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Wavefront estimation through structured detection in laser scanning microscopy

Biomedical Optics Express 2025年第5期16卷 2135-2155页

作者： Fersini, Francesco Zunino, Alessandro Morerio, Pietro Baldini, Francesca Diaspro, Alberto Booth, Martin J. Del Bue, Alessio Vicidomini, Giuseppe Molecular Microscopy and Spectroscopy Istituto Italiano di Tecnologia Genoa Italy Dipartimento di Informatica Bioingegneria Robotica e Ingegneria dei Sistemi University of Genoa Genoa Italy Pattern Analysis and Computer Vision Istituto Italiano di Tecnologia Genoa Italy Nanoscopy and NIC@IIT Istituto Italiano di Tecnologia Genoa Italy Department of Physics University of Genoa Genoa Italy Department of Engineering Science University of Oxford Oxford United Kingdom

Laser scanning microscopy (LSM) is the base of numerous advanced imaging techniques, including confocal laser scanning microscopy (CLSM), a widely used tool in life sciences research. However, its effective resolution is often compromised by optical aberrations, a common challenge in all optical systems. While adaptive optics (AO) can correct these aberrations, current methods face significant limitations: aberration estimation, which is central to any AO approach, typically requires specialized hardware or prolonged sample exposure, rendering these methods sample-invasive, and less user-friendly. In this study, we propose a simple and efficient AO strategy for CLSM systems equipped with a detector array – image-scanning microscopy – and an AO element for beam shaping. We demonstrate, for the first time, that datasets acquired with a detector array inherently encode aberration information. As a proof-of-concept of this important property, we designed a custom convolutional neural network capable of decoding aberrations up to the 11th Zernike coefficient, directly from a single acquisition. While this data-driven approach represents an initial exploration of the aberration content, it opens the door to more advanced decoding strategies – including model-based methods. This work establishes a new paradigm for aberration sensing in LSM and is designed to work synergistically with conventional AO approaches such as phase diversity, enabling faster, less invasive, and more accessible high-resolution imaging. © 2025 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.

关键词： Aberrations

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Multi robot SLAM for features based environment modelling

Multi robot SLAM for features based environment modelling

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11th IEEE International Conference on Mechatronics and Automation, IEEE ICMA 2014

作者： Riaz Un Nabi Jafri, Syed Ahmed, Waheed Ashraf, Zubair Chellali, Ryad Electronic Engineering Department NED UET Karachi Pakistan Pattern Analysis and Computer Vision LAB-IIT Genova Italy

ISBN: (纸本)9781479939787

This paper is presenting a multi robot simultaneous localization and mapping (SLAM) framework for environment modelling using 2D and 3D features. The proposed solution is using a team of mobile robots which are exploring unknown environment with unknown poses. Each team member is allowed to build its independent features based SLAM solution and to share the local map model among other mates. By matching the overlapping tendency of any two mates, a map merging strategy is introduced which in result is building global map. The overall approach has tested in 2D and 3D features based environment and results have shown. © 2014 IEEE.

关键词： Extended Kalman filters

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Multi-spectral scale and rotation invariant associative memory method for pattern recognition

Multi-spectral scale and rotation invariant associative memo...

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Optics, Illumination, and Image Sensing for Machine vision III 1988

作者： Kimball, Steven F. Messner, Richard A. University of New Hampshire Synthetic Vision and Pattern Analysis Laboratory Department of Electrical and Computer Engineering DurhamNH03824 United States

The method of using log-polar mapping with spectral band separation to form feature vectors for an associative memory is investigated. Log-polar mapping is used to provide the scale and rotation invariant properties. This reduces the teaching time and total capacity requirement for the associative memory because all orientations and sizes of the target object need not be learned. The images are also broken down into spatial frequency bands. The use of this technique is motivated by evidence that similar processes occur in the human visual system. Suspected benefits include enhanced recognition in the presence of noise and improved network robustness. Simulation results are presented for the case of character recognition. © 1989 SPIE. All rights reserved.

关键词： Associative processing

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Guided Zoom: Questioning network evidence for fine-grained classification 30

Guided Zoom: Questioning network evidence for fine-grained c...

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30th British Machine vision Conference, BMVC 2019

作者： Bargal, Sarah Adel Zunino, Andrea Petsiuk, Vitali Zhang, Jianming Saenko, Kate Murino, Vittorio Sclaroff, Stan Department of Computer Science Boston University United States Pattern Analysis and Computer Vision Istituto Italiano di Tecnologia Italy Adobe Research Department of Computer Science University of Verona Italy

We propose Guided Zoom, an approach that utilizes spatial grounding of a model's decision to make more informed predictions. It does so by making sure the model has "the right reasons" for a prediction, defined as reasons that are coherent with those used to make similar correct decisions at training time. The reason/evidence upon which a deep convolutional neural network makes a prediction is defined to be the spatial grounding, in the pixel space, for a specific class conditional probability in the model output. Guided Zoom examines how reasonable such evidence is for each of the top-k predicted classes, rather than solely trusting the top-1 prediction. We show that Guided Zoom improves the classification accuracy of a deep convolutional neural network model and obtains state-of-the-art results on three fine-grained classification benchmark datasets. © 2019. The copyright of this document resides with its authors.

关键词： Forecasting

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Visually-driven semantic augmentation for zero-shot learning 29

Visually-driven semantic augmentation for zero-shot learning

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29th British Machine vision Conference, BMVC 2018

作者： Roy, Abhinaba Cavazza, Jacopo Murino, Vittorio Pattern Analysis and Computer Vision Istituto Italiano di Tecnologia Genova Italy Department of Naval Electrical Electronic and Telecommunications Engineering University of Genova Italy Department of Computer Science University of Verona Italy

In this paper, we tackle the zero-shot learning (ZSL) classification problem and analyse one of its key ingredients, the semantic embedding. Despite their fundamental role, semantic embeddings are not learnt from the visual data to be classified, but, instead, they either come from manual annotation (attributes) or from a linguistic text corpus (distributed word embeddings, DWEs). Hence, there is no guarantee that visual and semantic information could fit well, and as to bridge this gap, we propose to augment the semantic information of attributes/DWEs with semantic representations directly extracted from visual data by means of soft labels. When combined in a novel ZSL paradigm based on latent attributes, our approach achieves favourable performances on three public benchmark datasets. © 2018. The copyright of this document resides with its authors.

关键词： Zero-shot learning

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Statistical analysis of visual attentional patterns for video surveillance 1

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18th Iberoamerican Congress on pattern Recognition, CIARP 2013

作者： Roffo, Giorgio Cristani, Marco Pollick, Frank Segalin, Cristina Murino, Vittorio Department of Computer Science University of Verona Italy Pattern Analysis and Computer Vision Dept. Istituto Italiano di Tecnologia Italy School of Psychology University of Glasgow United Kingdom

ISBN: (数字)9783642418273

ISBN: (纸本)9783642418266

We show that the way people observe video sequences, other than what they observe, is important for the understanding and the prediction of human activities. In this study, we consider 36 surveillance videos, organized in four categories (confront, nothing, fight, play ): the videos are observed by 19 people, ten of them are experienced operators and the other nine are novices, and the gaze trajectories of both populations are recorded by an eye tracking device. Due to the proved superior ability of experienced operators in predicting violence in surveillance footage, our aim is to distinguish the two classes of people, highlighting in which respect expert operators differ from novices. Extracting spatio-temporal features from the eye tracking data, and training standard machine learning classifiers, we are able to discriminate the two groups of subjects with an average accuracy of 80.26%. The idea is that expert operators are more focused on few regions of the scene, sampling them with high frequency and low predictability. This can be thought as a first step toward the advanced automated analysis of video surveillance footage, where machines imitate as best as possible the attentive mechanisms of humans. © Springer-Verlag 2013.

关键词： Eye tracking

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Effective brain connectivity through a constrained autoregressive model 1

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1st International Workshop on Simulation and Synthesis in Medical Imaging, SASHIMI 2016 held in conjunction with 19th International Conference on Medical Image Computing and computer-Assisted Intervention, MICCAI 2016

作者： Crimi, Alessandro Dodero, Luca Murino, Vittorio Sona, Diego Pattern Analysis and Computer Vision Istituto Italiano di Tecnologia Genoa Italy Department of Computer Science University of Verona Verona Italy Neuroinformatics Laboratory Fondazione Bruno Kessler Trento Italy

ISBN: (数字)9783319467207

ISBN: (纸本)9783319467191

Integration of functional and structural brain connectivity is a topic receiving growing attention in the research community. Their fusion can,in fact,shed new light on brain functions. Targeting this issue,the manuscript proposes a constrained autoregressive model allowing to generate an "effective" connectivity matrix that model the structural connectivity integrating the functional activity. In practice,an initial structural connectivity representation is altered according to functional data,by minimizing the reconstruction error of an autoregressive model constrained by the structural prior. The proposed model has been tested in a community detection framework,where the brain is partitioned using the effective network across multiple subjects. Results showed that using the effective connectivity the resulting clusters better describe the functional interactions of different regions while maintaining the structural organization. © Springer International Publishing AG 2016.

关键词： Brain mapping

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Handwritten word-image retrieval with synthesized typed queries

Handwritten word-image retrieval with synthesized typed quer...

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ICDAR2009 - 10th International Conference on Document analysis and Recognition

作者： Rodríguez-Serrano, José A. Perronnin, Florent Computer Vision Centre Universitat Autonoma de Barcelona Spain Textual and Visual Pattern Analysis Xerox Research Centre Europe France Computer Science Department Loughborough University United Kingdom

ISBN: (纸本)9780769537252

We propose a new method for handwritten word-spotting which does not require prior training or gathering examples for querying. More precisely, a model is trained "on the fly" with images rendered from the searched words in one or multiple computer fonts. To reduce the mismatch between the typed-text prototypes and the candidate handwritten images, we make use of: (i) local gradient histogram (LGH) features, which were shown to model word shapes robustly, and (ii) semi-continuous hidden Markov models (SC-HMM), in which the typed-text models are constrained to a "vocabulary" of handwritten shapes, thus learning a link between both types of data. Experiments show that the proposed method is effective in retrieving handwritten words, and the comparison to alternative methods reveals that the contribution of both the LGH features and the SC-HMM is crucial. To the best of the authors' knowledge, this is the first work to address this issue in a non-trivial manner. © 2009 IEEE.

关键词： Image retrieval

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Close-range photometric stereo with point light sources 2

Close-range photometric stereo with point light sources

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2014 2nd International Conference on 3D vision, 3DV 2014

作者： Wetzler, Aaron Kimmel, Ron Bruckstein, Alfred M. Mecca, Roberto Computer Science Department Technion Israel Institute of Technology Technion City Haifa32000 Israel Pattern Analysis and Computer Vision Department Istituto Italiano di Tecnologia via Morego 30 Genova16163 Italy

ISBN: (纸本)9781479970018

Shape recovery based on shading variations of a lighted object was recently revisited with improvements that allow for the photometric stereo approach to serve as a competitive alternative for other shape reconstruction methods. However, most efforts of using photometric stereo tend to ignore some factors that are relevant in practical applications. The approach we consider tackles the photometric stereo reconstruction in the case of near-field imaging which means that both camera and light sources are close to the imaged object. The known challenges that characterize the problem involve perspective viewing geometry, attenuation of light and possibly missing regions. Here, we pay special attention to the question of how to faithfully model these aspects and by the same token design an efficient and robust numerical solver. We present a well-posed mathematical representation that integrates the above assumptions into a single coherent model. The surface reconstruction in our near-field scenario can then be executed efficiently in linear time. The merging strategy of the irradiance equations provided for each light source allows us to consider a characteristic expansion model which enables the direct computation of the surface. We evaluate several types of light attenuation models with nonuniform albedo and noise on synthetic data using four virtual sources. We also demonstrate the proposed method on surface reconstruction of real data using three images, each one taken with a different light source. © 2014 IEEE.

关键词： Light sources

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Skew estimation and correction for form documents using wavelet decomposition

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2nd International Conference on Image analysis and Recognition, ICIAR 2005

作者： Xi, Dihua Kamel, Mohamed Lee, Seong-Whan Pattern Analysis and Machine Intelligence Research Group Department of Electrical and Computer Engineering University of Waterloo Waterloo Canada Center for Artificial Vision Research Korea University Seoul Korea Republic of

ISBN: (纸本)3540290699

Form document image processing has become an increasingly essential technology in office automation tasks. One of the problems is that the document image may appear skewed for many reasons. Therefore, the skew estimation plays an important role in any automatic document analysis system. In the past few years, many algorithms have been developed to detect the skew angle of text document images. However, these algorithms suffer from two major deficiencies. Firstly, most of them suppose that the original image is monochrome and therefore they are not suitable to apply to documents with a complicated background. Secondly, most of the current methods were developed for general document images that are not as complicated as form documents. In this paper, we present a new approach to skew detection for grey-level form document images. In our system, image decomposition by 2D wavelet transformations is used to estimate the skew angle. © Springer-Verlag Berlin Heidelberg 2005.

关键词： Image processing

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