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Data handling challenges for remote sensing systems

Data handling challenges for remote sensing systems

引用

IEEE conference on Aerospace

作者： J.M. Coupe Communications Division ITT Industries Aerospace Fort Wayne IN USA

Multi-spectral imaging systems in remote sensing satellites generate large volumes of image data. Information content increases as instruments use wider swaths, more spectral bands, finer resolution and larger bit depths. As an example, the next generation Landsat system is expected to have an instrument data rate of several gigabits per second. Solid state recorders appear to be the best storage technology for most remote sensing missions, but cost and size become prohibitive for multi-terabyte systems. With downlink bandwidth representing a bottleneck in the system, real-time on-board processing, particularly image compression, is a key to using on-board storage efficiently and reducing downlink data volume. However, the inherent constraints of space applications - size, weight, and power-generally preclude the use of software-only solutions. Reconfigurable computing should be considered for its potential to enhance system flexibility and performance by allowing the data handling subsystem to be reprogrammed from the ground to incorporate mission changes and/or improved algorithms.

关键词： Data handling Remote sensing Satellites Instruments Space technology Downlink image storage Multispectral imaging Solid state circuits Costs

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A Method Using Texture and Color Feature for Content-Based image Retrieval

A Method Using Texture and Color Feature for Content-Based I...

引用

2015 IEEE International conference on Computer and communications(ICCC 2015)

作者： He Zhang Xiuhua Jiang Information Engineering School Communication University of China

With the rapid growth of image database, contentbased image retrieval(CBIR) technology with its high value in theory and application has become a hot topic in the field of image processing. A retrieval method which combines color and texture feature is proposed in this paper. According to the characteristic of the image texture, we can represent the information of texture by fusion algorithm combines Gabor transform and edge histogram. The color histogram in HSV color space is chosen as the color feature, and the blocking and fuzzy color histogram is proposed in this paper. The experiment results show that this method is more efficient than the traditional CBIR method based on the single visual feature and method combining color and texture like CEDD.

关键词： image retrieval Texture feature Color feature Fusion

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Building an adaptive spoken language interface for perceptually grounded human-robot interaction

Building an adaptive spoken language interface for perceptua...

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IEEE-RAS International conference on Humanoid Robots

作者： P.F. Dominey J.-D. Boucher T. Inui CNRS Institut des Sciences Cognitives Bron France Graduate School of Informatics Kyoto University Sakyo Kyoto Japan

In previous research, we developed an integrated platform that combined visual scene interpretation with speech processing to provide input to a language-learning model. The system was demonstrated to learn a rich set of sentence-meaning mappings that could allow it to construct the appropriate meanings for new sentences in a generalization task. While this demonstrated potential promise, it fell short in several aspects of providing a useful human-robot interaction system. The current research addresses three of these shortcomings, demonstrating the natural extensibility of the platform architecture. First, the system must be able not only to understand what it hears, but also to describe what it sees and to interact with the human user. This is a natural extension of the knowledge of sentence-to-meaning mappings that is now applied in the inverse scene-to-sentence sense. Secondly, we extend the system's ontology from physical events to include spatial relations. We show that spatial relations are naturally accommodated in the predicate argument representations for events. Finally, because the robot community is international the robot should be able to speak multiple languages, we thus demonstrate that the language model extends naturally to include both English and Japanese. Concrete results from a working interactive system are presented and future directions for adaptive human-robot interaction systems are outlined.

关键词： Natural languages Humans Layout Robot sensing systems Humanoid robots Charge coupled devices Charge-coupled image sensors image processing Informatics Speech processing

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Cheque Information processing and Validation using Deep Learning

Cheque Information Processing and Validation using Deep Lear...

引用

communications and Information Technologies (GCCIT), Global conference on

作者： Suganthi K Darshan N Shenoy School of Electronics Engineering Vellore Institute of Technology Chennai

ISBN: (数字)9798350388916

ISBN: (纸本)9798350388923

Understanding document images, such as invoices, is a difficult task. It necessitates reading the text as well as comprehending the document’s general structure. Conventional techniques first extract text using Optical Character Recognition (OCR), yet this method has drawbacks. In addition to being computationally costly, OCR can have trouble converting between various languages and document formats and introduce errors that can compound throughout the analysis *** is an OCR-free VDU (visual Document Understanding) model that challenges this paradigm. It does not even bother with the text extraction stage; it analyzes the document image straight. This creative strategy produces notable advancements. Donut performs at the cutting edge, which means it is quick and precise. This is a significant development in the realm of visual document understanding since it enables Donut to handle a greater variety of languages and document types. The model has been tested using BLEU scores and ROUGE scores over 3 parameters namely – payee name, amount in words and amount in figure. The model has also been tested over variety of sample sizes ranging from 50 to 1000.

关键词： Training Productivity visualization Target recognition Optical character recognition Transforms Streaming media Multilingual Data mining Testing

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Explicit-NeRF-QA: A Quality Assessment Database for Explicit NeRF Model Compression

Explicit-NeRF-QA: A Quality Assessment Database for Explicit...

引用

IEEE visual communications and image processing (VCIP)

作者： Yuke Xing Qi Yang Kaifa Yang Yiling Xu Zhu Li Cooperative MediaNet Innovation Center Shanghai Jiao Tong University Shanghai China Department of Computer Science and Electrical Engineering University of Missouri-Kansas City USA

ISBN: (数字)9798331529543

ISBN: (纸本)9798331529550

In recent years, Neural Radiance Fields (NeRF) have demonstrated significant advantages in representing and synthesizing 3D scenes. Explicit NeRF models facilitate the practical NeRF applications with faster rendering speed, and also attract considerable attention in NeRF compression due to its huge storage cost. To address the challenge of the NeRF compression study, in this paper, we construct a new dataset, called Explicit-NeRF-QA. We use 22 3D objects with diverse geometries, textures, and material complexities to train four typical explicit NeRF models across five parameter levels. Lossy compression is introduced during the model generation, pivoting the selection of key parameters such as hash table size for InstantNGP and voxel grid resolution for Plenoxels. By rendering NeRF samples to processed video sequences (PVS), a large scale subjective experiment with lab environment is conducted to collect subjective scores from 21 viewers. The diversity of content, accuracy of mean opinion scores (MOS), and characteristics of NeRF distortion are comprehensively presented, establishing the heterogeneity of the proposed dataset. The state-of-the-art objective metrics are tested in the new dataset. Best Pearson correlation, which is around 0.85, is collected from the full-reference objective metric. All tested no-reference metrics report very poor results with 0.4 to 0.6 correlations, demonstrating the need for further development of more robust no-reference metrics. The dataset, including NeRF samples, source 3D objects, multiview images for NeRF generation, PVSs, MOS, is made publicly available at the following location: https://***/YukeXing/Explicit-NeRF-QA.

关键词： Measurement Three-dimensional displays Correlation Accuracy image coding visual communication Video sequences Neural radiance field Distortion Rendering (computer graphics)

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EyeRis: visual image Recognition using Machine Learning for the visually-Impaired

EyeRis: Visual Image Recognition using Machine Learning for ...

引用

International conference on Electronics, Information and communications (ICEIC)

作者： Alliah May Eugenio Marian Jowie Patulot Lykha Jane Seguiro Angelica Nicole Tuazon Shekinah Lor Huyo-a Mideth Abisado Gabriel Avelino Sampedro Department of Computer Science Technological University of the Philippines Manila Philippines Philippine Coding Camp Research and Development Center Manila Philippines College of Computing and Information Technologies National University Manila Philippines Faculty of Information and Communication Studies University of the Philippines Open University Laguna Philippines

visually impaired people struggle daily and have difficulty recognizing and distinguishing objects around them. Thus, they mainly depend on supervision from other people to assist them. Since smartphones have become a necessity in this modern world, the researchers formulated a solution to help the visually impaired through a machine learning-based mobile application for object recognition. Nowadays, software applications can provide accurate findings in picture classification and processing processes thanks to machine learning techniques and algorithms. In this study, the researchers use a convolutional neural network (CNN)-based system on TensorFlow Lite to create a mobile version of a visual information system employing a machine learning strategy and deep learning framework. The main objectives of the smartphone application, EyeRis, is to recognize and categorize items in real-time and to separate photographs from the user-selected scenarios. Results were analyzed and contrasted based on the app’s obtained recognition accuracy data. It demonstrated the utility of CNN as a model for image recognition algorithms.

关键词： visualization image recognition Machine learning algorithms Software algorithms Neural networks Software Real-time systems

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Landmine detection in high resolution 3D GPR images

Landmine detection in high resolution 3D GPR images

引用

International conference on Microwaves, Radar and Wireless communications

作者： E.E. Ligthart A.G. Yarovoy F. Roth L.P. Ligthart International Research Centre for Telecommunications-transmission and Radar (IRCTR) Delft University of Technology CD Delft The Netherlands International Research Centre for Telecommunications-transmission and Radar (IRCTR) Delft University of Technnology Delft Netherlands Int. Res. Center for Telecommun.-transmission & radar Delft Univ. of Technol. Netherlands

This work describes a novel landmine detection and classification algorithm for high resolution 3D ground penetrating radar (GPR) images. The algorithm was tested on data measured with a video impulse radar (VIR) system developed by the International Research Centre for Telecommunications-transmission and Radar (IRCTR). The algorithm detected all landmines (including the difficult to detect M14 mines) and classified almost all specific landmines features correctly with a reasonably low false alarm rate. The feature on a small height object demonstrates an effective reduction of false alarms.

关键词： Landmine detection image resolution Ground penetrating radar Radar imaging Radar detection Object detection Radar measurements Clutter image processing Radar polarimetry

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Lightweight image Classification Algorithm Based on Dual Knowledge Distillation 23

Lightweight Image Classification Algorithm Based on Dual Kno...

引用

Proceedings of the 2023 6th International conference on Artificial Intelligence and Pattern Recognition

作者： Peng Xiao Ying Liu Yu Hao Center for Image and Information Processing School of Communications and Information Engineering Xi'an University of Posts and Telecommunications China

ISBN: (纸本)9798400707674

Deep learning models perform exceptionally well in image processing; however, the increasing number of parameters and computational burdens make it difficult to apply these models on mobile devices. To address this issue, a widely adopted approach is using knowledge distillation to compress and optimize deep learning models. Traditional knowledge distillation trains a student network with soft targets from a teacher network. This paper proposes a Novel Dual Knowledge Distillation (NDKD) network by integrating Convolutional Block Attention Module (CBAM) distillation and feature distillation. Specifically, a new CBAM module and a hash layer are first added to improve the teacher-student network. Next, attention distillation loss is computed to transfer CBAM knowledge from the teacher module to the student network to enhance the student network's ability to capture low-level visual features. Finally, feature distillation loss is constructed by hashing layers to transfer semantic knowledge from the teacher network to the student network to enhance the student network's high-level semantic ability. Our method is compared with other knowledge distillation methods on benchmarking datasets including the CIFAR-10, SVNM, EMNIST, and Tire Pattern image dataset CIIP-TPID. Experimental results show that our method outperforms other methods on adapted datasets.

关键词： Convolutional Block Attention Module Deep learning image processing knowledge distillation

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Blind image suppression and carrier tracking in direct conversion receivers based on I/Q signal separation

Blind image suppression and carrier tracking in direct conve...

引用

Asilomar conference on Signals, Systems & Computers

作者： M. Valkama M. Renfors V. Koivunen Institute of Communications Engineering Tampere University of Technology Tampere Finland Signal Processing Laboratory Helsinki University of Technology Finland

The current trend in receiver architecture design is to simplify the RF front-end to get better integrability. One good example is the so-called direct-conversion receiver in which the desired RF channel is I/Q downconverted directly to baseband. In this paper, the I/Q mismatch problem in direct-conversion receivers is considered in detail, together with the more traditional carrier tracking task. It is shown that the fundamental effect of both the I/Q mismatch as well as carrier offsets is to create dependence between the I and Q signals. Based on this, a novel blind structure for joint carrier tracking and I/Q mismatch compensation is devised stemming from I/Q signal separation principle. The performance of the proposed approach is assessed using computer simulations and shown to be efficient and robust in the face of different imbalance and noise levels.

关键词： Source separation Radio frequency Frequency synchronization RF signals Signal processing Baseband Signal design Chirp modulation Constellation diagram Laboratories

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Annual International conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Mingshi Wang Boqiang Liu Zhongguo Liu College of Precision Instrument and Optoelectronics Engineering Tianjin University TJU Tianjin China College of Control Science and Engineering Shandong University Jinan China

ISBN: (纸本)0780384393

It is uncertain if different brain areas in response to pre-semantic picture processing are functionally homogeneous. Using event-related potentials (ERPs), we aimed to explore the neural activities in different brain regions in relation to processing of sentence memory and picture identification. Healthy subjects were chosen to discriminate visual stimulus pairs, and the ERPs were recorded from the scalp. Two kinds of stimuli were provided for each subject in the present study. One was Chinese sentence reading, referred as task 1. Another one was watching a line-drawing picture to judge if the picture matched the meaning of the sentence before. When the line-drawing picture received by the subject was inconsistent with the meaning of the sentence before, it was called as task 2, otherwise, if incongruous, it was called as task 3. Our findings implicate that stimuli of sentence memory and picture identification may exert neural activities on different working memory areas in the brain of human.

关键词： Enterprise resource planning Brain Humans Educational institutions Information processing Computer displays image processing Scalp Instruments Natural languages

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