Computer Vision
We provide two folders:
(1)The shallow depth of field image data set folder consists of 27 folders from 1 to 27.
In folder 1-27, each folder contains two test images and two word files. Img1 is the shallow depth of field image with the best focusing state taken with a 300 mm long focal lens, and img2 is the overall blurred image.
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The network attacks are increasing both in frequency and intensity with the rapid growth of internet of things (IoT) devices. Recently, denial of service (DoS) and distributed denial of service (DDoS) attacks are reported as the most frequent attacks in IoT networks. The traditional security solutions like firewalls, intrusion detection systems, etc., are unable to detect the complex DoS and DDoS attacks since most of them filter the normal and attack traffic based upon the static predefined rules.
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Liver tumor segmentation.
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Here we present recordings from a new high-throughput instrument to optogenetically manipulate neural activity in moving
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This document describes the details of the BON Egocentric vision dataset. BON denotes the initials of the locations where the dataset was collected; Barcelona (Spain); Oxford (UK); and Nairobi (Kenya). BON comprises first-person video, recorded when subjects were conducting common office activities. The preceding version of this dataset, FPV-O dataset has fewersubjects for only a single location (Barcelona). To develop a location agnostic framework, data from multiple locations and/or office settings is essential.
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To address the problem of online automatic inspection of drug liquid bottles in production line, an implantable visual inspection system is designed and the ensemble learning algorithm for detection is proposed based on multi-features fusion. A tunnel structure is designed for visual inspection system, which allows the bottles inspection to be automated without changing original processes and devices. A high precision method is proposed for vision detection of drug liquid bottles.
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Dataset asscociated with a paper in 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems
"Talk the talk and walk the walk: Dialogue-driven navigation in unknown indoor environments"
If you use this code or data, please cite the above paper.
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We present here an annotated thermal dataset which is linked to the dataset present in https://ieee-dataport.org/open-access/thermal-visual-paired-dataset
To our knowledge, this is the only public dataset at present, which has multi class annotation on thermal images, comprised of 5 different classes.
This database was hand annotated over a period of 130 work hours.
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This dataset contains satellite images of areas of interest surrounding 30 different European airports. It also provides ground-truth annotations of flying airplanes in part of those images to support future research involving flying airplane detection. This dataset is part of the work entitled "Measuring economic activity from space: a case study using flying airplanes and COVID-19" published by the IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. It contains modified Sentinel-2 data processed by Euro Data Cube.
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The region-based segmentation approach has been a major research area for many medical image applications. A vision guided autonomous system has used region-based segmentation information to operate heavy machinery and locomotive machines intended for computer vision applications. The dataset contains raw images in .png format fro brain tumor in various portions of brain.The dataset can be used fro training and testing. Images are calssified into three main regions as frontal lobe(level -1, level-2), optus-lobe(level-1), medula_lobe(level-1,level-2,level-3).
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