Temporally locating objects with arbitrary class texts is the primary pursuit of open-vocabulary Video Instance Segmentation (VIS). Because of the insufficient vocabulary of video data, previous methods leverage image...
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We present progress towards realizing electronic-photonic quantum systems on-chip;particularly, entangled photon-pair sources, placing them in the context of previous work, and outlining our vision for mass-producible...
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Oil spills represent a growing environmental challenge that poses a significant threat to living organisms. Moreover, the treatment of oil spills, especially in severe cases, has serious economic repercussions and req...
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ISBN:
(数字)9798331516963
ISBN:
(纸本)9798331516970
Oil spills represent a growing environmental challenge that poses a significant threat to living organisms. Moreover, the treatment of oil spills, especially in severe cases, has serious economic repercussions and requires substantial labor and time. Therefore, the effective detection of oil spills has become an important research problem. Traditional methods for detecting oil spills, such as manual patrolling and dynamic sensors, are often limited in accuracy and coverage. As a result, the automation of oil spills detection has emerged as a critical global imperative in scientific research. The aim of this paper is to employ deep learning technology to achieve effective detection of oil spills based on aerial images. Our approach is composed of two phases. In the first phase, a Deep Convolutional Neural Network (DCNN), namely ResNet50, is trained on a large dataset containing images showing oil spills at a seaport. The trained DCNN is used to classify the input image as "Oil Spill" or "No Oil Spill". In the second phase, the images classified as "Oil Spill" are analyzed using a deep learning detection model, namely You-Only-Look-Once (YOLOv4), to localize the oil spills. The results indicate the capability of the proposed method to achieve effective oil spill detection. In particular, the classification accuracy obtained by the ResNet50 model is equal to 98%. Moreover, the YOLOv4 model was able to obtain effective localization of the oil spills with mean-average precision of 62%.
This paper examines the reproducibility of massive information analytics under particular factors. The paper proposes the 'performing Scalable Inference' technique to cope with scalability troubles and to expl...
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Fiber optic-based sensors have experimented with significant technological advances in the last two decades. Distributed acoustic sensors represent their most recent iteration. This sensing technology become all the c...
Fiber optic-based sensors have experimented with significant technological advances in the last two decades. Distributed acoustic sensors represent their most recent iteration. This sensing technology become all the cable length into a sensor, a favorable condition for seismic studies. Data preprocessing is a crucial step in this study, in which the seismic signals captured by optical interrogators must be converted to the apparent velocity of particles that sensitized the fiber. Amongst the main conversion algorithms, the ones based on Fourier Transforms are more adopted at large-scale surveys. This paper presents an algorithm implementation for this conversion, based on the 2D Fourier Transform, in a small-scale laboratory investigation. The results are favorable and show that it is a possible use. It brings more definition to individualizing first break time arrivals, equalizing signal amplitude, and aligning oscillation peaks, essential parameters for applying reflections and refraction methods in seismic studies.
Reliable classification of sleep stages is crucial in sleep medicine and neuroscience research for providing valuable insights, diagnoses, and understanding of brain states. The current gold standard method for sleep ...
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The spread of Corona Virus Disease 19 (COVID-19) in Indonesia is still relatively high and has not shown a significant decrease. One of the main reasons is due to the lack of supervision on the implementation of healt...
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Exceptional points (EPs) are critical points in the parameter space of non-Hermitian systems, where two or more eigenvalues and eigenvectors simultaneously coalesce. The remarkable physics and behavior of waves at the...
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Exceptional points (EPs) are critical points in the parameter space of non-Hermitian systems, where two or more eigenvalues and eigenvectors simultaneously coalesce. The remarkable physics and behavior of waves at these EPs have raised considerable attention. Previous research has accessed EPs in parity-time (PT) symmetric systems through spatially modulated parameters. Using acoustics, this Letter demonstrates a different family of EPs in classical wave systems that emerge from coordinated modulation of mass density and loss/gain in time. This condition can create nonreciprocal coupling between arbitrary modes at the EPs, leading to exotic behaviors such as unilateral frequency conversion and linear amplification of waves that are unattainable at conventional time-invariant systems. Moreover, these phenomena can be attained with only loss, and acoustic gain via modal energy transfer is demonstrated in a loss-only system at such EPs. Our work marries time-varying systems with EPs, which could open new avenues for wave manipulation.
Video super-resolution (VSR) is widely used in various high-definition applications, such as HDTVs and smartphones, requiring a dedicated upscaling technique for realtime full-HD generation. To reduce on-chip buffers ...
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The impact of hot carrier injection (HCI) on the performance of standard and low-VT FinFETs are investigated and benchmarked with each other. For this investigation, these FinFETs were fabricated with various gate len...
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