Machine Learning

More than 85% of traffic utilization via mobile phones are consumed in the urban area, and most of the traffic is used for downloading. Improving the throughput in LTE for 1 user equipment (UE) in cities is an urgent problem. The collected data is intended to study a dependence of the KPI mobile base station and neighboring from installation extra technology. This study will support the development of methods for comparing traffic utilization of urban area and carry out recommendations for the Channel Quality Indicator (CQI) increases.

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Deep video representation learning has recently attained state-of-the-art performance in video action recognition. However, when used with video clips from varied perspectives, the performance of these models degrades significantly. Existing VAR models frequently simultaneously contain both view information and action attributes, making it difficult to learn a view-invariant representation.

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97 Views

The provided dataset is created is created by using European Commission Rapid Alert System's data for Salmonella cases. The dataset composed by 5 variables and all data is providet in categorical format. it is possible to use the dataset predict the salmonella cases based on type of food, month, country and warmth.

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76 Views

The detection and recognition of road traffic signs and panel guide content has become challenging in recent years. Few studies have been made to solve these two issues at the same time, especially in the Arabic language. Additionally, the limited number of datasets for traffic signs and panel guide content makes the investigation more interesting. the Tunisian research groups in intelligent machines of the University of Sfax (REGIM laboratory of Sfax) will provide the NaSTSArLaT dataset free to researchers in traffic detection signs and traffic road scene text detection.

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130 Views

This is the dataset we collected for the article "Scalable Undersized Dataset RF Classification: Using Convolutional Multistage Training". 17 objects were collected in the laboratory and scanned using a 'cw radar' setup featuring 2x UWB antennas (1 transmit antenna, 1 receive antenna), inside anechoic chamber. There was no clutter added in the experiment.

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181 Views

This dataset includes real-world Channel Quality Indicator (CQI) values from UEs connected to real commercial networks in Greece. In total, we collected CQI data from 74 cars that drive through a specific road in the city of Volos, Greece. This dataset is part of our following work:

 

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386 Views

This cherry tree disease detection dataset is a multimodal, multi-angle dataset which was constructed for monitoring the growth of cherry trees, including stress analysis and prediction. An orchard of cherry trees is considered in the area of Western Macedonia, where 577 cherry trees were recorded in a full crop season starting from Jul. 2021 to Jul. 2022. The dataset includes a) aerial / Unmanned Aerial Vehicle (UAV) images, b) ground RGB images/photos, and c) ground multispectral images/photos.

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571 Views

Mental health greatly affects the quality of life. The ability to detect and classify multiple levels of stress is therefore imperative. The aim of this work is to develop machine learning models for detection and multiple level classification of stress through ECG and EEG signals for both unspecified and specified genders. The models for the detection of stress from ECG are developed for real-world use, while the models based on ECG and EEG for the detection and multiple level classification of stress are devised towards clinical use.

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300 Views

This dataset contains 10,532 issues extracted from Github and Sourceforge. The dataset is for generating linguistic patterns to identify concurrency bug reports automatically.

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31 Views

The cold start problem is a significant challenge in recommendation systems. Traditional methods are ineffective when the amount of interaction data is small. Further, as meta-learning has achieved increasingly remarkablesuccess in few-shot classification, some studies in recent years has abstracted cold-start recommendations into few-shot problems and applied meta-learning-based approaches, but mostly, simple transplants of generic approaches have been adopted.

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