Search Results - "Pan, W. David"
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A Survey on Compression Domain Image and Video Data Processing and Analysis Techniques
Published in Information (Basel) (01-03-2023)“…A tremendous amount of image and video data are being generated and shared in our daily lives. Image and video data are typically stored and transmitted in…”
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Quantum Image Compression: Fundamentals, Algorithms, and Advances
Published in Computers (Basel) (01-08-2024)“…Quantum computing has emerged as a transformative paradigm, with revolutionary potential in numerous fields, including quantum image processing and…”
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Universal Golomb-Rice Coding Parameter Estimation Using Deep Belief Networks for Hyperspectral Image Compression
Published in IEEE journal of selected topics in applied earth observations and remote sensing (01-10-2018)“…For efficient compression of hyperspectral images, we propose a universal Golomb-Rice coding parameter estimation method using deep belief network, which does…”
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Microbiome characterization by high-throughput transfer RNA sequencing and modification analysis
Published in Nature communications (17-12-2018)“…Advances in high-throughput sequencing have facilitated remarkable insights into the diversity and functioning of naturally occurring microbes; however,…”
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Spatially and Spectrally Concatenated Neural Networks for Efficient Lossless Compression of Hyperspectral Imagery
Published in Journal of imaging (28-05-2020)“…To achieve efficient lossless compression of hyperspectral images, we design a concatenated neural network, which is capable of extracting both spatial and…”
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Impact of Misclassification Rates on Compression Efficiency of Red Blood Cell Images of Malaria Infection Using Deep Learning
Published in Entropy (Basel, Switzerland) (30-10-2019)“…Malaria is a severe public health problem worldwide, with some developing countries being most affected. Reliable remote diagnosis of malaria infection will…”
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Image Classification in JPEG Compression Domain for Malaria Infection Detection
Published in Journal of imaging (03-05-2022)“…Digital images are usually stored in compressed format. However, image classification typically takes decompressed images as inputs rather than compressed…”
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Efficient Lossless Compression of Multitemporal Hyperspectral Image Data
Published in Journal of imaging (01-12-2018)“…Hyperspectral imaging (HSI) technology has been used for various remote sensing applications due to its excellent capability of monitoring regions-of-interest…”
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Biased Run-Length Coding of Bilevel Classification Label Maps of Hyperspectral Images
Published in IEEE journal of selected topics in applied earth observations and remote sensing (01-10-2017)“…For efficient coding of bilevel sources with some dominant symbols often found in classification label maps of hyperspectral images, we proposed a novel biased…”
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Preventing brand name blunders in doing business across cultures: Theory and research
Published in Journal of global scholars of marketing science (02-04-2020)“…This paper contributes to international business literature by integrating firms' product competition, consumers' brand congruence, and contextual…”
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Early Termination of Dyadic Region-Adaptive Hierarchical Transform for Efficient Attribute Compression of 3D Point Clouds
Published in IEEE signal processing letters (2022)“…Thelow-complexity RAHT (Region-Adaptive Hierarchical Transform) and its corresponding Dyadic decomposition have been incorporated in the MPEG (Moving Picture…”
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Lossless Compression of Bilevel ROI Maps of Hyperspectral Images Using Optimization Algorithms
Published in IEEE geoscience and remote sensing letters (2022)“…In this letter, we propose a novel scheme for the compression of the bilevel region of interest (ROI) maps of hyperspectral images. The scheme can achieve high…”
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An efficient method for lossless compression of bi-level ROI maps of hyperspectral images
Published in 2016 IEEE Aerospace Conference (01-03-2016)“…While one can achieve very large size reduction on a hyperspectral image dataset by preserving only some regions-of-interest (ROI's), the bi-level map that…”
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Conference Proceeding -
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Predictive Lossless Compression of Regions of Interest in Hyperspectral Images With No-Data Regions
Published in IEEE transactions on geoscience and remote sensing (01-01-2017)“…This paper addresses the problem of efficient predictive lossless compression on the regions of interest (ROIs) in the hyperspectral images with no-data…”
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On fast and accurate block-based motion estimation algorithms using particle swarm optimization
Published in Information sciences (15-08-2012)“…Both fast and accurate block-matching algorithms are critical to efficient compression of video frames using motion estimation and compensation. While the…”
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Evaluations of deep convolutional neural networks for automatic identification of malaria infected cells
Published in 2017 IEEE EMBS International Conference on Biomedical & Health Informatics (BHI) (01-01-2017)“…This paper studied automatic identification of malaria infected cells using deep learning methods. We used whole slide images of thin blood stains to compile…”
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Conference Proceeding -
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Evolutionary Gain of Alanine Mischarging to Noncognate tRNAs with a G4:U69 Base Pair
Published in Journal of the American Chemical Society (05-10-2016)“…Fidelity of translation, which is predominately dictated by the accuracy of aminoacyl-tRNA synthetases in pairing amino acids with correct tRNAs, is of central…”
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Detecting moonquakes using convolutional neural networks, a non-local training set, and transfer learning
Published in Geophysical journal international (01-06-2021)“…SUMMARY The costly power requirements of delivering seismic data back to Earth from planetary missions requires the development of algorithms for lander-side…”
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A deep learning-assisted mathematical model for decongestion time prediction at railroad grade crossings
Published in Neural computing & applications (01-03-2022)“…This paper presents a deep learning-assisted framework to estimate the decongestion time at the grade crossing, and its key novelty lies in a differential…”
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Correction to: A deep learning-assisted mathematical model for decongestion time prediction at railroad grade crossings
Published in Neural computing & applications (01-04-2022)Get full text
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