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Performance Analysis of Color Normalization Methods in Histopathology Images

Performance Analysis of Color Normalization Methods in Histo...

引用

2022 international conference on Automatic Control and intelligent systems

作者： Yee, Wong Chung Jian, Tan Xiao Ab Rahman, Khairul Shakir Hoe, Teoh Leong Min, Lu Juei Hang, Quah Yi Ling, Teoh Chai Tunku Abdul Rahman Univ Coll TARUC Dept Elect & Elect Engn Kuala Lumpur Malaysia Tunku Abdul Rahman Univ Coll TARUC Ctr Multimodal Signal Proc Dept Elect & Elect Engn Kuala Lumpur Malaysia Hosp Tuanku Fauziah Dept Pathol Perlis Malaysia

ISBN: (纸本)9781665495813

Color normalization in histopathology is a prominent research topic in the image processing field as color in histopathology images plays a crucial role in diagnosis. As computer-aided diagnosis emerged, color normalization is much crucial as it becomes the foundation of medical image processing to assure algorithm precision and accuracy. In this paper, the main objective is to perform an analysis on three commonly used color normalization methods, namely histogram matching, histogram equalization, and stain unmixing methods. 60 breast histopathology images were used for testing purposes. Four statistical metrics were calculated to measure and determine the applicability of the color normalization methods: Structural similarity index measure (SSIM), Pearson's correlation coefficient (PCC), visual saliency-induced index (VSI), and Gradient similarity (GS). Based on the outputs, it is found that the stain unmixing method demonstrates better than that of the histogram matching and histogram equalization methods with higher values in SSIM and VSI, and comparable values in PCC and GS.

关键词： Color normalization histopathology histogram matching histogram equalization stain unmixing

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Deep Neural Network for visual Emotion Recognition based on ResNet50 using Song-Speech characteristics 5

Deep Neural Network for visual Emotion Recognition based on ...

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5th ieee international conference on Advanced systems and Emergent Technologies (IC_ASET)

作者： Ayadi, Souha Lachiri, Zied Natl Sch Engn Tunis ENIT Dept Elect Engn Signal Image & Informat Technol Lab SITI BP 37 Tunis 1002 Tunisia

ISBN: (纸本)9781665427357

Visual emotion recognition is a very large field. It plays a very important role in different domains such as security, robotics, and medical tasks. The visual tasks could be either image or video. Unlike the image processing, the difficulty of video processing is always a challenge due to changes in information over time variation. Significant performance improvements when applying deep learning algorithms to video processing. This paper presents a deep neural network based on ResNet50 model. The latter is conducted on the Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS) due to the variance of the nature of the data exists which is speech and song. The choice of ResNet model is based on the ability of facing different problems such as of vanishing gradients, the performing stability offered by this model, the ability of CNN for feature extraction which is considered to be the base architecture for ResNet, and the ability of improving the accuracy results and minimizing the loss. The achieved results are 57.73% for song and 55.52% for speech. Results shows that the Resnet50 model is suitable for both speech and song while maintaining performance stability.

关键词： Visual emotion recognition CNN ResNet50

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Multi-band discriminant speech synthesis analysis based on Natural Language processing 7

Multi-band discriminant speech synthesis analysis based on N...

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7th international conference on intelligent Computing and signal processing, ICSP 2022

作者： Liu, Songjia Yao, Yuancheng Liu, Binyu Zhu, Rui Ren, Jing Southwest University of Science and Technology School of Information Engineering Mianyang China

ISBN: (纸本)9781665478571

With the rapid development of neural networks and deep learning, speech synthesis technology has been significantly improved. The end-to-end speech synthesis systems based on deep learning have been able to synthesize speech with naturalness close to the original human pronunciation. However, the existing end-to-end speech synthesis system model is complex, and it is impossible to achieve real-time speech synthesis on devices with low computing power. In this paper, a multi-band discriminative autoregressive speech synthesis model is proposed based on natural language processing. The model uses an encoder-decoder architecture with attention mechanism, which is mainly composed of DSC-GRN modules. Stacking multiple convolutions with different expansion coefficients by gating the residual structure can increase the receptive field so that the encoder and decoder can pay attention to the context information with a longer time span, which can improve the performance of the model. The whole model uses full convolution architecture and can be trained in parallel. Compared with the existing autoregressive model, the number of parameters of the model is greatly reduced. The synthesis speed is improved, and the quality of synthesized speech is ensured. © 2022 ieee.

关键词： Deep learning

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D-band channel aggregation receiver architecture based on IF analog processing using digital wavelet 29

D-band channel aggregation receiver architecture based on IF...

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29th ieee international conference on Electronics, Circuits and systems (ieee ICECS)

作者： Dehos, Cedric Gulfo, Jorge-Luis Monsalve Lachartre, David Belot, Didier Courouve, Pierre Pelissier, Michael Univ Grenoble Alpes CEA LETI Minatec Campus Grenoble France

ISBN: (数字)9781665488235

ISBN: (纸本)9781665488235

The D-band (110-170GHz) is intended to provide tens of GHz bandwidth for beyond 5G very high data rate communications. The huge available band is split into multiple aggregated sub-bands. Managing such a number of bands is difficult using conventional heterodyne receiver. A different approach is proposed here relying on analogue projection in wavelet basis. In this paper, the signal projection in the Walsh/Hadamard domain is considered. The paper shows that the projection of aggregated channels into the parallelized Walsh analog architecture can relax the bandwidth constrains and the resolution of A/D conversion. The proposed architecture is deeply reconfigurable, allowing some AI to adjust the receiver for either communication purposes or spectrum sensing.

关键词： D-band channel aggregation compressive sensing Walsh receiver

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Estimation of Wrist Chattering Angle Based on Disturbance Observer 16

Estimation of Wrist Chattering Angle Based on Disturbance Ob...

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16th international Congress on Image and signal processing, BioMedical Engineering and Informatics, CISP-BMEI 2023

作者： Zhang, Xinyu Sun, Zhenyu Shu, Bairui Yokoi, Hiroshi Yong, Xu Li, Guanglin Jing, Xiaobei The Siat Branch Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen518055 China The University of Electro-Communications Joint Doctoral Program for Sustainability Research Tokyo182-8585 Japan The University of Electro-Communications Department of Mechanical Engineering and Intelligent Systems Tokyo182-8585 Japan

ISBN: (纸本)9798350330755

Due to the physiological constraints and daily habits of hand movements, the wrist chattering effect (WCE) will inadvertently cause disturbance to the accuracy of fingers' pattern recognition, when healthy subjects or amputees undergoing mirror training control their fingers according to instructions. This paper proposes a method for estimating WCE angles using a disturbance observer. Based on the Denavit-Hartenberg (D-H) convention and inverse kinematics, the intervals of the WCE during finger flexion and extension are determined. The research objective is to eliminate disturbance terms containing redundant information referring to sliding mode anti-jittering methods, making subsequent machine learning models less susceptible to disturbances. © 2023 ieee.

关键词： Inverse kinematics

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Aerial IRS-assisted Wireless Communication systems 10

Aerial IRS-assisted Wireless Communication Systems

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10th international conference on signal processing and Integrated Networks, SPIN 2023

作者： Sur, Samarendra Nath Singh, Arun Kumar Kandar, Debdatta Imoize, Agbotiname Lucky Sikkim Manipal Institute of Technology Sikkim Manipal UniversityMajitar Department of Electronics and Communication Engineering East Sikkim Rangpo737136 India North-Eastern Hill University Department of Information Technology Shillong India University of Lagos Akoka Faculty of Engineering Department of Electrical and Electronics Engineering Lagos100213 Nigeria Institute of Digital Communication Ruhr University Department of Electrical Engineering and Information Technology Bochum44801 Germany

ISBN: (纸本)9781665490993

intelligent reflecting surface (IRS) has emerged as a promising technology that open-up the window for manipulating the wireless channel. This introduced an additional degree of freedom in designing the future wireless communication system. The performance of a simple aerial IRS (AIRS) assisted wireless communication system is investigated in this paper by jointly optimizing the active and passive beamforming to maximize the sum-rate (SR). An alternating iterative algorithm is exploited to convert the non-convex optimization problem into two suboptimal problems corresponding to the active and passive beamforming. The simulated results highlight the possible SR gain that one can achieve through optimization in comparison to the un-optimized scenario. It also demonstrates the fact that optimization of beamforming also enhances the power efficiency of the system and also the impact of the IRS structure. © 2023 ieee.

关键词： Beamforming

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IOT Based Virtual Telepresence Robot

IOT Based Virtual Telepresence Robot

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ieee international conference on intelligent Techniques in Control, Optimization and signal processing (INCOS)

作者： S. Ewins Pon Pushpa T. Jayasree K. Mariammal Chris Jonathan Selwyn S. Benny Solomon S. Harish Raj Department of ECE College of Engineering Guindy Anna University Chennai India Department of Electronics Engg. Madras Institute of Technology Chrompet Anna University Chennai India

ISBN: (数字)9798350361186

ISBN: (纸本)9798350361193

This paper, marks an innovative exploration of robotics, IoT, and telepresence technologies, aiming to create a versatile and user-friendly robot, for remote control and real-time presence in distant locations. The key components and functionalities of this work, include the ESP32 micro controller, which serves as the central brain, interfacing with an analog joystick for user control. The Raspberry Pi camera, integrated through Message Queuing Telemetry Protocol, enhances capabilities, with high-quality real-time video, streaming to provide an immersive experience. The L298N motor driver facilitates precise control over the robot's mobility, allowing it to navigate in any direction. ESP32's role in interfacing with the analog joystick, for movement control is emphasized. As a conclusion, the integration of hardware and software components, in the development of the IoT based Virtual telepresence robot, represents a significant leap forward in the realm of remote robotics.

关键词： Visualization Telepresence Navigation Robot kinematics Robot vision systems Streaming media Real-time systems

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Study of Internal Exergy Parameters in Fault Diagnosis of Nuclear Power Plant systems 7

Study of Internal Exergy Parameters in Fault Diagnosis of Nu...

引用

7th international conference on intelligent Computing and signal processing, ICSP 2022

作者： Xie, Hongjun Yang, Zhigang Zheng, Gang Wu, Qingqun Xing, Zhaokai Shao, Jiaye Kang, Jiahao Yang, Zhiping State Nuclear Electric Power Planning Design & Reserch Institute Co. Ltd. Beijing China Shandong Nuclear Power Company Ltd. China North China Electric Power University China

ISBN: (纸本)9781665478571

As a clean, efficient, stable and sustainable energy, nuclear energy can be used for power generation, heating, seawater desalination, hydrogen production and so on. With the access of a high proportion of renewable energy, nuclear power will also undertake certain peak shaving tasks in the future. Therefore, the safety, economy and flexibility of nuclear power units will become a technical challenge for nuclear power units. As a means of diagnosing equipment faults, internal exergy parameters have the characteristics of simple calculation and intuitive expression, which provides a theoretical basis for real-time monitoring of equipment performance. Compared with the unit consumption analysis of equipment fault analysis and diagnosis of thermal power units, the calculation of internal exergy parameters is calculated for one of the logistics of a certain equipment, but this parameter can describe the overall performance of the equipment. The calculated internal exergy parameters can reflect the operation status of the equipment and effectively improve the safety and economy of the unit. © 2022 ieee.

关键词： Failure analysis

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Energy Efficiency Optimization in Massive MIMO systems with Low-Resolution ADCs 2

Energy Efficiency Optimization in Massive MIMO Systems with ...

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2nd international conference on Multidisciplinary Engineering and Applied Science, ICMEAS 2023

作者： Musa, Abdulwaheed Adebayo, Abdullateef Ola Peace Balogun, Oluwasijibomi Kwara State University Department of Electrical and Computer Engineering Malete Nigeria Kwara State University Centre for Artificial Intelligence and Machine Learning Systems Malete Nigeria University of Johannesburg Institute for Intelligent Systems South Africa

ISBN: (纸本)9798350358834

Massive multiple-input multiple-output (MIMO) is a promising 5G technology, but the high energy consumption from numerous radio components is a key challenge. Prior work has explored higher than 4-bit ADCs, but very low 1-2 bit remain uninvestigated. This paper provides an in-depth examination of the resolution versus power savings and signal quality degradation trade-offs with 1-3-bit analog-to-digital converters (ADCs) in Massive MIMO systems. Mathematical modeling and simulations quantify the exponential reduction in power consumption along with losses in key performance metrics like signal-to-interference-plus-noise ratio (SINR), throughput, and spectral efficiency with lower ADC resolutions stemming from increased quantization noise. Advanced linear detection techniques are shown to effectively recover the signal quality degradation. The analysis provides valuable insights on jointly optimizing ADC configuration and signal processing to maximize overall system efficiency. Energy savings of over 50% are demonstrated with 1-bit ADCs along with the ability to maintain acceptable performance metrics using linear detectors. The practical implementation feasibility is also discussed. This work enables ultra-low-resolution ADC deployments in energy-efficient Massive MIMO systems. © 2023 ieee.

关键词： Energy efficiency

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Automatic Persian Speech Emotion Recognition: A CNN-Based Approach Using PDREC and ShEMO Datasets

Automatic Persian Speech Emotion Recognition: A CNN-Based Ap...

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international conference of signal processing and intelligent systems (ICSPIS)

作者： Maryam Bahmani Hossein Marvi Department of Electronics and Robotics Shahrood University of Technology Shahrood Iran

ISBN: (数字)9798331532543

ISBN: (纸本)9798331532550

The need for advanced Speech Emotion Recognition (SER) systems has grown with the development of human-machine interaction technologies. This paper introduces a CNN model specifically designed to detect emotions in Persian speech, using two well-known datasets: the Persian Drama Radio Emotional Corpus (PDREC) and the Sharif Emotional Speech Database (ShEMO). The CNN model achieved high accuracy rates of 84% on the PDREC dataset and 90.21% on the ShEMO dataset, showing its reliability in different conditions. These results highlight the model's potential for real-world SER applications, improving the quality of human-computer interactions.

关键词： Human computer interaction Emotion recognition Accuracy Virtual assistants Speech recognition Mental health Speech enhancement signal processing Robustness Monitoring

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