Related papers: Deep Learning for Optical Tweezers
We consider deep learning strategies in ultrasound systems, from the front-end to advanced applications. Our goal is to provide the reader with a broad understanding of the possible impact of deep learning methodologies on many aspects of…
Deep optics has emerged as a promising approach by co-designing optical elements with deep learning algorithms. However, current research typically overlooks the analysis and optimization of manufacturing and assembly tolerances. This…
Since its invention by Arthur Ashkin and colleagues at Bell Labs in the 1970s, optical micromanipulation, also known as optical tweezers or laser tweezers, has evolved remarkably to become one of the most convenient and versatile tools for…
The implementation of deep learning algorithms has brought new perspectives to plankton ecology. Emerging as an alternative approach to established methods, deep learning offers objective schemes to investigate plankton organisms in diverse…
Acoustic tweezers can manipulate microscopic objects and cells independently of the optical, magnetic and electrical properties of the objects or their medium. However, because ultrasonic waves are attenuated within few millimeters,…
Optical machine learning offers advantages in terms of power efficiency, scalability and computation speed. Recently, an optical machine learning method based on Diffractive Deep Neural Networks (D2NNs) has been introduced to execute a…
We show a concept of optical frequency tweezers for tweezing light in the optical frequency domain with a high resolution, which is the frequency version of the optical tweezers for spatial manipulation of microscopic objects. We report the…
Recognition of objects with subtle differences has been used in many practical applications, such as car model recognition and maritime vessel identification. For discrimination of the objects in fine-grained detail, we focus on deep…
Deep neural networks have achieved remarkable breakthroughs by leveraging multiple layers of data processing to extract hidden representations, albeit at the cost of large electronic computing power. To enhance energy efficiency and speed,…
Deep learning has gained significant attention in remote sensing, especially in pixel- or patch-level applications. Despite initial attempts to integrate deep learning into object-based image analysis (OBIA), its full potential remains…
Today, deep learning represents the most popular and successful form of machine learning. Deep learning has revolutionised the field of pattern recognition, including biometric recognition. Biometric systems utilising deep learning have…
Deep neural networks have rightfully won the place of one of the most accurate analysis tools in high energy physics. In this paper we will cover several methods of improving the performance of a deep neural network in a classification task…
Scanning near-field optical microscopy is one of the most effective techniques for spectroscopy of nanoscale systems. However, inferring optical constants from the measured near-field signal can be challenging because of a complicated and…
We report the realization of the first planar optical tweezer trap system by a sheet of light. To visualize the trapping of the target object (dielectric bead or live cell) in a plane, an orthogonal widefield detection is employed. The…
The techniques of deep learning have become the state of the art methodology for executing complicated tasks from various domains of computer vision, natural language processing, and several other areas. Due to its rapid development and…
We present a novel platform of optical tweezers which combines rapid prototyping of user-definable microlens arrays with spatial light modulation (SLM) for dynamical control of each associated tweezer spot. Applying femtosecond direct laser…
Deep learning is an advanced technology that relies on large-scale data and complex models for feature extraction and pattern recognition. It has been widely applied across various fields, including computer vision, natural language…
Machine learning is a modern approach to problem-solving and task automation. In particular, machine learning is concerned with the development and applications of algorithms that can recognize patterns in data and use them for predictive…
Rotational optical tweezers are used to probe the mechanical properties of unknown microsystems. Quantifying the angular trap stiffness is essential for interpreting the rotational dynamics of probe particles. While methods to determine…
Optical levitation of dielectric particles in vacuum is a powerful technique for precision measurements, testing fundamental physics, and quantum information science. Conventional optical tweezers require bulky optical components for…