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Full-Text Articles in Computer Engineering
Design Development And Performance Analysis Of Distributed Least Square Twinsupport Vector Machine For Binary Classification, Bakshi Rohit Prasad, Sonali Agarwal
Design Development And Performance Analysis Of Distributed Least Square Twinsupport Vector Machine For Binary Classification, Bakshi Rohit Prasad, Sonali Agarwal
Turkish Journal of Electrical Engineering and Computer Sciences
Machine learning (ML) on Big Data has gone beyond the capacity of traditional machines and technologies. ML for large scale datasets is the current focus of researchers. Most of the ML algorithms primarily suffer from memory constraints, complex computation, and scalability issues.The least square twin support vector machine (LSTSVM) technique is an extended version of support vector machine (SVM). It is much faster as compared to SVM and is widely used for classification tasks. However, when applied to large scale datasets having millions or billions of samples and/or large number of classes, it causes computational and storage bottlenecks. This paper …
Scale-Invariant Histogram Of Oriented Gradients: Novel Approach For Pedestriandetection In Multiresolution Image Dataset, Sweta Panigrahi, Surya Narayana Raju Undi
Scale-Invariant Histogram Of Oriented Gradients: Novel Approach For Pedestriandetection In Multiresolution Image Dataset, Sweta Panigrahi, Surya Narayana Raju Undi
Turkish Journal of Electrical Engineering and Computer Sciences
This paper proposes a scale-invariant histogram of oriented gradients (SI-HOG) for pedestrian detection. Most of the algorithms for pedestrian detection use the HOG as the basic feature and combine other features with the HOG to form the feature set, which is usually applied with a support vector machine (SVM). Hence, the HOG feature is the most efficient and fundamental feature for pedestrian detection. However, the HOG feature produces feature vectors of different lengths for different image resolutions; thus, the feature vectors are incomparable for the SVM. The proposed method forms a scale-space pyramid wherein the histogram bin is calculated. Thus, …
A Counter Based Approach For Reducer Placement With Augmented Hadoop Rackawareness, Mir Wajahat Hussain, K Hemant Reddy, Diptendu Sinha Roy
A Counter Based Approach For Reducer Placement With Augmented Hadoop Rackawareness, Mir Wajahat Hussain, K Hemant Reddy, Diptendu Sinha Roy
Turkish Journal of Electrical Engineering and Computer Sciences
As the data-driven paradigm for intelligent systems design is gaining prominence, performance requirements have become very stringent, leading to numerous fine-tuned versions of Hadoop and its MapReduce programming model. However, very few researchers have investigated the effect of intelligent reducer placement on Hadoop's performance. This paper delves into this much ignored reducer placement phase for improving Hadoop's performance and proposes to spawn reduce phase of Hadoop tasks in an asynchronous fashion across nodes in a Hadoop cluster. The main contributions of this paper are: (i) to track when map phase of tasks are completed, (ii) to count the number of …