Expression classification results using grayscale points
An automated technique for carotid far wall classification using grayscale features and wall thickness variability
... high classification accuracy using a small feature set extracted from automatically segmented ...by using the IMT and IMTV poly features of the distal wall instead of the plaque regions and obtained ...
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Facial Expression Classification Using EEG and Gyroscope Signals
... scalp. Using the already present EEG device to classify facial expressions allows for a new hybrid brain-computer interface (BCI) system without introducing new hardware such as separate electromyography (EMG) ...
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Algorithms for the resizing of binary and grayscale images using a logical transform
... images using a logical ...paper, results in the desired scaling of the ...edge classification result in two additional variations, improving this initial ...to grayscale data as well, making ...
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Classification of Multi-Media Content (Video s on YouTube) Using Tags and Focal Points
... in high-level human interpretations of audiovisual media.” [2] The Problem with Multi-Media Content Unlike text data, Multi-Media Content (MMC) is way too much rich and expressive; however this poses a fundamental ...
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Gene Selection for Tumor Classification Using Microarray Gene Expression Data
... This paper also describes results concerning the robustness and generalization capabilities of kernel methods in classifying. We use traditional support vector machines (SVM), biased support vector machine (BSVM) ...
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Microarray Gene Expression Data Classification using a Hybrid Algorithm: MRMRAGA
... the classification model therefore, it is necessary to reduce feature in order to get good performance using feature selection ...the classification by classification or regression model ...
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Emotion Recognition from Facial Expression Based on Fiducial Points Detection and using Neural Network
... facial expression recognition are generally: face detection, feature extraction, and facial expression ...facial expression movement must be found and used for ...detected points to measure ...
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Feature Selection Technique Based on Neuro Classification using Gene Expression Data
... gene expression data to get better classification ...experimental results are revealed with its efficiency and then Neuro-fuzzy technique is also related to wrapper ...
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Complexity Reduced Tumor Classification System using Microarray Gene Expression Dataset
... The classification of cancer based on gene expression data is the advancements in DNA Microarray technology and genome ...purposes using such micro-array gene expression dataset and also the ...
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Tumor Classification by Partial Least Squares using Microarray Gene Expression Data
... the classification of tumors based on microarray gene expression ...gene expression space followed by logistic classification or ...these results hold under re-randomization ...
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Gene Expression-Based Glioma Classification Using Hierarchical Bayesian Vector Machines
... the classification of Glioma cancer is extremely difficult, we observe that most of the standard methods like neural network and random forest do equally poorly in ...better results than all the previous ...
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Semi-supervised Classification of Breast Cancer Expression Profiles Using Neural Networks
... Training Using Back-propagation Back-propagation is the adaptation of weights and biases of the network to make its set of actual outputs better fit a set of desired outputs for a given set of ...important ...
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A Comparative Analysis of Classification of Micro Array Gene Expression Data Using PCA
... She is currently pursuing Ph.D. degree, working closely with Prof. G.M.Kadhar Nawaz. She worked at Lecturer and Senior Lecturer in the Sona College Of Technology from 2000 to 2008. She served in the TULEC Computer ...
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A File Fragment Classification Method Based on Grayscale Image
... best classification algorithm that fits for file fragment ...ble classification algorithm, the effect of grayscale image width on classification accuracy is ...dimensions using PCA ...
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Grayscale Chessboard
... n chess, opponents attempt to whittle down each other’s pieces until they can achieve victory. Yet neither side is evil, they are merely two powers using all means and moves necessary to win. They are playing this ...
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Results on common fixed points
... In this note, we prove common fixed point theorems for Cf ∩ Cg and Cgf in bounded complete metric spaces and compact metric spaces.. Common fixed point theorems.[r] ...
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Wirelessly Transmitting a Grayscale Image using Visible Light
... regular grayscale image can be transmitted with this method and faithful reproduction is achieved at the ...rate, using OFDM modulation in accordance to the image data, such that the intensity appears ...
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Grayscale Image Compression using Discrete Cosine Transform
... Fig. 2 is for block diagram for Image Reconstruction it consists of DCT and IDCT in MATLAB approach. For image compression any image format here we can use i.e. JPEG, PNG, TIF image format. For image compression the ...
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Grayscale Image Colorization using Seeded Cellular Automaton
... a grayscale image in order to convert monochromatic images into visually plausible colored ...a grayscale image is a very important technique to improve its visual ...Experiment results revealed that ...
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Enhancement of digital grayscale image watermarking using sparse matrix
... Sumathi, 2013). These properties are often conflicting, which needs to accept some trade-offs between them. Additionally, security is a significant factor for high quality watermarking. Based on that, the following ...
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