Image Processing
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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Adhesion property measurements contribute to the comprehensive understanding of the mechanical properties of soft matters. Indentation tests are a common method for measuring adhesion force. However, indenters generally have a large volume and a small sensing angle and thus are not conducive to local detection in high-precision environments.
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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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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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In order to contribute to the development of automatic methods for the detection of bacilli, TBimages is an image dataset composed of two subsets: TbImages_SS1 contains 10 images per field, of different focal depths, and aims to support the definition of autofocus metrics and also the development of extended focus imaging methods to facilitate the detection of bacilli in smear microscopy imaging. TbImages_SS2 aims to support the development of automatic bacilli detection.
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This peach tree disease detection dataset is a multimodal, multi-angle dataset which was constructed for monitoring the growth of peach trees, including stress analysis and prediction. An orchard of peach trees is considered in the area of Thessaly, where 889 peach trees were recorded in a full crop season starting from Jul. 2021 to Sep. 2022. The dataset includes a) aerial / Unmanned Aerial Vehicle (UAV) images, b) ground RGB images/photos, and c) ground multispectral images/photos.
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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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