five

Desert v. Vinegar Flies: Eye Allometry|昆虫学数据集|数据分析数据集

收藏
Mendeley Data2024-01-31 更新2024-06-27 收录
昆虫学
数据分析
下载链接:
https://figshare.com/articles/dataset/Desert_v_Vinegar_Flies_Eye_Allometry/15127797/2
下载链接
链接失效反馈
资源简介:
Instructions needed to generate the statistics and figures used in Eye Allometry results: Make sure Python 3.6+ and the following Python packages are installed (try pip): -matplotlib -numpy -pandas -pickle -scikit-image -scipy -seaborn -statsmodels-eye_tools (from https://github.com/jpcurrea/eye_tools.git) A. Plot figures and calculate important statistics: In the terminal, cd to the downloaded folder and run the following: ~! python3 plot.py Running this script produces the following image files: -eye_composition.png -eye_composition.svg -eye_shape.png -eye_shape.svg -fields_of_view.png -fields_of_view.svg -optical_performance.png -optical_performance.svg We've also already saved the following files: -stats.txt: allometric statistics collated by measurement -stats.csv: allometric statistics used for table B. To generate the allometric data from scratch: 1. unzip image_stacks.zip, creating a folder of the same name 2. run the following: ~! python3 analysis.py Running this script produces the following: -allometry_data.csv: readable measurements dataframe -allometry_data.pkl: pickled measurements dataframe 3. to plot the data, running process A. above. C. To generate Supplemental Figure 2, cd to the downloaded folder and run the following: ~! python3 plot_demo.py
创建时间:
2024-01-31
用户留言
有没有相关的论文或文献参考?
这个数据集是基于什么背景创建的?
数据集的作者是谁?
能帮我联系到这个数据集的作者吗?
这个数据集如何下载?
点击留言
数据主题
具身智能
数据集  4099个
机构  8个
大模型
数据集  439个
机构  10个
无人机
数据集  37个
机构  6个
指令微调
数据集  36个
机构  6个
蛋白质结构
数据集  50个
机构  8个
空间智能
数据集  21个
机构  5个
5,000+
优质数据集
54 个
任务类型
进入经典数据集
热门数据集

MNIST

The MNIST database (Modified National Institute of Standards and Technology database) is a large collection of handwritten digits. It has a training set of 60,000 examples, and a test set of 10,000 examples. It is a subset of a larger NIST Special Database 3 (digits written by employees of the United States Census Bureau) and Special Database 1 (digits written by high school students) which contain monochrome images of handwritten digits. The digits have been size-normalized and centered in a fixed-size image. The original black and white (bilevel) images from NIST were size normalized to fit in a 20x20 pixel box while preserving their aspect ratio. The resulting images contain grey levels as a result of the anti-aliasing technique used by the normalization algorithm. the images were centered in a 28x28 image by computing the center of mass of the pixels, and translating the image so as to position this point at the center of the 28x28 field.

Papers with Code 收录

Simulation of rear wheel steering in a vehicle towing a single axle trailer with variable load distribution

This is the dataset for a publication on the stability of automotive vehicles when towing single axle trailers. The loading of the trailer is critical for stability, if the load distribution is too far back, then the trailer will begin to sway uncontrollably, dictating the track of the vehicle.In this research, small proportional control of the rear wheel steering of a larger towing vehicle is shown to be able to further stabilize the system easily, thus improving the safety margin. This is based on control measurements of the yaw angle, either directly measured or inferred from rear camera / parking sensor measurements.The simulation environment is Simulink and all scripts are included to initialise and plot the results. The work is based on the built in example "Two axle vehicle towing one axle trailer" with modifications to enable control algorithms for rear wheel steering control and variable load distribution. Reference for the original model is available at:T. M. Inc., Vehicle dynamics blockset version: 2.0 (r2023a) (2022). https://www.mathworks.comT. M. Inc., Trailer body 3dof documentation (2020). https://uk.mathworks.com/help/vdynblks/ref/trailerbody3dof.html<br>

DataCite Commons 收录

PCLT20K

PCLT20K数据集是由湖南大学等机构创建的一个大规模PET-CT肺癌肿瘤分割数据集,包含来自605名患者的21,930对PET-CT图像,所有图像都带有高质量的像素级肿瘤区域标注。该数据集旨在促进医学图像分割研究,特别是在PET-CT图像中肺癌肿瘤的分割任务。

arXiv 收录

Photovoltaic power plant data

包括经纬度、电源板模型、NWP等信息。

github 收录

CHBench

CHBench是首个全面的中文健康相关基准,旨在评估大型语言模型在理解各种场景下的身心健康方面的能力。CHBench包括6,493条与心理健康相关的条目和2,999条专注于身体健康相关的条目,涵盖了广泛的主题。

github 收录