computer vision
We generated an IV fluid-specific dataset to maximize the accuracy of the measurement. We developed our system as a smartphone application, utilizing the internal camera for the nurses or patients. Thus, users should be able to capture the surface of the fluid in the container by adjusting the smartphone's position or angle to reveal the front view of the container. Thus, we collected the front view of the IV fluid containers when generating the training dataset.
- Categories:
The morphological characteristics of skeletal muscles, such as fascicle orientation, fascicle length, and muscle thickness, contain valuable mechanical information that aids in understanding muscle contractility and excitation due to commands from the central nervous system. Ultrasound (US) imaging, a non-invasive measurement technique, has been employed in clinical research to provide visualized images that capture morphological characteristics. However, accurately and efficiently detecting the fascicle in US images is challenging.
- Categories:
We introduce a high-performance computer vision based Intraveneous (IV) infusion speed measurement system as a camera application on an iPhone or Android phone. Our system uses You Only Look Once version 5 (YOLOv5) as it was designed for real-time object detection, making it substantially faster than two-stage algorithms such as R-CNN. In addition, YOLOv5 offers greater precision than its predecessors, making it more competitive with other object detection methods.
- Categories:
Visual storytelling refers to the manner of describing a set of images rather than a single image, also known as multi-image captioning. Visual Storytelling Task (VST) takes a set of images as input and aims to generate a coherent story relevant to the input images. In this dataset, we bridge the gap and present a new dataset for expressive and coherent story creation. We present the Sequential Storytelling Image Dataset (SSID), consisting of open-source video frames accompanied by story-like annotations.
- Categories:
The Dataset consists of two videos, one recorded with blindfold on and the other without blindfold recorded using a 1080p Intel RealSense depth camera. It contains the videos, images extracted using ffmpeg and processed video which is made of a video with skipped frames created using ffmpeg. The scope of the dataset is for machine vision purposes to allow for tasks such as instance segmentation. A hat fixed on the head of a blindfolded person is used to record walking activities.
- Categories:
This dataset containg 1900+ images divided into fresh oranges and rotten oranges. In an orange packing factory, a video was recorded, by placing the camera parallel and above the oranges conveyor. The video was captured for 10 minutes with a quality of Ultra High Definition (4K) with 60 frames per second and a High Dynamic Range feature. The video was changed from High Dynamic Range to Standard Dynamic Range by the use of Splice - Video Editor & Maker software. The video is inserted to developed algorithm operating video processing on it and creating the frames.
- Categories:
This dataset was collected with the goal of providing researchers with access to a collection of hundreds of images for efficient classification of plant attributes and multi-instance plant localisation and detection. There are two folders, i.e. Side view and Top View.Each folder includes label files and image files in the.jpg format (.txt format). Images of 30 plants grown in 5 hydroponic systems have been collected for 66 days. Thirty plants of three species (Petunia, Pansy and Calendula) were grown in a hydroponic system for the purpose of collecting and analysing images.
- Categories: