Since there is no image-based personality dataset, we used the ChaLearn dataset for creating a new dataset that met the characteristics we required for this work, i.e., selfie images where only one person appears and his face is visible, labeled with the person's apparent personality in the photo.

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Portrait Personality dataset of selfies based on the ChaLearn dataset First Impressions. This dataset consists of 30,935 selfies labeled with apparent personality. Each selfie file was named with the prefix of the original video followed by the frame's number. "bigfive_labels.csv" contains the labels for each trait of the Big Five model, using the prefix (name of the original video). Video frames and models are available at https://github.com/miguelmore/personality.

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927 Views

the measurement data  simulated data of Hd-TCP and its comparisons' performance on the real high-speed railways scenario

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191 Views

These datasets are used to detect Intrusions in Controller Area Network (CAN) bus. Intrusions are detected using various Machine Learning and Deep Learning algorithms.

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670 Views

monitoring, processing and prediction data

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192 Views

ArPC is an Arabic paraphrase identification corpus. It consists of 1331 sentence pairs along with their binary score that indicates weather the pairs are paraphrase or not. The corpus has been manually annotated by three Arabic native speakers.

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119 Views

The PMMW real-time imager, SAIR-U, is developed by Microwave Laboratory of Beihang University, China.It could be (or has been) used in non-contact, non-cooperative (i.e. no need for a fixed posture) security, especially in the environment of large passenger flow. This is the dataset used in the experiment in paper"Real-time Concealed Object Detection from Passive Millimeter Wave Images Based on YOLOv3 Algorithm"

Instructions: 

This is a dataset about Passive Millimeter Wave(PMMW) data. It includes 1624 *2 files, divided into two parts, the original images and the annotation data. The relative system parameters are as following:

(a) The working band is Ka band, at 34Ghz.

(b) The imaging field of view is designed to be 40°×22°.

(c) The minimum imaging distance of the system is set according to the imaging field of view, and the imaging distance range is set to 2.5~5m.

(d) The spatial resolution of the design is determined to be centimeter, considering the application requirements, cost, hardware facilities, and the size of the contraband that the human body may carry. In the case of ensuring the number of system channels, the resolution of the human body at a distance of 3 meters from the system is about 6 to 7 cm.

(e) The sensitivity to temperature is 1~2K.

 

Provided in the experiments in the paper“Real-time Concealed Object Detection from Passive Millimeter Wave Images Based on YOLOv3 Algorithm”.

 

2019-12-19

 

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84 Views

The PMMW real-time imager, SAIR-U, is developed by Microwave Laboratory of Beihang University, China.It could be (or has been) used in non-contact, non-cooperative (i.e. no need for a fixed posture) security, especially in the environment of large passenger flow. This is the dataset used in the experiment in paper"Real-time Concealed Object Detection from Passive Millimeter Wave Images Based on YOLOv3 Algorithm"

Instructions: 

This is a dataset about Passive Millimeter Wave(PMMW) data. It includes 1624 *2 files, divided into two parts, the original images and the annotation data. The relative system parameters are as following:

(a) The working band is Ka band, at 34Ghz.

(b) The imaging field of view is designed to be 40°×22°.

(c) The minimum imaging distance of the system is set according to the imaging field of view, and the imaging distance range is set to 2.5~5m.

(d) The spatial resolution of the design is determined to be centimeter, considering the application requirements, cost, hardware facilities, and the size of the contraband that the human body may carry. In the case of ensuring the number of system channels, the resolution of the human body at a distance of 3 meters from the system is about 6 to 7 cm.

(e) The sensitivity to temperature is 1~2K.

 

Provided in the experiments in the paper“Real-time Concealed Object Detection from Passive Millimeter Wave Images Based on YOLOv3 Algorithm”.

 

2019-12-19

 

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55 Views

The dataset corresponds to the variables that affect the process of passing the sheet between rodsizer and the spooner section for a paper machine.

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279 Views

Research on damage detection of road surfaces has been an active area of research, but most studies have focused so far on the detection of the presence of damages. However, in real-world scenarios, road managers need to clearly understand the type of damage and its extent in order to take effective action in advance or to allocate the necessary resources. Moreover, currently there are few uniform and openly available road damage datasets, leading to a lack of a common benchmark for road damage detection.

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1644 Views

The 2020 Data Fusion Contest, organized by the Image Analysis and Data Fusion Technical Committee (IADF TC) of the IEEE Geoscience and Remote Sensing Society (GRSS) and the Technical University of Munich, aims to promote research in large-scale land cover mapping based on weakly supervised learning from globally available multimodal satellite data. The task is to train a machine learning model for global land cover mapping based on weakly annotated samples.

Last Updated On: 
Mon, 01/25/2021 - 09:03

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