Deep Learning
Deep learning for early performance prediction of introductory programming students: a comparative and explanatory study
... adopted deep learning and traditional ML models to identify students (n=897) in need of ...that deep learning would likely achieve better results, with new combination of features and more ...
26
Developing deep learning computational tools for cancer using omics data
... TensorFlow, deep learning techniques have been used widely, especially in what concerns to computer vision, speech recognition and natural language ...reinforcement learning [53]). The fact is that ...
106
A COMPARATIVE ANALYSIS OF WEB INFORMATION EXTRACTION TECHNIQUES DEEP LEARNING vs. NAÏVE BAYES vs. BACK PROPAGATION NEURAL NETWORKS IN WEB DOCUMENT EXTRACTION
... to a web page. Each Web document has its individual URI. Note that a Web document is not the same as a file: a single Web document can be accessible in a wide range of configurations and dialects, and a single file, for ...
7
Cyberthreat discovery in open source intelligence using deep learning techniques
... through deep learning architectures and al- gorithms represents a significant advantage in terms of efficiency and accuracy, which is why we will make use of neural ...that deep learning ...
81
A Deep Learning Approach for Red Lesions Detection in Video Capsule Endoscopies
... “deep learning”, started to present significantly better results than previous methods, automatically extracting characteristics from data and thus supporting new developments in CAD systems ...of ...
9
A Deep Learning Approach to Named Entity Recognition in Portuguese Texts
... machine learning algorithms, using annotated texts to automatically train a model that performs ...line, deep learning models started to be applied to NLP and “have been shown to perform very well on ...
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Age Estimation using Deep Learning on 3D Facial Features
... training deep learning models with synthetic data, even in different domains such as 3D landmark estimation [BT17b] or in-car object detection [TPA + 18] where new synthetic cars were created using Unreal ...
92
Summarizing ETDs with deep learning
... Deep learning requires a large set of labeled training data to produce satisfactory results, but to our knowledge no sufficient training set exists for ETD ...
7
Deep learning for single image super-resolution using residual image learning and multiple degradations
... Although a lot of works focus on Super-Resolution problems with known degrada- tion/downsamping kernels, only few works try to solve blind Super-Resolution problems considering that the degradation operators from HR ...
64
Adam Deep Learning with SOM for Human Sentiment Classification
... the Deep Convolutional network is the presence of a convolution layer which usually embed a convolution operation into the input data, passing the data towards next layer ...Adam Deep Learning (ADL) ...
23
A deep learning approach for sentence classification of scientific abstracts
... Abstract. The classification of abstract sentences is a valuable tool to support scientific database querying, to summarize relevant literature works and to assist in the writing of new abstracts. This study proposes a ...
11
Automatic transcription of music using deep learning techniques
... One of the main aims of this work was to check the viability of the one-classifier-per-note approach using artificial neural networks. To accomplish that, we elaborated an initial study to find out the current ...
116
Deep learning for constructing microblog behavior representation to identify social media user’s personality
... machine learning methods to built personality prediction models and have made some achievements, there are also some disadvantages for which improvements are ...
15
Repositório Institucional da Universidade Fernando Pessoa: Deteção de incêndios florestais com recurso a Deep Learning e Visão Computacional
... O sistema proposto inicia-se pela utilizac¸˜ao de dados meteorol´ogicos numa vertente mais auxiliar pois n˜ao atuam diretamente no processo de detec¸˜ao. Pretende-se que este m´odulo seja respons´avel pela obtenc¸˜ao do ...
82
Automatic indexing of web images: trends and challenges in deep learning context :: Brapci ::
... enquanto Deep Learning, que tem como base o uso de orientações oriundas da compreensão das redes convolucionais na programação tornando possível promover a detecção, a percepção e o reconhecimento ...
21
IMPROVEMENT OF RECOGNITION QUALITY IN DEEP LEARNING NETWORKS BY SIMULATED ANNEALING METHOD
... is deep learning methods, in which automatic construction of feature transforms is taken place in tasks of pattern ...of deep learning ...for deep learning networks, which are ...
6
Chimpanzee face recognition from videos in the wild using deep learning
... using deep neural network architectures for a direct biological application: the detection, tracking, and recognition of individual animals in longitudinal video archives from the ...state-of-the-art deep ...
10
A deep learning classifier for sentence classification in biomedical and computer science abstracts
... The CS Abstracts corpus has led to worse classification results when com- pared to the PubMed 20k data. Deep learning usually relies on large datasets for better training a model [34]. Thus, we argue that ...
26
DEEP LEARNING PARA CLASSIFICAC¸ ˜AO HIER ´ARQUICA DE ELEMENTOS TRANSPON´IVEIS
... Elementos Transpon´ıveis (TEs) s˜ao sequˆencias de DNA que podem se mover de um local para outro dentro do genoma de uma c´elula. Eles contribuem para a diversidade gen´etica das esp´ecies, e seus mecanismos de ...
125
A Portuguese Flora Identification Tool Using Deep Learning
... In today’s world, deep learning (DL) models for image classification are standard in many areas, including for the identification of flora. Several models are used for this purpose, but most focus on flora ...
75