Fecal microscopic data set is a set of fecal microscopic images, which is used in object detection task. The datasets are collected from the Sixth People’s Hospital of Chengdu (Sichuan Province, China). The samples were went flow diluted, stirred and placed, and imaged with a microscopic imaging system. The clearest 5 images were collected for each view of each sample with Tenengrad definition algorithm. The dataset we collected includes 10670 groups of views with 53350 jpg images. The Resolution of images are 1200×1600. There are 4 categories, RBCs, WBCs, Molds, and Pyocytes.

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This dataset consists of the training and the evaluation datasets for the LiDAR-based maritime environment perception presented in our journal publication "Maritime Environment Perception based on Deep Learning." Within the datasets, LiDAR raw data are processed using Deep Neural Networks (DNN). In the training dataset, we introduce the method for generating training data in Gazebo simulation. In the evaluation datasets, we provide the real-world tests conducted by two research vessels, respectively.

 

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358 Views

MI3

Surveillance video captured by Multi-intensity infrared illuminator.

GT(ground-truths) :bounding boxes of 'person' in channel 2,4 and 6 by following the Pascal VOC format.

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351 Views

The accompanying dataset for the CVSports 2021 paper: DeepDarts: Modeling Keypoints as Objects for Automatic Scoring in Darts using a Single Camera

Paper Abstract:

Instructions: 

The recommended way to load the labels is to use the pandas Python package:

import pandas as pd

labels = pd.read_pickle("labels.pkl")

See github repository for more information: https://github.com/wmcnally/deep-darts

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1225 Views

The dataset consists of 751 videos, each containing the performance one of the handball actions out of 7 categories (passing, shooting, jump-shot, dribbling, running, crossing, defence). The videos were manually extracted from longer videos recorded in handball practice sessions. 

Instructions: 

The directory scenes/ contains the videos in mp4 format with actions of interest performed in context of other players present in the scene. The files are arranged in subdirectories according to the action class of the action of interest. The directory actions/ contains the videos of performances of actions by single players isolated from the videos in scenes directory. The files are arranged in subdirectories according to the performed action class. Files are named so that the beginning of the name matches the original video from which the action is extracted. The directory player_detections/ contains the object detections for each frame in the videos.

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383 Views

SDU-Haier-AQD (Shandong University-Haier-Appearance Quality Detection) is an image dataset jointly constructed by Shandong University and Haier, which contains a various of air conditioner external unit image collected during actual detection process.The  Appearance Quality Detection (AQD) dataset is consisted of 10449 images, and the samples in the dataset are collected on the actual industrial production line of air conditioner.

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252 Views

For the task of detecting casualties and persons in search and rescue scenarios in drone images and videos, our database called SARD was built. The actors in the footage have simulate exhausted and injured persons as well as "classic" types of movement of people in nature, such as running, walking, standing, sitting, or lying down. Since different types of terrain and backgrounds determine possible events and scenarios in captured images and videos, the shots include persons on macadam roads, in quarries, low and high grass, forest shade, and the like.

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2304 Views

Networked detector systems can be deployed in urban environments to aid in the detection and localization of radiological and/or nuclear material. However, effectively responding to and interpreting a radiological alarm using spec- troscopic data alone may be hampered by a lack of situational awareness, particularly in complex environments.

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172 Views

Basil/Tulsi Plant is harvested in India because of some spiritual facts behind this plant,this plant is used for essential oil and pharmaceutical purpose. There are two types of Basil plants cultivated in India as Krushna Tulsi/Black Tulsi and Ram Tulsi/Green Tulsi.

Many of the investigator working on disease detection in Basil leaves where the following diseases occur

 1) Gray Mold

2) Basal Root Rot, Damping Off

 3) Fusarium Wilt and Crown Rot

Instructions: 

Basil/Tulsi Plant is harvested in India because of some spiritual facts behind this plant,this plant is used for essential oil and pharmaceutical purpose. There are two types of Basil plants cultivated in India as Krushna Tulsi/Black Tulsi and Ram Tulsi/Green Tulsi.

Many of the investigator working on disease detection in Basil leaves where the following diseases occur

 1) Gray Mold

2) Basal Root Rot, Damping Off

 3) Fusarium Wilt and Crown Rot

4) Leaf Spot

5) Downy Mildew

The Quality parameters (Healthy/Diseased) and also classification based on the texture and color of leaves. For the object detection purpose researcher using an algorithm like Yolo,  TensorFlow, OpenCV, deep learning, CNN

I had collected a dataset from the region Amravati, Pune, Nagpur Maharashtra state the format of the images is in .jpg.

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2615 Views

BTH Trucks in Aerial Images Dataset contains videos of 17 flights across two industrial harbors' parking spaces over two years.

Instructions: 

If you use these provided data in a publication or a scientific paper, please cite the dataset accordingly.

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940 Views

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