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In the last decade, a good number of supervised learning algorithms have been introduced by the intelligent computational researchers in machine learning and data mining. Recently research in classification problems to reduce misclassification rate focuses on aggregation methods like Boosting, which combines many classifiers to generate a single strong classifier. Boosting is also known as AdaBoost...
Continuing development in surgical techniques has elevated the level of sophistication in surgery. In order to reduce trauma to healthy tissue of the patient body, scientists are continuously trying different technologies in surgery. Minimally Invasive Surgery is one of this new practices adopted by the surgeons, which allows doctors to operate on patient with minimal damage and this reduces the post-operative...
Neural networks have been of interest for long, but have been hard to implement in practice, because of excessive complexity and training required. Neural networks have been proposed with hardware, such as with FPGAs and VLSI. This paper proposes implementing neurons and neural networks with MOS Flash memory technology. The floating gate of the flash memory can store a charge for years, influencing...
This paper deals with the problem of temporal segmentation present in practical applications of action and gesture recognition. In order to separate different gestures from gesture sequences a novel method utilizing depth information, oriented gradients and supervised learning techniques is proposed in this paper. The temporal segmentation task is modeled as a two-class problem and histogram oriented...
In this paper, a novel feature extraction algorithm for power quality (PQ) disturbance signal classification is proposed based on extracting spectral features from Discrete Cosine Transform (DCT) domain. The spectral domain feature extraction offers the ability to detect and localize transient events and thereby classify different power quality disturbance signals or events. For optimal feature set...
Essays are the most useful tool to assess learning outcomes. However, teachers have not enough time to evaluate a student's writing properly because of their other assigned responsibilities. Several Automated Essay Grading (AEG) systems have been developed to evaluate the human written (not hand written) essays easily. But, most of the AEG systems are used for grading English language or essays written...
In human brain the neurons are excited in a dynamic way. The response of different neurons varies widely because of the variation of electrical signal in every neuron. Backpropagation(BP) is a training algorithm where the learning of the Neural Network (NN) is done by a constant learning rate (LR). But to replicate the human brain function, the learning rate should be changed as the excitation of...
This paper presents multiclass object classification and recognition using smartphone and cloud computing (client server) technology. Smart phone camera is used as image acquisition device. Smartphone is working as a client and high speed computer act as a server. Our system is a feature based novel approach that requires huge computing power and stand-alone smart phone is not capable for performing...
It is well-known that an artificial agent exhibits deterministic dynamics when it moves in a closed real world environment. It is interesting to determine this dynamics when a real biological being such as fish is kept in a real closed environment and free to move in it. This paper determines some deterministic dynamics of fish motion freely moving in a closed environment. The task is divided into...
Handwritten character recognition is considered to be one of the most fascinating and interesting field of research in image processing and pattern recognition. Due to the various challenges associated with it, intensive research works are currently in progress for constructing algorithms that produce better recognition accuracy. This paper proposes an algorithm that recognizes offline isolated Bangla...
In computer vision, semantically accurate segmentation of an object is considered to be a critical problem. The different looking fragments of the same object impose the main challenge of producing a good segmentation. This leads to consider the high-level semantics of an image as well as the low-level visual features which require computationally intensive operations. This demands to optimize the...
This paper presents a brain-computer interface (BCI) that can help users to input phone numbers or select any command in the graphical user interface. The system is based on the steady-state visual evoked potential (SSVEP). To ensure universal applicability, a system with three fixed positioned electrodes for reducing user variation on system performance has been proposed. Sixteen buttons illuminated...
This paper presents a study on improving generalization ability of neural networks (NNs) by using ensemble approach. In already existing literature, both theoretical and experimental studies have revealed that the performance, i.e., generalization ability of NN ensemble is greatly dependent on both accuracy and diversity among individual NNs in the ensemble. In this study and implementation of NN...
In this study, support vector regression (SVR) analysis is used as a machine learning technique in order to predict the stock market price as well as to predict stock market trend. Moreover, different types of windowing operators are used as data preprocess or input selection technique for SVR models. This is a new approach which uses different types of windowing functions as data preprocess for predicting...
Miniature transformer is one of the most important components of electronic devices. A serious failure of such kind of transformer may cause loss of time and money. This paper presents a learning system to recognize internal fault of such kind of transformer. The different kinds of faults are made to occur intentionally and data are collected at various conditions. The faults include turn to turn,...
Load forecasting is becoming an important issue day by day for economic generation of power, economic allocation between plants, maintenance scheduling and for system security which involves peak load shaving by power inter change with interconnecting utilities. In this paper, sensitivity learning oriented multi reservoir Echo State Network (ESN) using non monotonic transfer function with optimized...
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