Computer Vision
This is a PART of the dataset used in our paper titled "Detecting Anomalous Robot Motion in Collaborative Robotic Manufacturing Systems".
- Categories:
45 Views
Recognizing and categorizing banknotes is a crucial task, especially for individuals with visual impairments. It plays a vital role in assisting them with everyday financial transactions, such as making purchases or accessing their workplaces or educational institutions. The primary objectives for creating this dataset were as follows:
- Categories:
326 Views
This dataset contains video-clips of five volunteers developing daily life activities. Each video-clip is recorded with a Far InfraRed (FIR) camera and includes an associated file which contains the three-dimensional and two-dimensional coordinates of the main body joints in each frame of the clip. This way, it is possible to train human pose estimation networks using FIR imagery.
- Categories:
467 Views
To treat visual attention defficiency and train pulmonary function simulataneously, we developed new Virtual reality(VR) system. Proposed VR system is consisted of three VR training games(Rocket game, Candle game and Food game).
We conducted user study on 24 ADHD children and collected Pulmonary function test(PFT), Advanced test of attention(ATA).
In this file, we coded data into the form that can be used SPSS statstic tool.
We wanted to compare date in two ways, pre-post comparision and between-subjects comparision.
- Categories:
50 Views
Fundus Image Myopia Development (FIMD) dataset contains 70 retinal image pairs, in which, there is obvious myopia development between each pair of images. In addition, each pair of retinal images has a large overlap area, and there is no other retinopathy. In order to perform a reliable quantitative evaluation of registration results, we follow the annotation method of Fundus Image Registration (FIRE) dataset [1] to label control points between the pair of retinal images with the help of experienced ophthalmologists. Each image pair is labeled with
- Categories:
395 Views
SYPHAXAR dataset is a dataset for Arabic text detection in the wild. It was collected from Tunisia in “Sfax” city, the second largest Tunisian city after the capital. A total of 3078 images were gathered through manual collection one by one, with each image energizing text detection challenges in nature according to real existing complexity of 15 different routes along with ring roads, intersections and roundabouts. These annotated images consist of more than 31000 objects, each of which is enclosed within a bounding box.
- Categories:
244 Views
It is important to accurately classify the defects in hot rolled steel strip since the detection of defects in hot rolled steel strip is closely related to the quality of the fifinal product. The lack of actual hot-rolled strip defect data sets currently limits further research on the classifification of hot-rolled strip defects to some extent. In real production, the convolutional neural network (CNN)-based algorithm has some diffificulties, for example, the algorithm is not particularly accurate in classifying some uncommon defects.
- Categories:
551 Views
Blade damage inspection without stopping the normal operation of wind turbines has significant economic value. This study proposes an AI-based method AQUADA-Seg to segment the images of blades from complex backgrounds by fusing optical and thermal videos taken from normal operating wind turbines. The method follows an encoder-decoder architecture and uses both optical and thermal videos to overcome the challenges associated with field application.
- Categories:
1103 Views
This dataset provides RGB and Depth images acquired by Kinect v2 of 10 cerebral palsy patients. For each subject (0001, 0002, ecc) there are 12 folders:
- 5 folders containing 5 left full gait cycles (L_01, L_02, ecc)
- 5 folders containing 5 right full gait cycles (R_01, R_02. ecc)
- 1 folder containing one static lateral view (left side) of the subject while standing upright (L_s)
- 1 folder containing one static lateral view (right side) of the subject while standing upright (R_s)
In each folder (dynamic and static) there are two subfolders:
- Categories:
183 Views
We present the RQMD dataset, a comprehensive collection of diverse material samples aimed at advancing computer vision and machine learning algorithms in terrain classification tasks. This dataset contains RGB images of 5 different terrains, such as Asphalt, Brick, Grass, Gravel, and Tiles, captured using an 8-megapixel Raspberry Pi camera from a top-view perspective. Notably, the dataset encompasses images taken at different times of the day, introducing variations in lighting conditions and environmental factors.
- Categories:
487 Views