Search results for "Machine"
showing 10 items of 2592 documents
Hyperspectral LCTF-based system for classification of decay in mandarins caused by Penicillium digitatum and Penicillium italicum using the most rele…
2013
[EN] Green mold (Penicillium digitatum) and blue mold (Penicillium italicum) are important sources of postharvest decay affecting the commercialization of mandarins. These fungi infections produce enormous economic losses in mandarin production if early detection is not carried out. Nowadays, this detection is performed manually in dark chambers, where the fruit is illuminated by ultraviolet light to produce fluorescence, which is potentially dangerous for humans. This paper documents a new methodology based on hyperspectral imaging and advanced machine-learning techniques (artificial neural networks and classification and regression trees) for the segmentation and classification of images …
Hyperspectral Texture Metrology Based on Joint Probability of Spectral and Spatial Distribution
2021
International audience; Texture characterization from the metrological point of view is addressed in order to establish a physically relevant and directly interpretable feature. In this regard, a generic formulation is proposed to simultaneously capture the spectral and spatial complexity in hyperspectral images. The feature, named relative spectral difference occurrence matrix (RSDOM) is thus constructed in a multireference, multidirectional, and multiscale context. As validation, its performance is assessed in three versatile tasks. In texture classification on HyTexiLa, content-based image retrieval (CBIR) on ICONES-HSI, and land cover classification on Salinas, RSDOM registers 98.5% acc…
Measuring the Novelty of Natural Language Text Using the Conjunctive Clauses of a Tsetlin Machine Text Classifier
2020
Most supervised text classification approaches assume a closed world, counting on all classes being present in the data at training time. This assumption can lead to unpredictable behaviour during operation, whenever novel, previously unseen, classes appear. Although deep learning-based methods have recently been used for novelty detection, they are challenging to interpret due to their black-box nature. This paper addresses \emph{interpretable} open-world text classification, where the trained classifier must deal with novel classes during operation. To this end, we extend the recently introduced Tsetlin machine (TM) with a novelty scoring mechanism. The mechanism uses the conjunctive clau…
Standard Vs Uniform Binary Search and Their Variants in Learned Static Indexing: The Case of the Searching on Sorted Data Benchmarking Software Platf…
2023
Learned Indexes are a novel approach to search in a sorted table. A model is used to predict an interval in which to search into and a Binary Search routine is used to finalize the search. They are quite effective. For the final stage, usually, the lower_bound routine of the Standard C++ library is used, although this is more of a natural choice rather than a requirement. However, recent studies, that do not use Machine Learning predictions, indicate that other implementations of Binary Search or variants, namely k-ary Search, are better suited to take advantage of the features offered by modern computer architectures. With the use of the Searching on Sorted Sets SOSD Learned Indexing bench…
Probing the low-temperature chemistry of ethanol via the addition of dimethyl ether
2018
Considering the importance of ethanol (EtOH) as an engine fuel and a key component of surrogate fuels, the further understanding of its auto-ignition and oxidation characteristics at engine-relevant conditions (high pressures and low temperatures) is still necessary. However, it remains difficult to measure ignition delay times for ethanol at temperatures below 850 K with currently available facilities including shock tube and rapid compression machine due to its low reactivity. Considering the success of our recent study of toluene oxidation under similar conditions [38], dimethyl ether (DME) has been selected as a radical initiator to explore the low-temperature reactivity of ethanol. In …
Modelling of a hydro-pneumatic system for heave compensation
2018
This paper presents a mathematical model of the dynamic behaviour of a passive heave compensation system. The main purpose is to develop a model that enables cost-efficient prototyping and testing of the control system in an active heave compensator. The physics are described by first principles, and result in 21 ordinary differential equations. Temperature calculations are included as an option during simulation in order to investigate its effect on the results. Similarly is a non-ideal gas law (Redlich-Kwong equation) implemented and compared to the ideal gas law. Verification against field data shows that the model is in good accordance with real-life drilling operations. It is further s…
Accelerated dinuclear palladium catalyst identification through unsupervised machine learning.
2021
Although machine learning bears enormous potential to accelerate developments in homogeneous catalysis, the frequent need for extensive experimental data can be a bottleneck for implementation. Here, we report an unsupervised machine learning workflow that uses only five experimental data points. It makes use of generalized parameter databases that are complemented with problem-specific in silico data acquisition and clustering. We showcase the power of this strategy for the challenging problem of speciation of palladium (Pd) catalysts, for which a mechanistic rationale is currently lacking. From a total space of 348 ligands, the algorithm predicted, and we experimentally verified, a number…
Basic Chemometric Tools
2013
Abstract The authentication of protected designation of origin and other protected geographical indications for foods involves the need for a deep knowledge of these kinds of samples and the correct identification of appropriate markers that are suitable to be used for authentication purposes. For this, significance tests must be developed and applied to provide evidence in a fast and accurate way; from this, it seems clear that advances in analytical tools, to obtain data regarding food chemical composition, and chemometric data treatments must be continued to provide to the users powerful identification methodologies. In this sense, the objective must be to differentiate between foods pro…
Methods for Experimentally Determining Stiffness of a Multi-Axis Machining Centre
2019
This paper deals with global methods for experimentally determining the static stiffness of multi-axis machining centres. Different devices used for measuring deflection, in specific, are explored, where accuracy and usability are highlighted. The methods were tested on a 3-axis CNC milling machine, 2-axis trunnion table and a 6-DOF industrial robot.
Benchmarking Wilms’ tumor in multisequence MRI data: why does current clinical practice fail? Which popular segmentation algorithms perform well?
2019
Wilms' tumor is one of the most frequent malignant solid tumors in childhood. Accurate segmentation of tumor tissue is a key step during therapy and treatment planning. Since it is difficult to obtain a comprehensive set of tumor data of children, there is no benchmark so far allowing evaluation of the quality of human or computer-based segmentations. The contributions in our paper are threefold: (i) we present the first heterogeneous Wilms' tumor benchmark data set. It contains multisequence MRI data sets before and after chemotherapy, along with ground truth annotation, approximated based on the consensus of five human experts. (ii) We analyze human expert annotations and interrater varia…