Deep Learning Important FeaTures (DeepLIFT)
Learning Deep Features for Discriminative Localization
... Fig. 13 shows the class-specific units for AlexNet ∗ -GAP trained on ILSVRC dataset for object recognition (top) and Places Database for scene recognition (bottom). We follow a similar procedure as [33] for estimating ...
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Learning deep and shallow features for human activity recognition.
... of deep and shallow feature representations for accelerometer data on HAR with data collected from the wrist and ...and deep features which includes two hybrid ...is important to determine ...
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Deep Learning of Audio and Language Features for Humor Prediction
... We propose to predict when people would laugh in a dialog with a supervised machine learning approach. While most of the past attempts concentrate on isolated examples, the response to humor in a conversation ...
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A Robust Visual Tracking Method through Deep Learning Features
... filter, Deep learning, Convolutional neural ...most important components in many applications of computer ...through deep learning ...
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Deep learning and localized features fusion for medical image classification
... The epithelium region inside a histology image has an irregular shape and a nonuni- form size, which cannot be used directly as input to the convolutional neural network. To fix this, there are two general approaches: ...
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Age Estimation using Deep Learning on 3D Facial Features
... 3D features affect the performance of an age esti- mation model, we first create a baseline model which will be trained on 2D images ...3D features. It is also important to point out that the ...
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Learning Deep Features for Scene Recognition using Places Database
... one important property of the primate brain is its hierarchical organization in layers of increasing processing complexity, an ar- chitecture that has inspired Convolutional Neural Networks or CNNs [2, ...
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FIND: Identifying Functionally and Structurally Important Features in Protein Sequences with Deep Neural Networks
... the learning of the model, improves 372 classification ...the features learned for the different classes using a weighted, 376 convolutional network with 256 parameters in the embedding matrix is the ...
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Arabic Dialect Identification with Deep Learning and Hybrid Frequency Based Features
... Abstract Studies on Dialectical Arabic are growing more important by the day as it becomes the primary written and spoken form of Arabic on- line in informal settings. Among the impor- tant problems that should be ...
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How deep learning extracts and learns leaf features for plant classification
... of deep learning to harvest discriminatory features from leaf images by learning, and apply them as classifiers for plant ...that learning the fea- tures using CNNs can provide better ...
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Learning local embedding deep features for person re identification in camera networks
... 4.3 Evaluation on different number of regions The purpose of dividing each pedestrian image into sev- eral regions is to fully consider the structural information. Hence, it is very important to determine the ...
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NetSurfP-2.0:improved prediction of protein structural features by integrated deep learning
... Having an integrated model has an effect on the accuracy of the tool, but most importantly makes it much more time-efficient. On top of that, our software uses two different profile creation strategies in order to ...
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Lung Disease Classification using GLCM and Deep Features from Different Deep Learning Architectures with Principal Component Analysis
... an important stage in implementing a Computer Aided Diagnosis (CADx) ...textural features. However textural features may not be enough to describe properties of an ...image. Deep ...
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Learning deep features from body and parts for person re identification in camera networks
... networks, Deep feature learning, Person re-identification 1 Introduction The camera networks, as a kind of wireless sensor net- works, have received considerable attention due to the potential value for the ...
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MRI brain classification using the quantum entropy LBP and deep-learning-based features
... of learning dependencies for prolonged periods and remember important information from previous processing ...images features across time by the connected memory blocks through its ...extracted ...
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Deep Domain Adaptation Learning Framework for Associating Image Features to Tumour Gene Profile
... 1 Chapter 1 Introduction The current practices for the treatment of human cancers rely upon the establishment of accurate diagnosis, which may involve a series of complex medical procedures comprising of patient ...
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Classification with Costly Features Using Deep Reinforcement Learning
... ditional action, which has two main effects: (1) It improves performance for samples needing a large amount of features. (2) It offloads the complex samples to HPC, so the model can focus its capacity more ...
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Learning (from) Deep Hierarchical Structure among Features
... Moreover, we consider a more general case where the hi- erarchical structure is not available. A hierarchical structure can give us more insight about the relations among features but learning it from data ...
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Learning Deep Features for Shape Correspondence with Domain Invariance
... domain-specific features and the consistent placement of ...feature learning approach, using deep convolutional neural networks, to extract correspondence-friendly features from shape ...
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E-learning in Norway: Some important features, projects and providers
... education, including the Norwegian Association for Distance Education, Norway Opening Universities, Norwegian School of Management and NKS Distance Education. NKI Distance Education, which is Scandinavia’s largest ...
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