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Wyniki wyszukiwania dla: CANCER & BLUR RECOGNITION
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Blur recognition using second fundamental form of image surface
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Viruses, cancer and non-self recognition
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Recognition Dynamics of Cancer Mutations on the ERp57-Tapasin Interface
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Cancer immune escape: the role of antigen presentation machinery
PublikacjaThe mechanisms of antigen processing and presentation play a crucial role in the recognition and targeting of cancer cells by the immune system. Cancer cells can evade the immune system by downregulating or losing the expression of the proteins recognized by the immune cells as antigens, creating an immunosuppressive microenvironment, and altering their ability to process and present antigens. This review focuses on the mechanisms...
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Ultrasound and Clinical Preoperative Characteristics for Discrimination Between Ovarian Metastatic Colorectal Cancer and Primary Ovarian Cancer: A Case-Control Study
PublikacjaThe aim of this study was to describe the clinical and sonographic features of ovarian metastases originating from colorectal cancer (mCRC), and to discriminate mCRC from primary ovarian cancer (OC). We conducted a multi-institutional, retrospective study of consecutive patients with ovarian mCRC who had undergone ultrasound examination using the International Ovarian Tumor Analysis (IOTA) terminology, with the addition of evaluating...
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ADT in mammography
PublikacjaWe discuss limitations of the known methods of IR imaging in diagnostics of breast cancer. In conclusion we show that for practical reasons one requires new approaches because the known methods based on simple observation of external temperature distribution are not fully effective. Even advanced pattern recognition could not help too much for static images. We ask the question: may active dynamic thermography, known in nondestructive...
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DIAGNOSIS OF MALIGNANT MELANOMA BY NEURAL NETWORK ENSEMBLE-BASED SYSTEM UTILISING HAND-CRAFTED SKIN LESION FEATURES
PublikacjaMalignant melanomas are the most deadly type of skin cancer but detected early have high chances for successful treatment. In the last twenty years, the interest of automated melanoma recognition detection and classification dynamically increased partially because of public datasets appearing with dermatoscopic images of skin lesions. Automated computer-aided skin cancer detection in dermatoscopic images is a very challenging task...
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Selected Technical Issues of Deep Neural Networks for Image Classification Purposes
PublikacjaIn recent years, deep learning and especially Deep Neural Networks (DNN) have obtained amazing performance on a variety of problems, in particular in classification or pattern recognition. Among many kinds of DNNs, the Convolutional Neural Networks (CNN) are most commonly used. However, due to their complexity, there are many problems related but not limited to optimizing network parameters, avoiding overfitting and ensuring good...
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Chemical hazard in glacial melt? The glacial system as a secondary source of POPs (in the Northern Hemisphere). A systematic review
PublikacjaToxicity of compounds belonging to persistent organic pollutants (POPs) iswidely known, and their re-emission from glaciers has been conclusively demonstrated. However, the harmful effects associated with such secondary emissions have yet to be thoroughly understood, especially in the spatial and temporal context, as the existing literature has a clear sampling biaswith the best recognition of sites in the European Alps. In this...
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Myrosinase activity in different plant samples; optimisation of measurement conditions for spectrophotometric and pH-stat methods
PublikacjaMyrosinase found in Brassicaceae plants, is the enzyme responsible for hydrolysis of glucosinolates. As a result a variety of biologically active metabolites are liberated, whose importance in crop protection and especially in cancer chemoprevention is rapidly gaining recognition. The growing practical application of glucosinolate degradation products requires that sensitive and reliable methods of myrosinase activity determination...
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Uncertainty in emotion recognition
PublikacjaPurpose–The purpose of this paper is to explore uncertainty inherent in emotion recognition technologiesand the consequences resulting from that phenomenon.Design/methodology/approach–The paper is a general overview of the concept; however, it is basedon a meta-analysis of multiple experimental and observational studies performed over the past couple of years.Findings–The mainfinding of the paper might be summarized as follows:...
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Covalent DNA modification by products of myrosinase catalysed glucosinolate degradation in cell-free system
PublikacjaThe bioactive phytochemicals found in Brassica vegetables belonging to glucosinolates (GLS) and especially the products of their degradation isothiocyanates (ITC) and indoles are regarded as the most promising cancer chemopreventive compounds. These secondary metabolites constitute defence system repelling or preventing the development of agrophages attacking brassica plants. The antibiological properties of these compounds suggest...
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Recognition and sensing of anions
PublikacjaMolecular ion recognition is one of the most intensively studied areas of supramolecular technology. The reason for this is the essential role that ions play in many biological as well as industrial processes. On the other hand, however, it has been proved that ions can have a negative impact on human health and the environment. For these reasons, it is extremly important to develop rapid and simple methods allowing the determination...
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Language Models in Speech Recognition
PublikacjaThis chapter describes language models used in speech recognition, It starts by indicating the role and the place of language models in speech recognition. Mesures used to compare language models follow. An overview of n-gram, syntactic, semantic, and neural models is given. It is accompanied by a list of popular software.
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Integration in Multichannel Emotion Recognition
PublikacjaThe paper concerns integration of results provided by automatic emotion recognition algorithms. It presents both the challenges and the approaches to solve them. Paper shows experimental results of integration. The paper might be of interest to researchers and practitioners who deal with automatic emotion recognition and use more than one solution or multichannel observation.
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Endoscopy video analysis algorithms and their independence of rotation , brightness , contrast , color and blur
PublikacjaThe article presents selected image analysis algorithms for endoscopy videos. Mathematical methods that are part of these algorithms are described, and authors’ claims about the characteristics of these algorithms, such as the independence of rotation, brightness, contrast, etc. are mentioned. Using the common test on the real endoscopic image database and a set of image transformations, the validity of these claims was checked...
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Human emotion recognition with biosignals
PublikacjaThis chapter presents issues in the field of affective computing. Basic preliminary information for the recognition of emotions is given and models of emotions, various ways of evoking emotions, as well as their theoretical foundations are discussed. The particular attention is given to the use of physiological signals in recognizing emotions. This subject is outlined further below by presenting selected biosignals, their relationship...
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Gold nanoparticles for cancer radiotherapy: a review
PublikacjaRadiotherapy is currently used in around 50% of cancer treatments and relies on the deposition of energy directly into tumour tissue. Although it is generally effective, some of the deposited energy can adversely affect healthy tissue outside the tumour volume, especially in the case of photon radiation (gamma and X-rays). Improved radiotherapy outcomes can be achieved by employing ion beams due to the characteristic energy deposition...
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Effect Of Resveratrol And Quercetin On Telomerase Regulation In Cancer Cells And Their Anti-Cancer Potential
PublikacjaTelomeres and telomerase are nowadays one on targets for anticancer therapy. Telomerase is expressed in ~90% of human cancer cell lines and tumor specimens, whereas its enzymatic activity is not detectable in most human somatic cells. Was found that some dietary compounds can modulate telomerase activity in cancer cells. This review summarizes the current knowledge about the effects of resveratrol and quercetin on telomerase regulation...
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Human UDP-Glucuronosyltransferases: Effects of altered expression in breast and pancreatic cancer cell lines.
PublikacjaIncreased aerobic glycolysis and de novo lipid biosynthesis are common characteristics of invasive cancers. UDP-glucuronosyltransferases (UGTs) are phase II drug metabolizing enzymes that in normal cells possess the ability to glucuronidate these lipids and speed their excretion; however, de-regulation of these enzymes in cancer cells can lead to an accumulation of bioactive lipids, which further fuels cancer progression. We hypothesize...
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Automatic sound recognition for security purposes
PublikacjaIn the paper an automatic sound recognition system is presented. It forms a part of a bigger security system developed in order to monitor outdoor places for non-typical audio-visual events. The analyzed audio signal is being recorded from a microphone mounted in an outdoor place thus a non stationary noise of a significant energy is present in it. In the paper an especially designed algorithm for outdoor noise reduction is presented,...
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Recognition of Hand Drawn Flowcharts
PublikacjaIn this paper the problem of hand drawn flowcharts recognition is presented. There are described two attitudes to this problem: on-line and off-line. A concept of FCE, a system for recognizing and understanding of freehand drawn on-line flow charts on desktop computer and mobile devices is presented. The first experiments with the FCE system and the planes for future are also described.
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Semantic Integration of Heterogeneous Recognition Systems
PublikacjaComputer perception of real-life situations is performed using a variety of recognition techniques, including video-based computer vision, biometric systems, RFID devices and others. The proliferation of recognition modules enables development of complex systems by integration of existing components, analogously to the Service Oriented Architecture technology. In the paper, we propose a method that enables integration of information...
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Using Physiological Signals for Emotion Recognition
PublikacjaRecognizing user’s emotions is the promising area of research in a field of human-computer interaction. It is possible to recognize emotions using facial expression, audio signals, body poses, gestures etc. but physiological signals are very useful in this field because they are spontaneous and not controllable. In this paper a problem of using physiological signals for emotion recognition is presented. The kinds of physiological...
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Emotion Recognition for Affect Aware Video Games
PublikacjaIn this paper the idea of affect aware video games is presented. A brief review of automatic multimodal affect recognition of facial expressions and emotions is given. The first result of emotions recognition using depth data as well as prototype affect aware video game are presented
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Emotion Recognition and Its Applications
PublikacjaThe paper proposes a set of research scenarios to be applied in four domains: software engineering, website customization, education and gaming. The goal of applying the scenarios is to assess the possibility of using emotion recognition methods in these areas. It also points out the problems of defining sets of emotions to be recognized in different applications, representing the defined emotional states, gathering the data and...
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Rough Sets Applied to Mood of Music Recognition
PublikacjaWith the growth of accessible digital music libraries over the past decade, there is a need for research into automated systems for searching, organizing and recommending music. Mood of music is considered as one of the most intuitive criteria for listeners, thus this work is focused on the emotional content of music and its automatic recognition. The research study presented in this work contains an attempt to music emotion recognition...
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Examining Feature Vector for Phoneme Recognition
PublikacjaThe aim of this paper is to analyze usability of descriptors coming from music information retrieval to the phoneme analysis. The case study presented consists in several steps. First, a short overview of parameters utilized in speech analysis is given. Then, a set of time and frequency domain-based parameters is selected and discussed in the context of stop consonant acoustical characteristics. A toolbox created for this purpose...
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Emotion Recognition Using Physiological Signals
PublikacjaIn this paper the problem of emotion recognition using physiological signals is presented. Firstly the problems with acquisition of physiological signals related to specific human emotions are described. It is not a trivial problem to elicit real emotions and to choose stimuli that always, and for all people, elicit the same emotion. Also different kinds of physiological signals for emotion recognition are considered. A set of...
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Facial emotion recognition using depth data
PublikacjaIn this paper an original approach is presented for facial expression and emotion recognition based only on depth channel from Microsoft Kinect sensor. The emotional user model contains nine emotions including the neutral one. The proposed recognition algorithm uses local movements detection within the face area in order to recognize actual facial expression. This approach has been validated on Facial Expressions and Emotions Database...
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Emotion recognition and its application in software engineering
PublikacjaIn this paper a novel application of multimodal emotion recognition algorithms in software engineering is described. Several application scenarios are proposed concerning program usability testing and software process improvement. Also a set of emotional states relevant in that application area is identified. The multimodal emotion recognition method that integrates video and depth channels, physiological signals and input devices...
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Dependable Integration of Medical Image Recognition Components
PublikacjaComputer driven medical image recognition may support medical doctors in the diagnosis process, but requires high dependability considering potential consequences of incorrect results. The paper presentsa system that improves dependability of medical image recognition by integration of results from redundant components. The components implement alternative recognition algorithms of diseases in thefield of gastrointestinal endoscopy....
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Feature extraction in detection and recognition of graphical objects
PublikacjaDetection and recognition of graphic objects in images are of great and growing importance in many areas, such as medical and industrial diagnostics, control systems in automation and robotics, or various types of security systems, including biometric security systems related to the recognition of the face or iris of the eye. In addition, there are all systems that facilitate the personal life of the blind people, visually impaired...
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Mining inconsistent emotion recognition results with the multidimensional model
PublikacjaThe paper deals with the challenge of inconsistency in multichannel emotion recognition. The focus of the paper is to explore factors that might influence the inconsistency. The paper reports an experiment that used multi-camera facial expression analysis with multiple recognition systems. The data were analyzed using a multidimensional approach and data mining techniques. The study allowed us to explore camera location, occlusions...
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Guido: a musical score recognition system
PublikacjaThis paper presents an optical music recognition system Guido that can automatically recognize the main musical symbols of music scores that were scanned or taken by a digital camera. The application is based on object model of musical notation and uses linguistic approach for symbol interpretation and error correction. The system offers musical editor with a partially automatic error correction.
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Multimodal English corpus for automatic speech recognition
PublikacjaA multimodal corpus developed for research of speech recognition based on audio-visual data is presented. Besides usual video and sound excerpts, the prepared database contains also thermovision images and depth maps. All streams were recorded simultaneously, therefore the corpus enables to examine the importance of the information provided by different modalities. Based on the recordings, it is also possible to develop a speech...
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Multiclass AdaBoost Classifier Parameter Adaptation for Pattern Recognition
PublikacjaThe article presents the problem of parameter value selection of the multiclass ``one against all'' approach of an AdaBoost algorithm in tasks of object recognition based on two-dimensional graphical images. AdaBoost classifier with Haar features is still used in mobile devices due to the processing speed in contrast to other methods like deep learning or SVM but its main drawback is the need to assembly the results of binary...
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Voice command recognition using hybrid genetic algorithm
PublikacjaAbstract: Speech recognition is a process of converting the acoustic signal into a set of words, whereas voice command recognition consists in the correct identification of voice commands, usually single words. Voice command recognition systems are widely used in the military, control systems, electronic devices, such as cellular phones, or by people with disabilities (e.g., for controlling a wheelchair or operating a computer...
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Investigating Feature Spaces for Isolated Word Recognition
PublikacjaMuch attention is given by researchers to the speech processing task in automatic speech recognition (ASR) over the past decades. The study addresses the issue related to the investigation of the appropriateness of a two-dimensional representation of speech feature spaces for speech recognition tasks based on deep learning techniques. The approach combines Convolutional Neural Networks (CNNs) and timefrequency signal representation...
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Anion recognition by n,n'-diarylalkanediamides
PublikacjaThe preparation of N,N'-diarylalkanediamides from respective aliphatic dicarboxylic acidesand 4-nitroaniline via microwave-promoted reactions is presented. The most positive effect of microwave irradiation was observed for N,N'-bis(4-nitrophenyl)butanediamide. Anion binding studies on the obtained diamides were carried out in DMSO and acetonitrile using UV-vis and 1H NMR spectroscopy. A mechanism for selective fluoride recognition...
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Examining Influence of Distance to Microphone on Accuracy of Speech Recognition
PublikacjaThe problem of controlling a machine by the distant-talking speaker without a necessity of handheld or body-worn equipment usage is considered. A laboratory setup is introduced for examination of performance of the developed automatic speech recognition system fed by direct and by distant speech acquired by microphones placed at three different distances from the speaker (0.5 m to 1.5 m). For feature extraction from the voice signal...
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Bridging challenges of clinical decision support systems with a semantic approach. A case study on breast cancer
PublikacjaThe integration of Clinical Decision Support Systems (CDSS) in nowadays clinical environments has not been fully achieved yet. Although numerous approaches and technologies have been proposed since 1960, there are still open gaps that need to be bridged. In this work we present advances from the established state of the art, overcoming some of the most notorious reported difficulties in: (i) automating CDSS, (ii) clinical workflow...
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Robust and Efficient Machine Learning Algorithms for Visual Recognition
PublikacjaIn visual recognition, the task is to identify and localize all objects of interest in the input image. With the ubiquitous presence of visual data in modern days, the role of object recognition algorithms is becoming more significant than ever and ranges from autonomous driving to computer-aided diagnosis in medicine. Current models for visual recognition are dominated by models based on Convolutional Neural Networks (CNNs), which...
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AN ALGORITHM FOR PORTAL HYPERTENSIVE GASTROPATHY RECOGNITION ON THE ENDOSCOPIC RECORDINGS
PublikacjaSymptoms recognition of portal hypertensive gastropathy (PHG) can be done by analysing endoscopic recordings, but manual analysis done by physician may take a long time. This increases probability of missing some symptoms and automated methods may be applied to prevent that. In this paper a novel hybrid algorithm for recognition of early stage of portal hypertensive gastropathy is proposed. First image preprocessing is described....
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Limitations of Emotion Recognition in Software User Experience Evaluation Context
PublikacjaThis paper concerns how an affective-behavioural- cognitive approach applies to the evaluation of the software user experience. Although it may seem that affect recognition solutions are accurate in determining the user experience, there are several challenges in practice. This paper aims to explore the limitations of the automatic affect recognition applied in the usability context as well as...
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Accelerometer signal pre-processing influence on human activity recognition
PublikacjaA study of data pre-processing influence on accelerometer-based human activity recognition algorithms is presented. The frequency band used to filter-out the accelerometer signals and the number of accelerometers involved were considered in terms of their influence on the recognition accuracy.
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Investigating Feature Spaces for Isolated Word Recognition
PublikacjaThe study addresses the issues related to the appropriateness of a two-dimensional representation of speech signal for speech recognition tasks based on deep learning techniques. The approach combines Convolutional Neural Networks (CNNs) and time-frequency signal representation converted to the investigated feature spaces. In particular, waveforms and fractal dimension features of the signal were chosen for the time domain, and...
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Bimodal Emotion Recognition Based on Vocal and Facial Features
PublikacjaEmotion recognition is a crucial aspect of human communication, with applications in fields such as psychology, education, and healthcare. Identifying emotions accurately is challenging, as people use a variety of signals to express and perceive emotions. In this study, we address the problem of multimodal emotion recognition using both audio and video signals, to develop a robust and reliable system that can recognize emotions...
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Music Genre Recognition in the Rough Set-Based Environment
PublikacjaThe aim of this paper is to investigate music genre recognition in the rough set-based environment. Experiments involve a parameterized music data-base containing 1100 music excerpts. The database is divided into 11 classes cor-responding to music genres. Tests are conducted using the Rough Set Exploration System (RSES), a toolset for analyzing data with the use of methods based on the rough set theory. Classification effectiveness...
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Emotion Recognition from Physiological Channels Using Graph Neural Network
PublikacjaIn recent years, a number of new research papers have emerged on the application of neural networks in affective computing. One of the newest trends observed is the utilization of graph neural networks (GNNs) to recognize emotions. The study presented in the paper follows this trend. Within the work, GraphSleepNet (a GNN for classifying the stages of sleep) was adjusted for emotion recognition and validated for this purpose. The...