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Scalable and custom-precision floating-point hardware convolution core for using in AI edge processors
AI algorithms such as CNNs devices have necessitated the design of lightweight, low-power, and fast hardware in edge processors. In this paper, a...
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Creating the Floating Architecture
Creating modern architecture patterns and trying to avoid the pitfalls of antipatterns, by adopting and applying the principles of DevOps. It will be...
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RS-UNet: lightweight network with reflection suppression for floating objects segmentation
The research on image semantic segmentation of floating objects on water is beneficial to realize the automatic location of pollutants and facilitate...
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TrueFloat: A Templatized Arithmetic Library for HLS Floating-Point Operators
Hardware designers working on FPGA accelerators are free to explore ad-hoc value representations that differ from the IEEE 754 floating-point...
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Synthesis of Rigorous Floating-Point Predicates
A floating-point predicate is a routine that returns a boolean value based on a result of a floating-point computation. For example, in computational...
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A Single Electron Transistor-Based Floating Point Multiplier Realization at Room Temperature Operation
Floating point numbers provide more range as compared to the fixed point values. The multiplier is one of the main blocks of a processor. For...
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Floating Fog: extending fog computing to vast waters for aerial users
There are thousands of flights carrying millions of passengers each day, having three or more Internet-connected devices with them on average....
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Modified term frequency-inverse document frequency based deep hybrid framework for sentiment analysis
Sentiment Analysis is a highly crucial subfield in Natural Language Processing that attempts to extract the public sentiment from the accessible user...
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Evaluation of the Use of Low Precision Floating-Point Arithmetic for Applications in Radio Astronomy
Conventionally, the front-end Digital Signal Processing (DSP) for applications in radio astronomy employed low-precision fixed-point arithmetic....
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Floating Point Numbers
Numbers from \(\mathbb {R}\) cannot be handled...
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Frequency domain-enhanced transformer for single image deraining
Since Transformers show a strong capability of building long-range dependencies, the relevant methods are extensively employed for image deraining...
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Hybrid Intelligent Control for Maximum Power Point Tracking of a Floating Wind Turbine
Floating Offshore Wind Turbines (FOWTs) are surrounded by an environment with random phenomena (wind and waves) that disturb the ideal operation of...
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Pyramid NeRF: Frequency Guided Fast Radiance Field Optimization
Novel view synthesis using implicit neural functions such as Neural Radiance Field (NeRF) has achieved significant progress recently. However, it is...
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CB-YOLO: composite dual backbone network for high-frequency transformer coding defect detection
The high-frequency transformer is a crucial component of various electronic devices. The coding on high-frequency transformers indicates the product...
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Frequency-importance gaussian splatting for real-time lightweight radiance field rendering
Recently, there have been significant developments in the realm of novel view synthesis relying on radiance fields. By incorporating the Splatting...
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SpFusionNet: deep learning-driven brain image fusion with spatial frequency analysis
In the domain of multi-focus (MF) and multi-model image fusion (MMIF), accurately merging focused regions from various images remains a challenge....
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Distribution-decouple learning network: an innovative approach for single image dehazing with spatial and frequency decoupling
Image dehazing methods face challenges in addressing the high coupling between haze and object feature distributions in the spatial and frequency...
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Towards Generalized UAV Object Detection: A Novel Perspective from Frequency Domain Disentanglement
When deploying unmanned aerial vehicle (UAV) object detection networks to complex, real-world scenes, generalization ability is often reduced due to...
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FeSTGCN: A frequency-enhanced spatio-temporal graph convolutional network for traffic flow prediction under adaptive signal timing
Traffic flow prediction is the fundamental cornerstone of intelligent urban transportation systems. However, existing research has predominantly...
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Degramnet: effective audio analysis based on a fully learnable time–frequency representation
Current state-of-the-art audio analysis algorithms based on deep learning rely on hand-crafted Spectrogram-like audio representations, that are more...
