Bi-orthogonal wavelets for compression, denoising and stereo matching of satellite images by Ji, Yanwen

“…In image compression, wavelet transform is first performed on the image, adaptive differential pulse code modulation (ADPCM) and vector quantization (VQ) are used to encode the coarse frequency components and detail frequency components, respectively. …”
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Real-time human detection for surveillance applications by Hoe, Qi Xiang

“…The use of Histogram of Oriented Gradient (HOG) is implemented in the detection of human figure in an image where vectors will be obtained from each pixel in the image through the computation of horizontal and vertical components; these vectors will be used to form a histogram for each image. …”
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Modeling renography data and formulating indices for quantitative means in differentiating kidney obstruction by Suriyanto

“…Lastly, using support vector machine (SVM) classifier as a quantitative means for differentiating kidney obstructions was proposed based on the simulation results of the samples that had been compared with clinical interpretation of renograms by a certified nuclear medicine doctor.…”
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Video processing of ophthalmic image sequences by Ambarish, Sridhar Prakash

“…One measure of evaluation, proposed by this project is to segment the surgery video into parts based on the different procedures, thereby measuring the time and hence efficiency of the surgeon for the particular tasks. A Support Vector Machine (SVM) was trained based on the SIFT features of images from a given video using the Bag of Visual Words (BoVW) approach. …”
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Effect of contextual information in human action recognition in videos by Koh, Hong Wei

“…The first phase of the project is to extract features from the videos using log covariance matrix with Support Vector Machine (SVM) and Extreme Learning Machine (ELM) as the classifiers to discriminate the actions. …”
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Machine learning algorithm for electroencephalography (EEG) based brain signal analysis by Teo, Jeffrey Eng Hock

“…The 3 classifiers being evaluated are Linear Discriminant Analysis (LDA), Linear Support Vector Machine (SVM) and k-Nearest Neighbour (KNN). …”
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Efficient HIK SVM learning for image classification by Wu, Jianxin

“…Histogram intersection kernel (HIK) and support vector machine (SVM) classifiers are shown to be very effective in dealing with histograms. …”
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Focusing of linearly polarized Lorentz–Gauss beam with one optical vortex by Rui, Fu, Zhang, Dawei, Ting, Mei, Gao, Xiumin, Zhuang, Songlin

“…Focusing properties of linearly polarized Lorentz–Gauss beam with one on-axis optical vortex was investigated by vector diffraction theory. Results show that the focal pattern can be altered considerably by charge number of the optical vortex and the beam parameters. …”
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Generalized RBF feature maps for efficient detection by Vempati, S, Vedaldi, A, Zisserman, A, Jawahar, CV

“…Furthermore, we investigate a learning method using l1 regularization to encourage sparsity in the final vector representation, and thus reduce its dimension. …”

Efficient additive kernels via explicit feature maps by Vedaldi, A, Zisserman, A

“…Large scale nonlinear support vector machines (SVMs) can be approximated by linear ones using a suitable feature map. …”

Discovering objects and their location in images by Sivic, J, Russell, BC, Efros, AA, Zisserman, A, Freeman, WT

“…The model is applied to images by using a visual analogue of a word, formed by vector quantizing SIFT-like region descriptors. The topic discovery approach successfully translates to the visual domain: for a small set of objects, we show that both the object categories and their approximate spatial layout are found without supervision. …”

Efficient visual search of videos cast as text retrieval by Sivic, J, Zisserman, A

“…This requires a visual analogy of a word which is provided here by vector quantizing the region descriptors. The final ranking also depends on the spatial layout of the regions. …”

Predictive modeling of gold prices: integrating technical indicators for enhanced accuracy by Husiani, Noor Aida, Gan, Yee Jing, Ghazali, Rozaida, Mohmad Hassim, Yana Maswin, Yap, Jie Shen, Joseph, Jerome Subash

“…For this, three (3) machine learning (ML) models - Decision Tree Regressor (DTR), Support Vector Regression (SVR), and Random Forest (RF); must be carefully chosen, and model parameters must be adjusted so that predicted values roughly match actual results. …”
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Optimized GPU algorithms for sparse data problems by Pham, Nguyen Quang Anh

“…The algorithm reduces I/O for vector accesses by 37% on average, and improves performance up to 35% compared to the previously fastest GPU SpMV algorithm. …”
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Machine Learning Method for Forecasting Weather Needed For Crop Water Demand Estimations in Low-Resource Settings Using A Case Study in Morocco by Sheline, Carolyn, Winter, Amos

“…The focus of this work is on the accuracy with which Moroccan weather can be predicted with a vector autoregression (VAR) model compared to using typical meteorological year (TMY) weather, and how this accuracy changes as the number of weather parameters is reduced.…”
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Contracting differential equations in weighted Banach spaces by Srinivasan, Anand, Slotine, Jean-Jacques

“…Geodesic contraction in vector-valued differential equations is readily verified by linearized operators which are uniformly negative-definite in the Riemannian metric. …”
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Analyticity and the Unruh effect: a study of local modular flow by Sorce, Jonathan

“…Finally, I discuss a few settings in which converse results can be shown — i.e., settings in which a state can be constructed whose modular flow reproduces a given vector field.…”
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Portfolio Optimization Using a Hybrid Machine Learning Stock Selection Model by Masuda, Joshua S.

“…In this paper, seven machine learning techniques are used for stock price prediction: Linear Regression, Support Vector Machine, Random Forest, Recurrent Neural Network, Long Short-Term Memory, Bidirectional Long Short-Term Memory, and LightGBM. …”
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Real-time chiral dynamics at finite temperature from quantum simulation by Ikeda, Kazuki, Kang, Zhong-Bo, Kharzeev, Dmitri E., Qian, Wenyang, Zhao, Fanyi

“…By introducing a chiral chemical potential μ5 through a quench process, we drive the system out of equilibrium and analyze the induced vector currents and their evolution over time. The Hamiltonian is modified to include the time-dependent chiral chemical potential, thus allowing the investigation of the CME within a quantum computing framework. …”
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Dengue : challenges for policy makers and vaccine developers by Wilder-Smith, Annelies, Macary, Paul

“…Dengue vaccine introduction will not be the only strategy to combat dengue, but needs to be “packaged” with novel vector control approaches, with community-based interventions to reduce the number of breeding sites, and reducing the case fatality rate by improving case management.…”
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