Search results for "image processing"
showing 10 items of 3285 documents
The urban being between environment and landscape. On the old town as an emerging subject
2018
The landscape units of the Sicilian mountainous inland, as for the case of Petralia Soprana, are marked by the presence of ancient urban centres controlling the agricultural territory, from which they derived their own wealth, and to which they conferred landscape significance. The unity between economy and landscape has been interrupted by the radical transformation of the socio-economic structure and the technologic progress, which have eroded the consistency between structures and superstructures. We propose an assessment approach based on a synthesis of semiotic and phenomenological view. The approach mainly focuses on the basic concepts and contents of the valuation process that can be…
Language Detection and Tracking in Multilingual Documents Using Weak Estimators
2010
Published version of an article from the book: Structural, Syntactic, and Statistical Pattern Recognition . The original publication is available at Spingerlink. http://dx.doi.org/DOI: 10.1007/978-3-642-14980-1_59 This paper deals with the extremely complicated problem of language detection and tracking in real-life electronic (for example, in Word-of-Mouth (WoM)) applications, where various segments of the text are written in different languages. The difficulties in solving the problem are many-fold. First of all, the analyst has no knowledge of when one language stops and when the next starts. Further, the features which one uses for any one language (for example, the n-grams) will not be…
An Interactive Demonstration of Collaborative VR for Laparoscopic Liver Surgery Training
2019
We introduce a collaborative virtual reality (VR) system for planning and simulation in laparoscopic liver surgery training. Patient image data is used for surgical model visualization and simulation. We developed two modes for training in laparoscopic procedures: exploration and surgery mode. Surgical joysticks are used in surgery mode to provide training for psychomotor skills and cooperation between a camera assistant and an experienced surgeon. Continuous feedback from our clinical partner comprised an important part of the development. Our evaluation showed that surgeons were positive about the usability and usefulness of the developed system. For further details, please refer to our f…
Multi-Path U-Net Architecture for Cell and Colony-Forming Unit Image Segmentation
2022
U-Net is the most cited and widely-used deep learning model for biomedical image segmentation. In this paper, we propose a new enhanced version of a ubiquitous U-Net architecture, which improves upon the original one in terms of generalization capabilities, while addressing several immanent shortcomings, such as constrained resolution and non-resilient receptive fields of the main pathway. Our novel multi-path architecture introduces a notion of an individual receptive field pathway, which is merged with other pathways at the bottom-most layer by concatenation and subsequent application of Layer Normalization and Spatial Dropout, which can improve generalization performance for small datase…
Leader election and local identifiers for three‐dimensional programmable matter
2020
International audience; In this paper, we present two deterministic leader election algorithms for programmable matter on the face-centered cubic grid. The face-centered cubic grid is a 3-dimensional 12-regular infinite grid that represents an optimal way to pack spheres (i.e., spherical particles or modules in the context of the programmable matter) in the 3-dimensional space. While the first leader election algorithm requires a strong hypothesis about the initial configuration of the particles and no hypothesis on the system configurations that the particles are forming, the second one requires fewer hypothesis about the initial configuration of the particles but does not work for all pos…
Vine leaf roughness estimation by image processing
2013
International audience; The application of plant protection product has an important role in agricultural production processes. With current pesticides management, a huge amount of them are applied to worldwide orchards. In precision spraying, spray application efficiency depends on the pesticide application method, the phytosanitary product as well as the leaf surface properties. For environmental and economic reasons, the global trend is to reduce the pesticide application rate of the few approved active substances. Under these constraints, one of the challenges is to improve the efficiency of pesticide application. Different parameters can influence pesticide application such as nozzle t…
A Scheme for Continuous Input to the Tsetlin Machine with Applications to Forecasting Disease Outbreaks
2019
In this paper, we apply a new promising tool for pattern classification, namely, the Tsetlin Machine (TM), to the field of disease forecasting. The TM is interpretable because it is based on manipulating expressions in propositional logic, leveraging a large team of Tsetlin Automata (TA). Apart from being interpretable, this approach is attractive due to its low computational cost and its capacity to handle noise. To attack the problem of forecasting, we introduce a preprocessing method that extends the TM so that it can handle continuous input. Briefly stated, we convert continuous input into a binary representation based on thresholding. The resulting extended TM is evaluated and analyzed…
A formal proof of the e-optimality of discretized pursuit algorithms
2015
Learning Automata (LA) can be reckoned to be the founding algorithms on which the field of Reinforcement Learning has been built. Among the families of LA, Estimator Algorithms (EAs) are certainly the fastest, and of these, the family of discretized algorithms are proven to converge even faster than their continuous counterparts. However, it has recently been reported that the previous proofs for ??-optimality for all the reported algorithms for the past three decades have been flawed. We applaud the researchers who discovered this flaw, and who further proceeded to rectify the proof for the Continuous Pursuit Algorithm (CPA). The latter proof examines the monotonicity property of the proba…
Stochastic discretized learning-based weak estimation: a novel estimation method for non-stationary environments
2016
The task of designing estimators that are able to track time-varying distributions has found promising applications in many real-life problems.Existing approaches resort to sliding windows that track changes by discarding old observations. In this paper, we report a novel estimator referred to as the Stochastic Discretized Weak Estimator (SDWE), that is based on the principles of discretized Learning Automata (LA). In brief, the estimator is able to estimate the parameters of a time varying binomial distribution using finite memory. The estimator tracks changes in the distribution by operating a controlled random walk in a discretized probability space. The steps of the estimator are discre…
Distributed learning automata for solving a classification task
2016
In this paper, we propose a novel classifier in two-dimensional feature spaces based on the theory of Learning Automata (LA). The essence of our scheme is to search for a separator in the feature space by imposing a LA based random walk in a grid system. To each node in the gird we attach an LA, whose actions are the choice of the edges forming the separator. The walk is self-enclosing, i.e, a new random walk is started whenever the walker returns to starting node forming a closed classification path yielding a many edged polygon. In our approach, the different LA attached at the different nodes search for a polygon that best encircles and separates each class. Based on the obtained polygon…