
mgr inż. Arkadiusz Kwasigroch
Employment
- Assistant at Department of Control Systems Engineering
Keywords Help
- deep learning
- machine learning
- convolutional neural networks
- decision support
- image processing
- malignant melanoma
- artifcial intelligence
- artificial neural networks
- batch normalization, transfer learning, dropout
- decision support, diagnostics, image processing, artificial neural networks, ensemble of neural networks, melanoma malignant
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Publication showcase
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DEEP CONVOLUTIONAL NEURAL NETWORKS AS A DECISION SUPPORT TOOL IN MEDICAL PROBLEMS – MALIGNANT MELANOMA CASE STUDY
The paper presents utilization of one of the latest tool from the group of Machine learning techniques, namely Deep Convolutional Neural Networks (CNN), in process of decision making in selected medical problems. After the survey of the most successful applications of CNN in solving medical problems, the paper focuses on the very difficult problem of automatic analyses of the skin lesions. The authors propose the CNN structure...
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Intelligent system supporting diagnosis of malignant melanoma
Malignant melanomas are the most deadly type of skin cancers. Early diagnosis is a key for successful treatment and survival. The paper presents the system for supporting the process of diagnosis of skin lesions in order to detect a malignant melanoma. The paper describes the development process of an intel-ligent system purposed for the diagnosis of malignant melanoma. Presented sys-tem can be used as a decision support system...
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Selected Technical Issues of Deep Neural Networks for Image Classification Purposes
In 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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