deep learning models
Content Selection in Deep Learning Models of Summarization
... Content selection is a central component in many natural language generation tasks, where, given a generation goal, the system must determine which information should be expressed in the output text (Gatt and Krahmer, ...
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Deep Learning Models for Sentiment Analysis in Arabic
... machine learning (ML) techniques, where senti- ment analysis is formalized as a classification ...documents. Deep learning has been recently considered for sentiment analysis (Socher et ...Other ...
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The potential of synthetic training data for training deep learning models
... of deep learning is the shortage of data for training deep learning ...which models were trained using data sets with sizes of 5, 10, 20, 50, 100 and 200 images show that a low dataset ...
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Recognition Of Animal Species On Camera Trap Images Using Machine Learning And Deep Learning Models
... machine learning algorithms including Support Vector Machine (SVM), Random Forest (RF) and deep learning models such as Alexnet, Inception V3 for classification of animal ...which deep ...
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Applying Deep Learning Models to Mouse Behavior Recognition
... https://doi.org/10.4236/jbise.2019.122012 186 J. Biomedical Science and Engineering In the created mouse behavior dataset, among totally more than 9000 short clips, only 4200 clips that are most unambiguous were selected ...
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List of Deep Learning Models
... early models for deep learning [1-8]. Deep learning methods very fast emerged and expanded applications in various scientific and engineer- ing ...machine learning algo- rithms, ...
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Training deep learning models to count based on synthetic data
... of deep learning has advanced enormously. Deep learning enables training of a neural network or model, which is capable of learning relations in data at a level that humans can most of ...
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Combining Shallow and Deep Learning for Aggressive Text Detection
... For deep learning models, we tried using a CNN and a BiLSTM network ...both models were GloVe (Pennington et ...each deep learning ...with learning rate values of ...
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Cooking is All About People: Comment Classification on Cookery Channels Using Bert and Classification Models (Malayalam-English Mix-Code)
... and Deep Learning (Convolutional Neural Network, Long Short-Term Memory Network, and Long-Term Recurrent Convolutional Network) ...classical models such as Support Vector Machines (SVM) and Neural ...
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Automatic Generation of Photorealistic Image Fillers for Privacy Enabled Urban Basemaps using Generative Adversarial Networks
... machine learning and particularly Deep Learning ...mathematical models that can solve complex problems without the need of expert domain ...Such models have achieved impressive results ...
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Deep Learning: Approaches and Challenges
... popular deep learning tools and libraries that are available to construct and execute efficiently deep learning ...Environment, deep learning toolk- its provide a development ...
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Vol 7, No 10 (2017)
... approachestypicallyconsidersupervised learning to getsensible feature ...in deep feature learning was created by Hinton and ...of deep learning models have shown spectacular ...
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A Comparative Study of Alzheimer’s Disease Classification using Multiple Transfer Learning Models
... machine learning techniques, particularly predictive algorithms and automatic recognition of patterns in medical ...transfer learning has been utilized to classify Magnetic Resonance (MR) images by a ...
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Deep Learning: A Vision for Computer
... Machine learning and deep learning are the branches of the artificial ...prediction. Deep learning is précised version of machine learning that reduces many efforts involved in ...
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Dynamic Models for Entity Trajectory Prediction Using Deep Learning
... Many deep learning models like RNNs and CNNs have been applied to such sequence-to-sequence modelling ...our models include many other output classes other than humans such as bikers, cars, ...
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Deep Reinforcement Learning for Mention Ranking Coreference Models
... Mention-ranking models score pairs of mentions for their likelihood of coreference rather than compar- ing partial coreference ...mention-ranking models are fast, scalable, and simple to train, caus- ing ...
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Identification of Wheel Spinning Cases while Learning and Retaining a Skill in Intelligent Tutoring Systems
... mastery learning data from Cognitive ...towards learning and amount learned and perception [8]of the system was modeled using combination of machine learning methods and classical statistical ...
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What Do We Learn from Word Associations? Evaluating Machine Learning Algorithms for the Extraction of Contextual Word Meaning in Natural Language Processing
... Keywords: Machine Learning; Algorithms; Natural Language Processing, Deep Learning, Vector 29.. Space Models, Semantic Similarity, Distributional Semantics, Latent Semantic Analys[r] ...
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Learning Deep Architectures for AI - Free Computer, Programming, Mathematics, Technical Books, Lecture Notes and Tutorials
... and learning becomes essential in this ...multi-task learning [7, 8, 32, 88, ...tasks. Deep learning algorithms are based on learning intermediate rep- resentations which can be shared ...
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A Review on Democratization of Machine Learning In Cloud
... It is a very powerful tool that enable everyone (even those who do not belong to machine learning background) to build and deploy powerful image recognition software. The functionality of Object Detection API ...
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