[PDF] Top 20 On the use of convolutional neural networks for robust classification of multiple fingerprint captures
Has 10000 "On the use of convolutional neural networks for robust classification of multiple fingerprint captures" found on our website. Below are the top 20 most common "On the use of convolutional neural networks for robust classification of multiple fingerprint captures".
On the use of convolutional neural networks for robust classification of multiple fingerprint captures
... the fingerprint is taken into ...the fingerprint images. Then, a 3-hidden layer neural network is applied to carry out the ...quality fingerprint images are manually selected so as to train a ... See full document
22
Convolutional Neural Networks for Sentence Classification
... on multiple benchmarks, suggesting that the pre-trained vectors are ‘universal’ feature ex- tractors that can be utilized for various classifica- tion ...the use of both pre-trained and task-specific ... See full document
6
A Sensitivity Analysis of (and Practitioners’ Guide to) Convolutional Neural Networks for Sentence Classification
... sentence classification using CNN ar- ...with multiple convolution lay- ers, positing latent, dense and low-dimensional word vectors (initialized to random values) as in- ... See full document
11
A robust modulation classification method using convolutional neural networks
... DL networks are applied as classifiers to han- dle preprocessed ...the classification. The classification accu- racy is higher than that of conventional neural ...high-accuracy ... See full document
15
Classification of lung sounds using convolutional neural networks
... The convolutional network architecture is a remarkably versatile yet conceptually simple paradigm that can be ap- plied to a wide spectrum of perceptual ...tional networks are trainable, multistage ...[11]. ... See full document
9
Deep Learning Methods On Neutron Scattering Data
... [4]. Convolutional neural networks (CNNs) is a well-known deep learning architecture inspired by the natural visual perception mechanism of the living ...image classification [5] [6], video ... See full document
6
Understanding Convolutional Neural Networks for Text Classification
... Accompanying their rising popularity, CNNs have seen multiple advances in interpretability when used for computer vision tasks (Zeiler and Fergus, 2014). These techniques unfortunately do not trivially apply to ... See full document
10
Unified Framework For Deep Learning Based Text Classification
... artificial neural networks, which are inspired by biological brain model made of ...more multiple hidden layers before the output is performed through output ...are convolutional neural ... See full document
5
Hierarchical Classification with Convolutional Neural Networks for Biomedical Literature
... hierarchical classification has two ...obtain robust parameter estimates, Xue [1] proposed a deep classification approach to categorize Web documents which contains two stages: search stage and ... See full document
9
Extraction of Fingerprint Pore with the use of Convolutional Neural Networks
... eminence fingerprint scanning, solitary from the Level 3 landscapes of impressions, consume effectively used in spontaneous fingerprint appreciation ...spontaneous fingerprint recognition systems, ... See full document
5
Brain Tumor Classification Using Convolutional Neural Networks
... of neural network. The neural network is mainly used for vector quantization, approximation, data clustering, pattern matching, optimization functions and classification ...The neural network ... See full document
5
An Automated System for Identification of Skeletal Maturity using Convolutional Neural Networks Based Mechanism
... we use Faster R-CNN algorithm [20], an object detection ...we use has 5 shareable ...each convolutional layer. The next three 3X3 convolutional layers with 384, 384 and 256 respectively were ... See full document
7
Deep machine learning provides state of the art performance in image based plant phenotyping
... the classification, but also localization of plant root and shoot features, significantly im- proving upon the state of the ...fully convolutional networks, performing segmentation directly, rather ... See full document
10
YNUWB at SemEval 2019 Task 6: K max pooling CNN with average meta embedding for identifying offensive language
... We use two different pre-training vector model- s (fastText and Glove) to obtain a more accurate meta-embedding with a simple averaging tech- nique (Coates and Bollegala, ... See full document
5
Combining Recurrent and Convolutional Neural Networks for Relation Classification
... we use L2 regularization with a weight of 0.0001. For CNN training, we use mini batches of 25 training examples while we perform stochastic gradient descent for the ... See full document
6
Rationale Augmented Convolutional Neural Networks for Text Classification
... manual classification is a natural interaction for annotators, and requires little additional effort (Settles, 2011; McDonnell et ...new classification systems, it is natu- ral to acquire supervision at ... See full document
10
The Application of Neural Network in Multiple Object Tracking
... of neural networks in MOT, such as feature extraction, model formulation of both appearance and ...in neural networks has shown competitive superiority and drawn wide attention from ...of ... See full document
7
Exploring the Effectiveness of Privacy Preserving Classification in Convolutional Neural Networks
... The focus of this study is only on encrypted classification, therefore the layers were only created with the feed-forward phase in mind. Backpropagation was not included. HElib only supports additions and ... See full document
101
Impact of Earnings per Share on Market Price of Share with Special Reference to Selected Companies Listed on NSE
... Thermal imaging has evolved into one of the most valuable diagnostic tools for industrial applications. By detecting anomalies often invisible to the naked eye, thermography allows corrective action to be taken before ... See full document
5
A Novel Method for Remotely Sensed Hyperspectral Image Classification Based on Convolutional Neural Network
... HSI classification a challenging ...image classification may include determination of a suitable classification system, selection of training samples, image pre-processing, feature extraction, ... See full document
10
Related subjects