Konu "Transfer learning" için Araştırma Çıktıları | TR-Dizin | WoS | Scopus | PubMed listeleme
Toplam kayıt 6, listelenen: 1-6
-
Detection of damaged buildings after an earthquake with convolutional neural networks in conjunction with image segmentation
(Springer, 2021)Detecting damaged buildings after an earthquake as quickly as possible is important for emergency teams to reach these buildings and save the lives of many people. Today, damaged buildings after the earthquake are carried ... -
Detection of forest fire using deep convolutional neural networks with transfer learning approach[Formula presented
(Elsevier Ltd, 2023)Forest fires caused by natural causes such as climate change, temperature increase, lightning strikes, volcanic activity or human effects are among the world's most dangerous, deadly, and destructive disasters. Detection, ... -
Improving brain tumor classification with combined convolutional neural networks and transfer learning
(Elsevier B.V., 5 Septembe)Brain tumors pose a serious threat, causing the deaths of thousands of people worldwide, and can lead to life-threatening consequences when not accurately diagnosed. The classification of brain tumors and the determination ... -
Integrated deep learning and ensemble learning model for deep feature-based wheat disease detection
(Elsevier Inc., 2024)Early detection of plant diseases is critical to prevent disease spread and assist farmers. Thanks to their high discrimination ability, Convolutional Neural Network (CNN)-based architectures can offer practical solutions ... -
MediNet: transfer learning approach with MediNet medical visual database
(Springer, 2023)The rapid development of machine learning has increased interest in the use of deep learning methods in medical research. Deep learning in the medical field is used in disease detection and classification problems in the ... -
Transfer Learning Approach and Nucleus Segmentation with MedCLNet Colon Cancer Database
(SPRINGER, 2022)Machine learning has been recently used especially in the medical field. In the diagnosis of serious diseases such as cancer, deep learning techniques can be used to reduce the workload of experts and to produce quick ...