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Found 7 papers, 1 papers with code
Transfer Learning with Ensembles of Deep Neural Networks for Skin Cancer Detection in Imbalanced Data Sets
We propose a novel ensemble-based CNN architecture where multiple CNN models, some of which are pre-trained and some are trained only on the data at hand, along with auxiliary data in the form of metadata associated with the input images, are combined using a meta-learner.
Extracting Signals of Higgs Boson From Background Noise Using Deep Neural Networks
Higgs boson is a fundamental particle, and the classification of Higgs signals is a well-known problem in high energy physics.
Wind Speed Prediction using Deep Ensemble Learning with a Jet-like Architecture
Inspired by the shape and working of a jet, a novel Deep Ensemble Learning using Jet-like Architecture (DEL-Jet) technique is proposed to enhance the diversity and robustness of a learning system against the variations in the input space.
Malware Classification using Deep Learning based Feature Extraction and Wrapper based Feature Selection Technique
The proposed DLMD technique uses both the byte and ASM files for feature engineering, thus classifying malware families.
A Recent Survey on the Applications of Genetic Programming in Image Processing
GP has thus been used in different ways for Image Processing since its inception.
A Survey of the Recent Architectures of Deep Convolutional Neural Networks
The availability of a large amount of data and improvement in the hardware technology has accelerated the research in CNNs, and recently interesting deep CNN architectures have been reported.
Adaptive Transfer Learning in Deep Neural Networks: Wind Power Prediction using Knowledge Transfer from Region to Region and Between Different Task Domains
This paper introduces the idea of Adaptive Transfer Learning in Deep Neural Networks (ATL-DNN) for wind power prediction.
