Quantum network is an emerging type of network structure that leverages the principles of quantum mechanics to transmit and process information. Compared with classical data reconstruction algorithms, quantum networks...
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ISBN:
(纸本)9798350364613;9798350364606
Quantum network is an emerging type of network structure that leverages the principles of quantum mechanics to transmit and process information. Compared with classical data reconstruction algorithms, quantum networks make image reconstruction more efficient and accurate. They can also process more complex image information using fewer bits and faster parallel computing capabilities. Therefore, this paper will discuss image reconstruction methods based on our quantum network and explore their potential applications in imageprocessing. We will introduce the basic structure of the quantum network, the process of image compression and reconstruction, and the specific parameter training method. Through this study, we can achieve a classical image reconstruction accuracy of 97.57%. Our quantum network design will introduce novel ideas and methods for image reconstruction in the future.
The diagnosis of a range of eye disorders needs to categorize the retinal vessels. Computerized implementation of this process is becoming increasingly essential for automated screening systems for retinal diseases. T...
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Radar-based sensing emerges as a promising alternative to cameras and wearable devices for indoor human activity recognition. Unlike wearables, radar sensors offer non-contact and unobtrusive monitoring, while being i...
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ISBN:
(纸本)9781510673915;9781510673908
Radar-based sensing emerges as a promising alternative to cameras and wearable devices for indoor human activity recognition. Unlike wearables, radar sensors offer non-contact and unobtrusive monitoring, while being insensitive to lighting conditions and preserving privacy as compared to cameras. This paper addresses the task of continuous and sequential classification of daily life activities, unlike the problem to isolate distinct motions in isolation. Upon acquiring raw radar data containing sequences of motions, an event detection algorithm, the Short-Time-Average/Long-Time-Average (STA/LTA) algorithm, is utilized to detect individual motion segments. By recognizing breaks between transitions from one motion type to another, the STA/LTA detector isolates individual activity segments. To ensure consistent input shapes for activities of varying durations, image resizing and cropping techniques are employed. Furthermore, data augmentation techniques are applied to modify micro-Doppler signatures, enhancing the classification system's robustness and providing additional data for training.
The proceedings contain 325 papers. The topics discussed include: significance and comparison of PCA in removing multicollinearity of variables in face detection and recognition;plant species classification using deep...
ISBN:
(纸本)9798350365092
The proceedings contain 325 papers. The topics discussed include: significance and comparison of PCA in removing multicollinearity of variables in face detection and recognition;plant species classification using deep learning;optimized local secret sharing techniques for distributed blockchain networks;NNXG: privacy based imageprocessing in pneumonia detection from chest x-ray using modified neural network architecture and XGBoost;a systematization of polycystic ovary syndrome using ultrasonography image follicle screening;automatic number plate recognition system using deep learning algorithms and imageprocessing for surveillance;ai-enhanced intelligent control systems for electric vehicles;and speculative analysis of CNN's and ResNet50 for the identification of emotion from facial expressions.
This paper delves into the groundbreaking potential of quantum computing, with a primary focus on qubits and their wide-ranging applications. It explores the fundamental principles of quantum physics, such as entangle...
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Despite the widespread implementation of SCADA systems in factories for centralized data management, their functionality is restricted to devices equipped with sensors. Manual readings are still prevalent for critical...
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To improve the segmentation performance of multi-objective evolutionary clustering algorithms, this paper proposes a parallel dual broad learning surrogate assisted semi-supervised kernel multi-objective evolutionary ...
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ISBN:
(纸本)9798350349122;9798350349115
To improve the segmentation performance of multi-objective evolutionary clustering algorithms, this paper proposes a parallel dual broad learning surrogate assisted semi-supervised kernel multi-objective evolutionary rough fuzzy clustering algorithm (PDBLS-SKMRFC) for image segmentation. First, the algorithm constructs a parallel dual broad learning surrogate assisted multi-objective evolutionary framework. It uses two broad learning systems as classification and regression surrogate models to evaluate the population in parallel manner. In the framework, a multi-population division strategy guided by dual broad learning system, a dominant individual crossover strategy, a sub-population mutation strategy, and a hierarchical environment selection strategy are designed to obtain more excellent offspring populations. Then, a semi-supervised kernel rough fuzzy intra-class compactness function is constructed, which uses a few labels and pseudo-labels as supervision information to improve the image segmentation performance, and evaluates the clustering quality together with the kernel separability function. Finally, a semi-supervised kernel rough fuzzy clustering validity index is designed to select the optimal solution from the final non-dominated solution set for image segmentation. Experimental results on color images show the effectiveness of the proposed algorithm.
As one of the main carriers of information transmission and storage, image data need to be compressed in some application scenarios. Traditional image compression methods, although reducing the size of image files to ...
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Artificial intelligence (AI) is a computer technology that has a human way of thinking and can imitate the human brain. The integration of AI into medical imaging has revolutionized diagnosis and treatment, providing ...
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In this paper, we present a novel transformer-based architecture for end-to-end image compression. Our architecture incorporates blocks that effectively capture local dependencies between tokens, eliminating the need ...
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