With the rapid advancement of modern electronic warfare, the volume of signals intercepted by electronic reconnaissance equipment is increasing exponentially, yet the quality of these signals remains inconsistent. Low...
详细信息
In the realm of Printed Circuit Board (PCB) manufacturing, the alignment process is pivotal for ensuring the functional integrity of the final product. Traditional image measurement techniques, while foundational, oft...
详细信息
ISBN:
(纸本)9798400717024
In the realm of Printed Circuit Board (PCB) manufacturing, the alignment process is pivotal for ensuring the functional integrity of the final product. Traditional image measurement techniques, while foundational, often fall short of achieving the high degree of accuracy and precision necessary for today's complex PCB designs. This research presents a novel approach that significantly enhances measurement accuracy through the application of optimized imageprocessing techniques. By leveraging advanced algorithms within the OpenCV library, we introduce a methodology that accurately transforms pixel coordinates into real-world measurements, crucial for precise PCB alignment. Our technique employs edge detection algorithms such as Canny, Sobel, and Prewit filters, combined with a machine learning model that adapts to variations in real-time imaging conditions. The study delineates the development of a user-friendly graphical interface that streamlines the measurement process, making it accessible for practical industrial application. Results from experimental validations indicate a substantial improvement in measurement precision, with a demonstrable reduction in alignment errors compared to conventional methods. This leap forward not only promises to elevate the standards of PCB manufacturing but also opens avenues for similar advancements in other domains where image measurement is essential. The implications of this work are far-reaching, with the potential to significantly boost the efficiency and reliability of electronic manufacturing processes globally.
Language models have been successfully used to model natural signals, such as images, speech, and music. A key component of these models is a high quality neural compression model that can compress high-dimensional na...
详细信息
ISBN:
(纸本)9781713899921
Language models have been successfully used to model natural signals, such as images, speech, and music. A key component of these models is a high quality neural compression model that can compress high-dimensional natural signals into lower dimensional discrete tokens. To that end, we introduce a high-fidelity universal neural audio compression algorithm that achieves 90x compression of 44.1 KHz audio into tokens at just 8kbps bandwidth. We achieve this by combining advances in high-fidelity audio generation with better vector quantization techniques from the image domain, along with improved adversarial and reconstruction losses. We compress all domains (speech, environment, music, etc.) with a single universal model, making it widely applicable to generative modeling of all audio. We compare with competing audio compression algorithms, and find our method outperforms them significantly. We provide thorough ablations for every design choice, as well as open-source code and trained model weights. We hope our work can lay the foundation for the next generation of high-fidelity audio modeling.
image denoising is a critical task in imageprocessing that involves the removal of noise or unwanted distortions from an image while preserving its essential features. Most of the commonly captured pictures are obtai...
详细信息
ISBN:
(纸本)9789819984756;9789819984763
image denoising is a critical task in imageprocessing that involves the removal of noise or unwanted distortions from an image while preserving its essential features. Most of the commonly captured pictures are obtained using mobile cameras or CCTV surveillance cameras producing video footage of the activities of people who are stationary or in motion. There is a need to restore such captured footage from noise so that it can become evidence for different criminal cases. Denoising face images captured using CCTV is a challenging task due to fine details being affected by noise. In this paper, we evaluate three image denoising techniques Block-Matching and 3D (BM3D), k-Means Singular Value Decomposition (KSVD), and Weighted Nuclear Norm Minimization (WNNM). The performance of these methods is analyzed using Mean Squared Error (MSE), Peak Signal to Noise Ratio (PSNR), Structural Similarity Index (SSIM), and Visual Information Fidelity (VIF). It is observed that the overall performance of KSVD is better for a Gaussian and Salt and Pepper noise.
A camera with an image sensor is an important alternative device to a photodiode-based receiver of visible-light communication in outdoor scenarios. The intrinsic color separation capability of a camera qualifies colo...
详细信息
A camera with an image sensor is an important alternative device to a photodiode-based receiver of visible-light communication in outdoor scenarios. The intrinsic color separation capability of a camera qualifies color shift keying (CSK) modulation as an intuitive solution to enhance the achievable data rate. The symbol error rate (SER) of CSK modulation is considerably important to system design and performance evaluation, and has not been extensively investigated for outdoor optical camera communication systems from the viewpoint of camera-based channel and imageprocessing-based demodulation. In this study, a two-level channel model is proposed to characterize CSK transmission in a single pixel and in the entire image. A general framework of SER analysis for arbitrary CSK constellations was proposed by directly calculating the upper bounds from the empirical distribution of the noise light in the CIE 1931 color space. Through numerical simulations, the influence of the image detector on CSK demodulation was evaluated. The results indicated that an accurate target region is important for maintaining the SER, and an enlarged target region is beneficial when the maximum ratio combination and selective combination algorithms are used in pixel combination.
Detection of corrosion in moving objects like ships is challenging due to the dynamic nature of the input image. Existing machine learning techniques are suitable for static images and the algorithms suffer in perform...
详细信息
Finding min s-t cuts in graphs is a basic algorithmic tool, with applications in image segmentation, community detection, reinforcement learning, and data clustering. In this problem, we are given two nodes as termina...
详细信息
ISBN:
(纸本)9781713899921
Finding min s-t cuts in graphs is a basic algorithmic tool, with applications in image segmentation, community detection, reinforcement learning, and data clustering. In this problem, we are given two nodes as terminals and the goal is to remove the smallest number of edges from the graph so that these two terminals are disconnected. We study the complexity of differential privacy for the min s-t cut problem and show nearly tight lower and upper bounds where we achieve privacy at no cost for running time efficiency. We also develop a differentially private algorithm for the multiway k-cut problem, in which we are given k nodes as terminals that we would like to disconnect. As a function of k, we obtain privacy guarantees that are exponentially more efficient than applying the advanced composition theorem to known algorithms for multiway k-cut. Finally, we empirically evaluate the approximation of our differentially private min s-t cut algorithm and show that it almost matches the quality of the output of non-private ones.
This study addresses the detection of dislodged fault in photovoltaic (PV) power stations by proposing a visible light imageprocessing method utilizing line scanning. The method employs HSV (Hue-Saturation-Value) col...
详细信息
In this paper, the problem of Integrated Sensing and Communications (ISAC) system is considered to achieve an overall improvement in positioning accuracy. To achieve this goal, two optimization algorithms are proposed...
详细信息
Aiming at the problem that the temperature information of the solid-state power controllers (SSPCs) contains both fault features and a large amount of redundant data, a convolutional neural network (CNN) fault diagnos...
详细信息
暂无评论