem for modern deep face recognition systems. It aims at matching a low-resolution probe image with high-resolution gallery images registered in a database. Existing methods mainly leverage pri ...

This paper describes the development of a novel medical x-ray imaging system adapted to the needs and constraints of low- and middle-income countries. The developed system is based on an indirect conversion chain: a scintillator plate produces visible ligh ...

In recent years, new emerging immersive imaging modalities, e.g. light fields, have been receiving growing attention, becoming increasingly widespread over the years. Light fields are often captured through multi-camera arrays or plenoptic cameras, with th ...

We study the plasmon modes of gold nanorods (as short as similar to 100 nm) on a nonmetallic conductive substrate using scanning tunneling microscope-induced light emission (STM-LE) with a nonplasmonic tungsten tip at room temperature in high vacuum (10-7 ...

Data imputation of incomplete image sequences is an essential prerequisite for analyzing and monitoring all development stages of plants in precision agriculture. For this purpose, we propose a conditional Wasserstein generative adversarial network TransGr ...

Due to the increasing number of pictures captured and stored every day by and on digital devices, lossy image compression has become inevitable to limit the needed storage requirement. As a consequence, these compression methods might introduce some visual ...

Rationale and objectives: To prospectively evaluate feasibility and robustness of an accelerated T2 mapping sequence (GRAPPATINI) in brain imaging and to assess its synthetic T2-weighted images (sT2w) in comparison with a standard T2-weighted sequence (T2 ...

The properties of signal strength and integrated intensity in a scanned imaging system are reviewed. These prop-erties are especially applied to confocal imaging systems, including image scanning microscopy. The integrated intensity, equal to the image of ...

We consider the problem of compressing an information source when a correlated one is available as side information only at the decoder side, which is a special case of the distributed source coding problem in information theory. In particular, we consider ...

State-of-the-art 2D image compression schemes rely on the power of convolutional neural networks (CNNs). Although CNNs offer promising perspectives for 2D image compression, extending such models to omnidirectional images is not straightforward. First, omn ...

Large-scale analysis of high-speed atomic force microscopy data sets using adaptive image processing

Chat with Graph Search

Data-driven control in atomic force microscopy using a genetic algorithm

Engineering Spin Interaction Channels of FePc on Au(111)

Mspo: a Machine Learning Hyperparameter Optimization Method for Enhanced Breast Cancer Image Classification

Aggregating Spatial and Photometric Context for Photometric Stereo

Micro modeling of irregular stone masonry walls using mathematical programming

Nanolithography of the nanocorral structure of chemisorbed oxygen atoms on the graphitic lattice

On the assessment of high-quality images: advances on the JPEG AIC-3 activity

3D reconstruction of curvilinear one-dimensional objects viewed in transmission electron microscopy

A KL Divergence-Based Loss for In Vivo Ultrafast Ultrasound Image Enhancement with Deep Learning

Templates for 3D Object Pose Estimation Revisited: Generalization to New Objects and Robustness to Occlusions

Cross-resolution Face Recognition via Identity-Preserving Network and Knowledge Distillation

X-ray imaging detector for radiological applications adapted to the context and requirements of low- and middle-income countries

Towards learning-based denoising of light fields

Selectively Exciting and Probing Radiative Plasmon Modes on Short Gold Nanorods by Scanning Tunneling Microscope-Induced Light Emission

Time Dependent Image Generation of Plants from Incomplete Sequences with CNN-Transformer

Towards JPEG AIC part 3: visual quality assessment of high to visually lossless image coding

Clinical feasibility and validation of the accelerated T2 mapping sequence GRAPPATINI in brain imaging

Signal strength and integrated intensity in confocal and image scanning microscopy

Neural Distributed Image Compression with Cross-Attention Feature Alignment

OSLO: On-the-Sphere Learning for Omnidirectional Images and Its Application to 360-Degree Image Compression