Computer Vision
In nighttime driving scenes, due to insufficient and uneven lighting, and the scarcity of high-quality datasets, the miss rate of nighttime pedestrian detection (PD) is much higher than that of daytime. Vision-based distance detection (DD) has the advantages of low cost and good interpretability, but the existing methods have low precision, poor robustness, and the DD is mostly performed independently of PD.
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359 Views
Tea chrysanthemums can provide many components that are beneficial to human health. However, the harvesting process is time-consuming and labor-intensive. In the future, tea chrysanthemums harvesting can be done by machines. The first step towards automated harvesting is the detection of tea chrysanthemums, which are highly dependent on the quantity and quality of datasets. In a natural environment, a strain of chrysanthemum can present multiple flower heads in different stages and sizes.
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559 Views
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.
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883 Views
This dataset contains continuous gesture data for both Chinese and English, including 14 Chinese characters and 4 English words. The Chinese characters are: 不 (bù), 程 (chéng), 刀 (dāo), 工 (gōng), 古 (gǔ), 今 (jīn), 力 (lì), 刘 (liú), 木 (mù), 石 (shí), 土 (tǔ), 外 (wài), 中 (zhōng), 乙 (yǐ). The English words included are: 'can', 'NO', 'Who', 'yes'.
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176 Views
Ear biting is a welfare challenge in commercial pig farming. Pigs sustain injuries at the site of bite paving the way for bacterial infections. Early detection and management of this behaviour is important to enhance animal health and welfare, increase productivity whilst minimising inputs from medication. Pig management using physical observation is not practical due to the scale of modern pig production systems. The same applies to the manual analysis of captured videos from pig houses. Therefore, a method of automated detection is desirable.
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356 Views
The deployment of unmanned aerial vehicles (UAV) for logistics and other civil purposes is consistently disrupting airspace security. Consequently, there is a scarcity of robust datasets for the development of real-time systems that can checkmate the incessant deployment of UAVs in carrying out criminal or terrorist activities. VisioDECT is a robust vision-based drone dataset for classifying, detecting, and countering unauthorized drone deployment using visual and electro-optical infra-red detection technologies.
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7403 Views
In this study, we present advances on the development of proactive control for online individual user adaptation in a welfare robot guidance scenario, with the integration of three main modules: navigation control, visual human detection, and temporal error correlation-based neural learning. The proposed control approach can drive a mobile robot to autonomously navigate in relevant indoor environments. At the same time, it can predict human walking speed based on visual information without prior knowledge of personality and preferences (i.e., walking speed).
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232 Views
This paper presents a digital image dataset of historical handwritten birth records stored in the archives of several parishes
across Sweden, together with the corresponding metadata that supports the evaluation of document analysis algorithms’
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113 Views
The Paddy Doctor dataset contains 16,225 labeled paddy leaf images across 13 classes (12 different paddy diseases and healthy leaves). It is the largest expert-annotated visual image dataset to experiment with and benchmark computer vision algorithms. The paddy leaf images were collected from real paddy fields using a high-resolution (1,080 x 1,440 pixels) smartphone camera. The collected images were carefully cleaned and annotated with the help of an agronomist.
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11187 Views