neural network-based classifiers
Lower bounds on the robustness to adversarial perturbations
... Contractive Network, which includes a smoothness penalty in the training procedure inspired by the Contractive ...the network to have small components, thus making the network robust to small changes ...
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A Comparative Evaluation Study of Automated Gait Recognition based on Spatiotemporal Feature and Different Neural Network Classifiers
... Based on the above discussion, this paper proposing a new gait recognition technique based on cascaded spatial and transform-based feature extraction; to extract spatiotemporal gait ...supervised ...
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Influence of Acoustic Feedback on the Learning Strategies of Neural Network-Based Sound Classifiers in Digital Hearing Aids
... Sound classifiers embedded in digital hearing aids are usually designed by using sound databases that do not include the distortions associated to the feedback that often occurs when these devices have to work at ...
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Neural Network For Face Recognition Using Different Classifiers
... On the other hand, while PCA-based and LDA-based approaches depend only on second-order statistical structure between pixels in the face image, ICA method has been used to find statistically independent ...
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Context-aware convolutional neural network for grading of colorectal cancer histology images
... of standard patch classifiers. The input image is then divided into small patches (224 × 224) in sliding window fashion with no-overlap. The LR-CNN takes the patches as input and converts them into ...
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WAVELET ANALYSIS AND NEURAL NETWORK CLASSIFIERS TO DETECT MID-SAGITTAL SECTIONS FOR NUCHAL TRANSLUCENCY MEASUREMENT
... is based on the meaning of echogenicity of each pixel or set of pixels of the ...approach based on the identification of three classes (anechogenic, echogenic and uncertainty) via probability distribution ...
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Analysis of the Effects of Finite Precision in Neural Network-Based Sound Classifiers for Digital Hearing Aids
... 2.1. Feature Extraction. There is a number of interesting features that could potentially exhibit different behavior for speech, music, and noise and thus may help the system classify the sound signal. In order to carry ...
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Classification of Brain Tumor Grades using Neural Network
... the neural network and support vector machine classifiers for the classification of brain ...the neural network ...classes. Neural network is the non-linear computational ...
5
Text Dependent Speaker Recognition using MFCC features and BPANN
... the network is of size 200 × 65 for a cluster size of ...classifier based direct method. The comparison of neural network based and minimum distance based classifiers are ...
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Ensemble Neural Network and K-NN Classifiers for Intrusion Detection
... is based on the principle that the characteristics of intrusion are different from normal behavior In general, IDS can be divided into two categories:anomaly detection and misuse(signature) ...
5
Consistent performance measurement of a system to detect masses in mammograms based on blind feature extraction
... tissue) based on feature extraction and classification of regions of interest (previously extracted from the DDSM database, in our ...is based in blind feature extraction using independent component ...
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Robust Neural Network Classifier
... classes. Neural Networks (NN) are an effective tool in the field of pattern ...training neural networks. However (MSE) based learning algorithm is not robust in presence of outliers that may pollute ...
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Pulsar selection using fuzzy knn classifier
... Recently, neural network techniques are proposed to solve the ...is based on the fuzzy knn ...other classifiers, including neural network classifiers, using three ...
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FUZZY LOGIC BASED VOLTAGE AND FREQUENCY OF A SELF EXCITED INDUCTION GENERATOR FOR MICRO HYDRO TURBINES FOR RURAL APPLICATIONS
... structure based on external or internal information that flows through the network during the learning phase ...optimize neural networks for ...with neural networks to investigate the tradeoff ...
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Leaf Recognition based on Neural Network Feed- Forward and Support Vector Machine Classifiers
... Leaf recognition is very important in plant classification and its key subject to distinguish different kinds of leaves. Comparing with other methods, such as cell and molecule biology methods, classification ...
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Comparing Naive Bayes Method And Artificial Neural Network For Semen Quality Categorization
... We have experimented with two popular machine learning techniques to classify the quality of human semen, in order to assess the male fertility potential. Our dataset is highly imbalanced and biased towards the ...
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MELANOMA SKIN CANCER DETECTION USING IMAGE PROCESSING
... learning based classifiers as Neural Network, Support Vector Machine and unsupervised learning based classification as K-means clustering ...of Neural Network and Support ...
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LTL UDE at SemEval 2019 Task 6: BERT and Two Vote Classification for Categorizing Offensiveness
... list- based classification, using classifiers such as SVM or logistic regression based on sentence embed- dings, and neural network-based models such as a Multi-layer Perceptron ...
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A Comparison of Neural Classifiers for Graffiti Recognition
... of neural networks is well known in solving complex problems through many decision-making techni- ...three neural based ...proposed classifiers use multilayer feed-forward neural ...
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GLOBAL JOURNAL OF ADVANCED ENGINEERING TECHNOLOGIES AND SCIENCES RECOGNITION OF PERSIAN HANDWRITTEN NUMBERS BASED ON ASSEMBLY OF REINFORCED CLASSIFIERS Hamid Parvin*, Seyed Ahad Zolfagharifar, Faramarz Karamizadeh
... a neural network is used as the primary ...matrix, neural network with two layers has been ...in neural networks, in first layer linear and in second layer has been tangent ...
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