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Early Skin Cancer Detection Using Deep Learning 3

Early Skin Cancer Detection Using Deep Learning

引用

3rd international conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023

作者： Ali, Mohd Arif Khan, Munna Sherwani, Kashif I.K. Jamia Millia Islamia Department of Electrical Engineering New Delhi India

ISBN: (纸本)9798350319125

Skin cancer is a prevalent and potentially life-threatening disease which is increasing day by day globally, due to the depletion of the ozone layer and other atmosphere changes. Various computer-aided methods have been proposed for diagnosis of skin cancer. However, for accurate diagnosis of skin cancer, computer-aided diagnosis (CAD) system poses several difficulties. These includes data quality, heterogeneity and complexity of skin layers which is a challenging visual characteristic for cell detection. Challenge of automatically and effectively extracting discriminative features for skin cancer detection is indeed a significant research problem in the field of medical image analysis. Deep learning-based methods have shown great promise in automating feature extraction by learning relevant features directly from the raw images. Convolutional Neural Networks (CNNs) and other deep architectures can automatically discover hierarchical features that may not be apparent to human experts. However, these models require a large amount of labeled data for training, which can be a challenge for the skin cancer detection. To address these challenges and further improve deep learning models for skin cancer detection. The architecture of Alex Net offers an innovative approach by proposing a Convolutional Neural Network (CNN) based Alex net model. This technique involves pre-trained weights and features learned by Alex net model on large datasets. Additionally for accurate skin cancer diagnosis, data augmentation techniques are employed to enhance the robustness and generalization capabilities of the model. The proposed model achieves 98.0% accuracy with augmentation and without any augmentation it achieves 92.9% accuracy. © 2023 IEEE.

关键词： Alex Net CNN transfer learning model Deep learning ISIC Dataset Malignant detection

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A Novel Speckle-Robust Feature Map and Research on Rotation Invariance of Feature Maps in the SAR Image 3

A Novel Speckle-Robust Feature Map and Research on Rotation ...

引用

3rd international conference on computer Vision and Pattern Analysis, ICCPA 2023

作者： Li, Jiamu Wang, Yi Yu, Wenbo Wang, Zijian Yu, Zhongjun Aerospace Information Research Institute Chinese Academy of Sciences Beijing100190 China School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences Beijing101408 China School of Technology Beijing Forestry University Beijing100083 China Research Center for Biodiversity Intelligent Monitoring Beijing Forestry University Beijing100083 China

ISBN: (纸本)9781510667563

The feature map is often used for describing the characteristics of key points in image registration applications. Due to feature information being sensitive to rotation and noise, the values of calculation methods for various feature maps would change in different rotation or noise conditions. Consequently, it is unfavorable to obtain the stable descriptor for the same feature point in different images. Specifically, speckle noise damages the synthetic aperture radar (SAR) image seriously, which makes SAR image registration more difficult. In this paper, a novel feature map, which is robust to speckle noise, is proposed. A fully size-adaptive sliding window method is embedded into the ratio of exponentially weighted average method for its noise robustness improvement. Then, a series of Monte Carlo experiments compare the rotation and speckle stabilities among various feature map methods comprehensively. The experimental results reflect that the proposed feature map method is stable while speckle noise increases, and it has less mean orientation difference than others. Moreover, the data of experimental results can be used to support many other analyses on feature maps. © 2023 SPIE.

关键词： Image registration

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A method for generating reconfigurable photonic arbitrary phasecoded microwave signals with fundamental/double/triple carrier frequencies 2

A method for generating reconfigurable photonic arbitrary ph...

引用

2nd international conference on Optoelectronic Information and computer engineering, OICE 2023

作者： Yin, Jing Zhao, Yan Yang, Feng Yang, Dengcai Wang, Yunxin Institute of Laser Engineering Faculty of Materials and Manufacturing Beijing University of Technology Beijing100124 China Department of Physics and Optoelectronic Engineering Faculty of Science Beijing University of Technology Beijing100124 China Beijing Engineering Research Center of Precision Measurement Technology and Instruments Beijing University of Technology Beijing100124 China

ISBN: (纸本)9781510667525

A method for generating reconfigurable photonic arbitrary phase-coded microwave signal with fundamental/double/triple carrier frequencies is proposed and demonstrated. A dual-parallel dual-polarization Mach-Zehnder modulator (DP-DPMZM) and an optical bandpass filter (OBPF) are cascaded to generate orthogonally polarized optical carrier signals and 1st/2nd/3rd-order sideband signals, which are sent into a polarization-dependent phase modulator (PD-PM), which can realize phase modulation with different polarization state optical signals. The phasemodulated signal after PD-PM will be projected into the polarization direction with a polarizer (Pol) and the phaseshifting microwave signal will be obtained with a photodetector (PD). This method enables the frequency multiplication factor to be changed by tuning the bias voltage of the modulator alone, which makes the system can work in a wide bandwidth, and it also reduces the frequency requirements of the local oscillator (LO) signal. In the simulation, binary phase-coded signals with center frequencies of 6 GHz, 12 GHz, and 18 GHz are generated, and their performance is verified. © 2023 SPIE. All rights reserved.

关键词： Polarization

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Design of digital watermarking algorithm based on compression sensing 3

Design of digital watermarking algorithm based on compressio...

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3rd international conference on Image Processing and Intelligent Control, IPIC 2023

作者： Wang, Yichen Sheng, Hu Li, Jing Li, Jiating Liu, Jinxing School of Computer and Communication Engineering Dalian Jiaotong University Liaoning Province Dalian116028 China

ISBN: (纸本)9781510668140

With the rapid development of multimedia technology and the Internet, the security of multimedia data is facing more and more threats. Digital watermarking technology can effectively solve this problem, and compressed sensing theory is widely used in the field of digital watermarking. As the theoretical basis of the new generation of information processing, this theory can effectively solve the problem of multimedia data being attacked. Based on compressed sensing theory, combined with discrete wavelet transform and SVD decomposition, this research realized the embedding and extraction of watermark in the observation domain after image thinning, and tested different forms of watermark attacks such as salt pepper noise, Gaussian noise and filtering on the watermarked image. The experimental data shows that the PSNR value and NC of the algorithm are in line with expectations, and it has good robustness, transparency, and extraction resistance. © 2023 SPIE.

关键词： Discrete wavelet transforms

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Sustainable Development of Smart Farming and Agriculture Business using Data Mining 3

Sustainable Development of Smart Farming and Agriculture Bus...

引用

3rd international conference on Secure Cyber Computing and Communications, ICSCCC 2023

作者： Kholiya, Deepak Bagla, Piyush Mishra, Amit Kumar Tripathi, Neha Pandey, Neeraj Kumar School of Agriculture Graphic Era Hill University Uttarakhand Dehradun India National Institute of Technology Computer Science & Engineering Dept. Punjab Jalandhar India Graphic Era Hill University Dept. of Computer Science & Engineering Uttarakhand Dehradun India Graphic Era Deemed to Be University Dept. of Computer Science & Engineering Uttarakhand Dehradun India School of Computing Dit University Uttarakhand Dehradun India

ISBN: (纸本)9798350300710

The globally most significant financial sector is developing in agriculture, which is expected to play a significant role in India's overall financial landscape. Sustainable smart agriculture development is a newly created techniques, to save crops from susceptible to many environments and financial factors. Soil, climate / weather, irrigation, organic fertilizers, suitable temperature, precipitation, gathering, pesticide weeds, and other areas are a small part of the area on which development is down and out. Crop yield records are also necessary for the skilful chain selling of associations focused on experiences. The approach to survey a plan of 'server farms' is to group them into 'social activities' according to some segment measure. In contrast to server farms in different groups, which are in a monstrous fair route from one another, the goal is for server farms in a significant group to have a nice little path from one another. Exam data is packaged in specifically designed social affairs. The 'usual' structure of the data would be obtained by explicitly outlining bundles. Data mining techniques like one rule, Repeated Incremental Pruning to Produce Error Reduction (RIPPER), Fuzzy Un-ordered Rule Induction Algorithm (FURIA), and multiple linear regression with binomial are used to analyze agribusiness data and identify appropriate crop expansion boundaries. Agribusiness advances and becomes more resilient to climate change by reviewing new, non-exploratory data and mining a wealth of old harvest, soil, and meteorological data. © 2023 IEEE.

关键词： Multiple linear regression

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Status and Application of Artificial Intelligence-Based Cooperative Positioning and Navigation technology for UAV Clusters 1

引用

3rd international conference on Autonomous Unmanned Systems, ICAUS 2023

作者： Sheng, Danting Cheng, Jin Li, Fengyi Hao, Mingrui Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China Intelligent Science and Technology Academy Limited of CASIC Beijing100041 China

ISBN: (数字)9789819710911

ISBN: (纸本)9789819710904

Aiming at the UAV cluster cooperative navigation, this paper tries to summarize the development experience and existing results on two issues, namely, the application of filtering and artificial intelligence in UAV cluster cooperative navigation. The application of filtering in UAV cluster cooperative navigation briefly describes the application of Kalman filtering and extended Kalman filtering, traceless Kalman filtering and other nonlinear filters, intelligent optimization algorithms combined with particle filtering in cooperative navigation. Artificial Intelligence Methods in Cooperative Navigation of UAV Clusters describes the application of deep feed-forward networks, brain-like information fusion methods based on integrated learning, multivariate interpolation of radial-based neural networks and Kalman filtering combined in the field of cooperative navigation. The results of existing applications of filtering and artificial intelligence in UAV cluster cooperative navigation are analyzed and summarized, and the future development of the field is outlooked. © Beijing HIWING Scientific and Technological Information Institute 2024.

关键词： Kalman filters

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VSPNet: A fish counting model based on convolutional neural network 3

VSPNet: A fish counting model based on convolutional neural ...

引用

3rd international conference on Intelligent Computing and Human-computer Interaction, ICHCI 2022

作者： Tian, Yuan Yue, Jun School of Information and Electrical Engineering Ludong University Yantai264025 China

ISBN: (纸本)9781510661301

Fish counting is one of the key issues in fish farming and trade. However, manual counting is not only expensive and inefficient, but it can also harm the fish. In order to solve the above problems, this paper proposes a counting model named VSPNet based on convolutional neural network to realize intelligent counting of snakehead fish. Firstly, the snakehead counting dataset is created, and the snakehead objects in each image in the dataset are labeled to obtain the true density map;and then the EESP module is added after the 10th convolutional layer of the VGG model to increase the receptive field, extract deep-level semantic information, and generate the estimated density map;finally, the total number of snakehead in the image is predicted from the density map. The experimental results show that the method proposed in this paper outperforms the MPS and DSNet models on the snakehead fish counting dataset, which proves the effectiveness of the method. © 2023 SPIE.

关键词： Fish

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Research on AINDANE-Faster R-CNN based metal plate defect detection method 3

Research on AINDANE-Faster R-CNN based metal plate defect de...

引用

3rd international conference on Digital Signal and computer Communications, DSCC 2023

作者： Yang, Xu Yan, Peiyu An, Xiaofeng School of Electronic Information Engineering Changchun University of Science and Technology Jilin Province Changchun China JiLin Engineering Normal University Jilin Province Changchun China

ISBN: (数字)9781510666566

ISBN: (纸本)9781510666559

To address the problem that metal reflection, ambient illumination and different defect size affect the defect detection accuracy in metal defect detection, an AINDANE-Faster R-CNN based metal flat detection method under complex illumination conditions is proposed, which firstly adopts a adaptive and integrated neighborhood dependent approach for nonlinear enhancement(AINDANE) to preprocess the defect images and improve the image brightness to highlight the detail features such as color,profile and texture of defects, and then ResNet50 network is utilized as the defect semantic feature extraction network for the Two-stage Faster R-CNN model. In addition, this paper also constructs a dataset of three defects of metal aluminum plate under low light and uneven light conditions, such as scratches, oil stains and pits, and the method achieves a mean average accuracy of 92.01% on the defect dataset. Compared to existing one-stage surface defect detection methods, the algorithm in this paper is optimal. © 2023 SPIE.

关键词： Image enhancement

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Image Classification of Ischemic Stroke Blood Clot Origin using Stacked EfficientNet-B0, VGG19 and ResNet-152 3

Image Classification of Ischemic Stroke Blood Clot Origin us...

引用

3rd international conference on Secure Cyber Computing and Communications, ICSCCC 2023

作者： Rao, Masabathula V S Raghavendra Puligundla, Surya Ekkala, Nikhil Sai Chebrolu, Srilatha National Institute of Technology Department of Computer Science and Engineering Andhra Pradesh India

ISBN: (纸本)9798350300710

Stroke continues to be the second-leading cause of mortality globally. Over 700,000 Americans suffer from an ischemic stroke every year as a result of a blood clot clogging a brain artery. The chances of the patient surviving a second stroke where recurrent strokes account for 23% of all incidents, are decreased. The motivation of this work is to help physicians better understand the causes of blood clots in fatal strokes, making it simpler for doctors to recommend the most effective post-stroke therapeutic management and lowering the risk of a second stroke. Whole slide digital pathology images capture the blood clot of the patient who has suffered from ischemic stroke. The objective of this work is to classify the blood clot origin in the case of ischemic stroke. Its a binary classification problem where the classes are Cardioembolism and Large artery atherosclerosis. Deep learning models can be applied to classify the stroke origin efficiently. This work proposes a stacked deep learning model with VGG19, ResNet-152, EfficientNet-B0 to classify the stroke origin. Experiments have been conducted on Mayo Clinic - Strip AI dataset from Kaggle. Comparisons have been made with these individual models and also combinations of these models and found that the proposed model is achieving lower loss value. © 2023 IEEE.

关键词： computer vision

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Precision-Aware Data Management in Federated Cloud Environments: A Context-Aware Approach 3

Precision-Aware Data Management in Federated Cloud Environme...

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3rd international conference on Innovative Mechanisms for Industry Applications, ICIMIA 2023

作者： Kolekar, Vikas K Sakhare, Sachin R SMT. Kashibai Navale College of Engineering Department of Computer Engineering Pune India Savitribai Phule Pune University Pune India Vishwakarma Institute of Information Technology Department of Computer Engineering Pune India

ISBN: (纸本)9798350343632

In the ever-evolving world of cloud computing, the management of data in federated cloud environments presents a complex challenge. Presented study investigates precision-aware data management techniques with the goal of improving the efficiency of federated cloud systems. Our work acknowledges the crucial significance of context-awareness in enhancing data operations and introduces an adaptive data management middleware. The precision-aware system caters to the requirement for accuracy and reliability in data processing by integrating sophisticated algorithms and techniques. Simultaneously, the integration of context-awareness ensures that data management strategies dynamically adapt to the changing contextual conditions within federated cloud environments. This strategy has two aspects, first to increase the accuracy of data operations and second to improve the overall responsiveness and adaptability of the system. Our study focuses on creating innovative middleware that can effortlessly integrate precision-aware and context-aware features. We assess the effectiveness of the proposed system by conducting empirical evaluations and analyzing real-world use cases. Our findings demonstrate that the system is capable of optimizing data management in diverse and dynamic federated cloud contexts. The results of this study enhance the progress of adaptive data management approaches by providing a detailed comprehension of the interaction between precision and context in federated cloud environments. Proposed work is important for research scholars, practitioners, and industry experts who are looking for creative ways to improve the performance and adaptability of data management systems in complex cloud environments. © 2023 IEEE.

关键词： Adaptive middleware Context-awareness Data management Federated cloud environments Precision-awareness

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