This paper presents our research on Indonesian question answering system for solving arithmetic word problems using pattern matching approach on intelligent humanoid robot. The objective of this paper is to elaborate ...
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In the literature of face recognition many methods have been proposed which extract local texture features for robust pattern classification. But for final computation of the feature the information about central pixe...
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In the literature of face recognition many methods have been proposed which extract local texture features for robust pattern classification. But for final computation of the feature the information about central pixel is not taken into account. In this paper, we propose a novel method which utilizes Local Ternary pattern and Booth's Algorithm techniques to capture the local face features, which utilize central pixel for computation of the feature. Face images are spatially varied and classification works better with local descriptors, a Non-overlapping block wise processing is done on image to limit the features. The Support Vector machine (SVM) and KNN classifier with proposed similarity measure is used for face classification. Finally, ROC and CMC are plotted for analysis of the system. Experiments are conducted on ORL and faces94 datasets demonstrates that the proposed method has better classification accuracy than previously proposed methods.
We present a novel 3D face recognition approach based on geometric invariants introduced by Elad and Kimmel. The key idea of the proposed algorithm is a representation of the facial surface, invariant to isometric def...
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Classification of conservation tillage practices from hyperspectral imagery is challenging due to spectral similarity between soils and senescent crop residues. In this paper, a novel classifier using both spectral an...
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ISBN:
(纸本)9781479941575
Classification of conservation tillage practices from hyperspectral imagery is challenging due to spectral similarity between soils and senescent crop residues. In this paper, a novel classifier using both spectral and spatial information is proposed for hyperspectral image classification. Three steps are included: (1) a feature extraction method using a very simple local averaging filter to produce the joint spectral-spatial features;(2) an efficient local Fisher discriminant analysis projection for dimensionality reduction and class separability enhancement;and (3) the typical k-nearest neighbor classifier for final classification. Experimental results using real hyperspectral data demonstrate the benefits of the proposed approach, which can outperform other popular classifiers, such as support vector machine with composite kernel.
As a key technology in the field of computer vision, point cloud semantic segmentation has been widely used in intelligent life and has become a hot spot and a difficult area of research in 3D vision. Current research...
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The manufacture of a wide variety of sweets is on the rise in the entire Bengal (both Bangladesh and West Bengal). As a consequence, the sweet39;s name escapes the vast majority of individuals in our country. Comput...
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ISBN:
(纸本)9783031686160;9783031686177
The manufacture of a wide variety of sweets is on the rise in the entire Bengal (both Bangladesh and West Bengal). As a consequence, the sweet's name escapes the vast majority of individuals in our country. Computer vision advancements have made object recognition from photos easier in recent years. Using computer vision to automatically categorize sweets is still a challenge because of the similarity between various sorts and characteristics such as their placement or lighting conditions. Classifying sweets may be useful in a variety of domains, including autonomous economic robots and the creation of mobile apps for identifying certain sweets on the market. In this article, we employed deep convolutional neural network (DCCN) methods to evaluate five alternative models for sweet detection. The endemic Bengali delicacies we used to train my model included Inception-v3, ResNet-50, VGG15, AlexNet, and CNN. This model was efficient. Our dataset comprised images of confections from thirteen distinct sweet categories. Two portions of the dataset were separated: 80% for training and 20% for testing. The training dataset was enhanced and increased to make preparation simpler. Using the Inception-v3 model, we were able to attain a 100% accuracy rate with our dataset.
The proceedings contain 42 papers. The special focus in this conference is on Experimental and Efficient Algorithms. The topics include: A hybrid bin-packing heuristic to multiprocessor scheduling;efficient edge-swapp...
ISBN:
(纸本)3540220674
The proceedings contain 42 papers. The special focus in this conference is on Experimental and Efficient Algorithms. The topics include: A hybrid bin-packing heuristic to multiprocessor scheduling;efficient edge-swapping heuristics for finding minimum fundamental cycle bases;solving chance-constrained programs combining tabu search and simulation;an algorithm to identify clusters of solutions in multimodal optimisation;on an experimental algorithm for revenue management for cargo airlines;cooperation between branch and bound and evolutionary approaches to solve a bi-objective flow shop problem;simple max-cut for split-indifference graphs and graphs with few P4’s;a randomized heuristic for scene recognition by graph matching;an efficient implementation of a joint generation algorithm;lempel, even, and cederbaum planarity method;a greedy approximation algorithm for the uniform labeling problem analyzed by a primal-dual technique;distributed circle formation for anonymous oblivious robots;dynamic programming and column generation based approaches for two-dimensional guillotine cutting problems;engineering shortest path algorithms;how to tell a good neighborhood from a bad one;implementing approximation algorithms for the single-source unsplittable flow problem;fingered multidimensional search trees;faster deterministic and randomized algorithms on the homogeneous set sandwich problem;efficient implementation of the BSP/CGM parallel vertex cover FPT algorithm and combining speed-up techniques for shortest-path computations.
To guarantee high-quality and trustworthy data, we first highlight the need of preprocessing. The dataset is prepared for analysis by using standard methods such as data cleansing, normalization, and feature engineeri...
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In the realm of AI-enabled Wireless Sensor Networks (WSNs) and Internet of Things (IoT) integration, efficient resource allocation is paramount for enhancing energy efficiency and optimizing data utilization. The dyna...
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In this paper an artificial immune system approach is used to model an agent that plays the Iterated Prisoner’s Dilemma. The learning process during the game is accomplished in two phases: recognition of the opponent...
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