Piotr Boniecki - Academia.edu (original) (raw)

Papers by Piotr Boniecki

Eleventh International Conference on Digital Image Processing (ICDIP 2019)

In this paper an attempt was made to build classification models, based on convolutional neural n... more In this paper an attempt was made to build classification models, based on convolutional neural networks, for identification of co-substrate composted with sewage sludge. Due to the pilot character of the studies, they were limited to two co-substrates, i.e. maize straw and rapeseed straw. In total, 12 composting experiments were carried out, each half of them with the content of each of the adopted types of straw. As a result of experiments, 2304 images of composted material samples were obtained, and they bacame the input information for the neural networks. Classification models were developed using the Tensorflow environment, TFLearn library and Python programming language. In their structure, one convolutional layer with different number of convolutional filters and one pooling layer were used to extract image features, and also two fully-connected layers were adopted for classification purposes. The training of the network was carried out with the use of the Adam optimization algorithm. Finally, 4 convolutional neural networks were developed, and their classification error estimated for the test set ranged from 4.1 to 11.0%.

Journal of Research and Applications in Agricultural Engineering, 2011

The aim of this study was to analyze the possibilities of the acquisition of information from ima... more The aim of this study was to analyze the possibilities of the acquisition of information from images of porcine oocytes using binarization. Also attentionwas paid to the main problem of this processing, which is the selection of an adequate threshold. In this study summarizes the effects of binarization for the analyzed images using different methods of selecting thresholds. Purposefulness of using this method in the test images was verified, as well as the conditions for application of the adequate parameters of binarization.

Journal of Research and Applications in Agricultural Engineering, 2017

Tenth International Conference on Digital Image Processing (ICDIP 2018), 2018

In recent years, requirements on potato tuber quality and minimization of chemical protection mea... more In recent years, requirements on potato tuber quality and minimization of chemical protection measures have steadily increased. Increasingly, the precautionary measures in the protection of potato during its vegetation, using the dressing of seed material, are increasingly taking place. Growing awareness of potato producers and increasingly restrictive plant protection standards force the use of new technologies. The quality of the process of applying chemicals to the surface of tubers of seed potato material affects the subsequent quantity and quality of the crop. The aim of the study was to validate the method of evaluating the quality of seed dressing coverage in the process of spraying tubers with a chemical based on computer image analysis.

Journal of Research and Applications in Agricultural Engineering, 2009

The aim of the following thesis was the description of chosen methods of the prediction and the c... more The aim of the following thesis was the description of chosen methods of the prediction and the comparison of their efficiency in the field of agricultural engineering with the use of artificial neural networks. There were also pointed the typologies of networks which turned out to be the most effective in the process of solving the prediction problems. METODY PROGNOZOWANIA WYBRANYCH ZAGADNIEŃ INŻYNIERII ROLNICZEJ Z WYKORZYSTANIEM SZTUCZNYCH SIECI NEURONOWYCH Streszczenie Celem pracy było omówienie neuronowych metod prognozowania oraz porównanie ich efektywności w wybranych zagadnieniach inżynierii rolniczej przy użyciu sztucznych sieci neuronowych. Wskazano przy tym topologie sieci, które w rozwiązaniu problemów predykcyjnych charakteryzowały się najlepszą skutecznością.

Journal of Research and Applications in Agricultural Engineering, 2010

The purpose of this study was the analysis of ability classification neural model type Kohonen. C... more The purpose of this study was the analysis of ability classification neural model type Kohonen. Classification has been selected three varieties of apples, which often appear in Polish orchards in the area. For purposes of comparison, a similar analysis was performed to identify the quality of dried vegetables. Neural classification was based on the information encoded in the form of a set of digital images apples and dried. As the characteristics feature adopted color and shape of apples and dried carrots. KLASYFIKACJA WYBRANYCH ODMIAN JABŁEK ORAZ SUSZU MARCHWI Z WYKORZYSTANIEM SIECI NEURONOWYCH TYPU KOHONENA Streszczenie Celem badań była analiza zdolności klasyfikacyjnych modelu neuronowego typu Kohonena, uczonego metodą "nie nadzorowaną". Klasyfikacji poddano trzy wyselekcjonowane odmiany jabłek, które często występują w sadach na terenie Polski. Ze względów porównawczych, podobną analizę przeprowadzono w celu identyfikacji jakości suszu warzywnego. Neuronowej klasyfikacji dokonano w oparciu o informację zakodowaną w postaci zbioru cyfrowych obrazów jabłek oraz suszu marchwi. Jako cechy charakterystyczne, stanowiące podstawę do przeprowadzenia klasyfikacji, przyjęto reprezentacje w postaci palety dominujących barw występujących w kolorze owoców i suszu warzywnego oraz wybranych współczynników kształtu.

Journal of Research and Applications in Agricultural Engineering, 2012

The software "USG Recognizer" that was described in this work is equipped with a binarization fun... more The software "USG Recognizer" that was described in this work is equipped with a binarization function with threshold. The application also fulfills some additional functions such as: contrast and closing. With this functionality it is possible to achieve empirical data from digital ultrasound photo of cow's womb. The artificial neural network was generated on the basis of created application. The main purpose of this network is to support an identification or exclusion of the gestation in user's ultrasound picture. "USG Recognizer" was created using Visual Paradigm (UML 8.0) and Microsoft Visual Studio 2010 Professional Edition environments.

Journal of Research and Applications in Agricultural Engineering, 2012

Image analysis and gathering data from digital images is an important element in process of gener... more Image analysis and gathering data from digital images is an important element in process of generating learning sets for the construction of the neural models. With the development of computer image analysis it is possible to obtain more data. This is a reason to create and develop computer systems that support neural image analysis and increase usability of this software.

Tenth International Conference on Digital Image Processing (ICDIP 2018), 2018

Self-Organizing Feature Map (SOFM), has been used for the qualitative identification of strawberr... more Self-Organizing Feature Map (SOFM), has been used for the qualitative identification of strawberry juice powders. The research was based on image recognition using powders obtained through an industrial spray-drying process. Results demonstrated that the color features were able to effectively distinguish the research material consisting of spray-dried powders of strawberry juice. The adequate model in terms of the lowest error value RMS (Root Mean Square) contained 46 neurons in the input layer and neurons in the output layer. The model is an effective tool for classifying wrong color changes in strawberry powders.

SPIE Proceedings, 2017

In the recent years, there has been a continuously increasing demand for vegetables and dried veg... more In the recent years, there has been a continuously increasing demand for vegetables and dried vegetables. This trend affects the growth of the dehydration industry in Poland helping to exploit excess production. More and more often dried vegetables are used in various sectors of the food industry, both due to their high nutritional qualities and changes in consumers’ food preferences. As we observe an increase in consumer awareness regarding a healthy lifestyle and a boom in health food, there is also an increase in the consumption of such food, which means that the production and crop area can increase further. Among the dried vegetables, dried carrots play a strategic role due to their wide application range and high nutritional value. They contain high concentrations of carotene and sugar which is present in the form of crystals. Carrots are also the vegetables which are most often subjected to a wide range of dehydration processes; this makes it difficult to perform a reliable qualitative assessment and classification of this dried product. The many qualitative properties of dried carrots determining their positive or negative quality assessment include colour and shape. The aim of the research was to develop and implement the model of a computer system for the recognition and classification of freeze-dried, convection-dried and microwave vacuum dried products using the methods of computer image analysis and artificial neural networks.

Ninth International Conference on Digital Image Processing (ICDIP 2017), 2017

The Web application presented here supports plant production and works with the graph database Ne... more The Web application presented here supports plant production and works with the graph database Neo4j shell to support the assessment of the condition of crops on the basis of geospatial data, including raster and vector data. The adoption of a graph database as a tool to store and manage the data, including geospatial data, is completely justified in the case of those agricultural holdings that have a wide range of types and sizes of crops. In addition, the authors tested the option of using the technology of Microsoft Cognitive Services at the level of produced application that enables an image analysis using the services provided. The presented application was designed using ASP.NET MVC technology and a wide range of leading IT tools.

The aim of this work was to discuss issues relating to synthetic neural compression of graphical ... more The aim of this work was to discuss issues relating to synthetic neural compression of graphical data using a topology of artificial neural networks. Utilitarian aspect of the analysis was the implementation of the proposed image compression technology in the original system “Sunflower.b”, supporting the processing of photos of selected agricultural objects

SPIE Proceedings, 2014

ABSTRACT The main aim of the article was to present research on the application of computer image... more ABSTRACT The main aim of the article was to present research on the application of computer image analysis in Life Science and Environmental Engineering. The authors used different methods of computer image analysis in developing of an innovative biotest in modern biomonitoring of water quality. Created tools were based on live organisms such as bioindicatorsLemna minor L. and Hydra vulgaris Pallas as well as computer image analysis method in the assessment of negatives reactions during the exposition of the organisms to selected water toxicants. All of these methods belong to acute toxicity tests and are particularly essential in ecotoxicological assessment of water pollutants. Developed bioassays can be used not only in scientific research but are also applicable in environmental engineering and agriculture in the study of adverse effects on water quality of various compounds used in agriculture and industry.

SPIE Proceedings, 2013

ABSTRACT The aim of this work was a neural identification of selected apple tree orchard pests. T... more ABSTRACT The aim of this work was a neural identification of selected apple tree orchard pests. The classification was conducted on the basis of graphical information coded in the form of selected geometric characteristics of agrofags, presented on digital images. A neural classification model is presented in this paper, optimized using learning sets acquired on the basis of information contained in digital photographs of pests. In particular, the problem of identifying 6 selected apple pests, the most commonly encountered in Polish orchards, has been addressed. In order to classify the agrofags, neural modelling methods were utilized, supported by digital analysis of image techniques.

SPIE Proceedings, 2013

ABSTRACT The environmental monitoring (EM) is an essential part of protection of the environment,... more ABSTRACT The environmental monitoring (EM) is an essential part of protection of the environment, most of the methods of environmental protection based on visual techniques or physico-chemical and biochemical measurements. The automation of traditional methods proceeds at an accelerating rate, modern laboratories prefer this type of tools to conduct a more comprehensive assessment and online monitoring. The application of computer image analysis methods in biomonitoring brings to this discipline the opportunity to develop innovative tools that allow for more precise sensitive and quantified assessment of monitored processes. The application of techniques based on computer image processing technology will dominate in the future and very comfortable and intuitive tool for researchers in the study of the components of the environment quality. The article presents some methods of automation the acute toxicity bioassay based on the application of computational methods.

Using of artificial neuron networks for identifying mechanical damage of seeds presented on photo... more Using of artificial neuron networks for identifying mechanical damage of seeds presented on photographs requires selection of proper characteristics, which can be the basis for identification process. Data choice can be verified by using the instrument of network sensitivity analysis. Thanks to its use the significance level of particular characteristics can be evaluated, and it may be verified if all selected variables are essential in the learning process.