mlsanityData to 14 Oct 2026

EMDS-7: Environmental Microorganism Image Dataset Seventh Version for Multiple Object Detection Evaluation

arXiv 2110.07723 ↗First posted 11 Oct 2021cs.CVcited by 2

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Abstract (arXiv)

The Environmental Microorganism Image Dataset Seventh Version (EMDS-7) is a microscopic image data set, including the original Environmental Microorganism images (EMs) and the corresponding object labeling files in ".XML" format file. The EMDS-7 data set consists of 41 types of EMs, which has a total of 2365 images and 13216 labeled objects. The EMDS-7 database mainly focuses on the object detection. In order to prove the effectiveness of EMDS-7, we select the most commonly used deep learning methods (Faster-RCNN, YOLOv3, YOLOv4, SSD and RetinaNet) and evaluation indices for testing and evaluation. EMDS-7 is freely published for non-commercial purpose at: https://figshare.com/articles/dataset/EMDS-7_DataSet/16869571

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 19 of its 55 references that are in the map. First posted on arXiv 11 Oct 2021.

Builds on

19 of 55 references.

References · 19

  1. 2015Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networkscited by 9,639
  2. 2016Feature Pyramid Networks for Object Detectioncited by 5,036
  3. 2015You Only Look Once: Unified, Real-Time Object Detectioncited by 4,852
  4. 2015SSD: Single Shot MultiBox Detectorcited by 3,130
  5. 2020YOLOv4: Optimal Speed and Accuracy of Object Detectioncited by 1,630
  6. 2017Focal Loss for Dense Object Detectioncited by 752
  7. 2021A Comprehensive Review of Computer-aided Whole-slide Image Analysis: from Datasets to Feature Extraction, Segmentation, Classification, and Detection Approachescited by 44
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  10. 2021A Comprehensive Review of Image Analysis Methods for Microorganism Counting: From Classical Image Processing to Deep Learning Approachescited by 20
  11. 2021GasHisSDB: A New Gastric Histopathology Image Dataset for Computer Aided Diagnosis of Gastric Cancercited by 17
  12. 2020Gastric histopathology image segmentation using a hierarchical conditional random fieldcited by 16
7 more
  1. 2021Is the aspect ratio of cells important in deep learning? A robust comparison of deep learning methods for multi-scale cytopathology cell image classification: from convolutional neural networks to visual transformerscited by 16
  2. 2021Applications of Artificial Neural Networks in Microorganism Image Analysis: A Comprehensive Review from Conventional Multilayer Perceptron to Popular Convolutional Neural Network and Potential Visual Transformercited by 14
  3. 2021A New Pairwise Deep Learning Feature For Environmental Microorganism Image Analysiscited by 12
  4. 2021A State-of-the-art Survey of Object Detection Techniques in Microorganism Image Analysis: From Classical Methods to Deep Learning Approachescited by 12
  5. 2020A Multi-scale CNN-CRF Framework for Environmental Microorganism Image Segmentationcited by 9
  6. 2021A Comparative Study of Deep Learning Classification Methods on a Small Environmental Microorganism Image Dataset (EMDS-6): from Convolutional Neural Networks to Visual Transformerscited by 9
  7. 2021EMDS-5: Environmental Microorganism Image Dataset Fifth Version for Multiple Image Analysis Taskscited by 7

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Citing papers per year: 2022: 1; 2023: 1.

2 papers.

  1. 2023Simple but Effective Unsupervised Classification for Specified Domain Images: A Case Study on Fungi Imagescited by 1
  2. 2022A State-of-the-art Survey of U-Net in Microscopic Image Analysis: from Simple Usage to Structure Mortificationcited by 0