Signal Processing
These are tight pedestrian masks for the thermal images present in the KAIST Multispectral pedestrian dataset, available at https://soonminhwang.github.io/rgbt-ped-detection/
Both the thermal images themselves as well as the original annotations are a part of the parent dataset. Using the annotation files provided by the authors, we develop the binary segmentation masks for the pedestrians, using the Segment Anything Model from Meta.
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446 Views
We used the recording data of four marine mammals from 1940 to 2000 provided by the Watkins Marine Mammal Sound Library, namely 'Killer Whale', 'Humpback Whale', 'Pilot Whale', and 'Bottlenose Dolphin'. This sound library provides researchers with three options for experimental use: selected clips, complete clip sets, and original tapes [39]. This paper relies on selected clips. This part of the data further shows the wide applicability of our model because it covers different time periods, geographical locations, and recording equipment.
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219 Views
Abstract—In recent years, there has been a significant advancement
in the field of healthcare systems with the introduction
of fifth generation cellular communications and beyond (5GB).
This development has paved the way for the utilization of
telecommunications technologies in healthcare systems with an
level of certainty, reaching up to 99.999 percent. In this paper,
we present a novel task computing framework that can address
the requirements of healthcare systems, such as reliability. In
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294 Views
The terahertz communications band in the 252 to325 GHz range has been recently explored for its potential to meet the stringent requirements for the emerging sixth generation of wireless communications. However, there are several challenges including noise and nonlinearity that hinder efficient implementations. We aim to address this limitation in terahertz communications through convolutional neural networks (CNN) enhanced by the domain knowledge from traditional Volterra filters.
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266 Views
Solar photovoltaic (PV) systems are increasingly recognized as crucial sustainable energy sources with diverse applications. Their implementation leverages rapid advancements in material engineering, communication systems, and computational intelligence tools. This paper focuses on mathematical methods for signal analysis, including multichannel signal processing, optimization methods, and feature evaluation, to monitor PV systems with panels situated in a specific coordinate system.
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57 Views
This paper includes a variety of media location data generated in the paper.According to the wideband near-field signal propagation model, sample data were generated based on four layers of media with known media types. The main differences between simulated data and real data are errors due to electromagnetic dispersion, multipath and noise, which are not currently taken into account because of different electromagnetic characteristics in inhomogeneous media. The setting of condition variables in the experiment was shown in Table I.
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801 Views
Six publicly available datasets are applied to Speech/Music Classification (SMC), Music Genre Classification (MGC), and Environmental Sound Classification (ESC), respectively. The utilized datasets include: 1) For SMC tasks, we employed the GTZAN-SMC and MUSAN datasets. 2) In ESC, the commonly employed ESC-10 and US8K datasets were included. 3) Classic GTZAN and Homburg datasets for MGC.
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208 Views
Moroccan Dialect Emotion Recognition Dataset is a collection of voice records of people speaking Moroccan dialect in 5 states of emotion: Neutral, Happy, Sad, Angry and Fearful. The dataset has been collected in different Moroccan cities in 2024. Each recorder has 5 records per emotion class. The dataset contains 2000 record. The records are saved in .wav format, which is useful for signal processing with python libraries. The dataset is used for signal processing and emotion recognition using deep Learning models.
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366 Views
Measurement campaign was performed across the entire growing season of 2023. Seven Arduino+LoRaWAN sensors were measuring soil moisture, temperature and pH, as well as solar irradiance in the radius of about 35 km around Gdansk, Poland. Raw data were being collected with a nomadic gateway aboard an UAV and transferred to the cloud for analysis (package part A). Based on the physics informed analysis of the underlying measurement processes anomalies were classified and parametrized.
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578 Views
In our work, we propose an innovative system to accurately infer and track occluded target locations using mmWave beat frequency signals. Our approach combines a classic direction-finding method with advanced deep learning techniques, specifically a convolutional neural network (CNN), to enhance detection capabilities. The dataset includes raw beat frequency signal data from the TI IWR6843ISK rev B with TI mmWAVEICBOOST and the TI DCA1000EVM capture board. Corresponding ground truth data (target position) from the Realsense L515 RGB-D camera is also provided.
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348 Views