Sökning: "Deep neural network"
Visar resultat 1 - 5 av 292 uppsatser innehållade orden Deep neural network.
- Master-uppsats, KTH/Medicinteknik och hälsosystem
Sammanfattning : Malignant melanoma is the deadliest form of skin cancer. If correctly diagnosed in time, the expected five-year survival rate can increase up to 97 %. Therefore, exploring various methods for early detection can contribute with tools which can be used to improve detection of disease and finally to make sure that help is given in time. LÄS MER
- Master-uppsats, Lunds universitet/Matematik LTH
Sammanfattning : Prostate cancer is one of the most common types of cancer for men, making proper diagnostic essential. Using machine learning as a tool to help in digital pathology has become increasingly popular and helps to limit the high intra observer variability between pathologists. LÄS MER
3. Providing Mass Context to a Pretrained Deep Convolutional Neural Network for Breast Mass ClassificationKandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS); KTH/Skolan för elektroteknik och datavetenskap (EECS)
Sammanfattning : Breast cancer is one of the most common cancers among women in the world, and the average error rate among radiologists during diagnosis is 30%. Computer-aided medical diagnosis aims to assist doctors by giving them a second opinion, thus decreasing the error rate. LÄS MER
4. Analyzing Radial Basis Function Neural Networks for predicting anomalies in Intrusion Detection SystemsMaster-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)
Sammanfattning : In the 21st century, information is the new currency. With the omnipresence of devices connected to the internet, humanity can instantly avail any information. However, there are certain are cybercrime groups which steal the information. LÄS MER
- Master-uppsats, Linköpings universitet/Datorteknik
Sammanfattning : A convolutional neural network (CNN) is a deep learning framework that is widely used in computer vision. A CNN extracts important features of input images by perform- ing convolution and reduces the parameters in the network by applying pooling operation. LÄS MER