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13
datasets available to search
ShareScore release 0.9.0
Dataset results
13 results for “YOLOv5”
Animal Recognition Using Methods Of Fine-Grained Visual Analysis - YOLOv5 Object Detection Dataset (Oxford-IIIT Pet)
<p>Preprocessed dataset for Oxford-IIIT Pet in YOLOv5 format.. Ground truth labels for head bounding boxes, body bounding boxes (derived from segmentation mask).</p>
Animal Recognition Using Methods Of Fine-Grained Visual Analysis - YOLOv5 Breed Classification Dataset (Oxford-IIIT Pet)
<p>Oxford-IIIT Pet Dataset with ground truth labels for breeds (from https://public.roboflow.com/object-detection/oxford-pets).</p>
Animal Recognition Using Methods Of Fine-Grained Visual Analysis - YOLOv5 Object Detection Dataset (Tsinghua Dogs)
<p>Preprocessed dataset for Tsinghua Dogs in YOLOv5 format.. Ground truth labels for head bounding boxes, body bounding boxes</p>
Figure 8. F1 scores for YOLOv5 in Use of open-source object detection algorithms to detect Palmer amaranth (Amoronthus polmeri) in soybean
Figure 8. F1 scores for YOLOv5 indicating the harmonic mean between precision and recall scores. Data indicated that detection results for both species would be best at a confidence threshold of 0.298.
Figure 11. YOLOv5 in Use of open-source object detection algorithms to detect Palmer amaranth (Amoronthus polmeri) in soybean
Figure 11. YOLOv5 precision (A), recall (B), and F1 score (C) changes as a function of Amoronthus polmeri density (plants m−2).
Figure 10. Detection results for YOLOv5 with a in Use of open-source object detection algorithms to detect Palmer amaranth (Amoronthus polmeri) in soybean
Figure 10. Detection results for YOLOv5 with a confidence interval of 0.15. False-positive detections of Mollugo verticillata and Abutilon theophrasti as Amoronthus polmeri are denoted by arrows pointing from "A" and "B," respectively.
Figure 9. YOLOv5 in Use of open-source object detection algorithms to detect Palmer amaranth (Amoronthus polmeri) in soybean
Figure 9. YOLOv5 detection results for Amoronthus polmeri and soybean using confidence thresholds of 0.15 (A) and 0.70 (B). The likelihood of false-negative (FN) detections increases as confidence thresholds increase, as can be seen in B. Objects assigned a confidence interval of less than 0.70 are not detected in B. FN A. palmeri and soybean detections in B are indicated by the orange and white arrows, respectively.
Figure 6. Precision–recall curve for YOLOv5. Amoronthus polmeri achieved a in Use of open-source object detection algorithms to detect Palmer amaranth (Amoronthus polmeri) in soybean
Figure 6. Precision–recall curve for YOLOv5. Amoronthus polmeri achieved a slightly higher average precision (AP) (0.788) than soybean. Solid blue line represents mean average precision (mAP) computed on the test data set. The AP for each class and the mAP for the overall algorithm were representative of the area of the graph under each respective curve.
A method for designated target anti-interference tracking combining YOLOv5 and SiamRPN for UAV tracking and landing control
<p>The <strong>experiment data</strong> includes the experimental results of each part of Chapter 3 of the article. The <strong>simulation code</strong> is used to implement the simulation experiments in Chapter 3.</p>
Animal Recognition Using Methods Of Fine-Grained Visual Analysis - YOLOv5 Breed Classification Dataset (Tsinghua Dogs)
<p>Tsinghua Dogs Dataset with ground truth labels for breeds in YOLOv5 format.</p>
yolokamon v1.0 A Yolov5 Japanese Kamon detection Model
<p>A Yolov5 Japanese Kamon detection Model.</p>
Agrari Training Dataset YOLOv5
<p>This is a repository that contains Agrari dataset for detection model building</p>
Image Dataset and Trained Detection Models (based on YOLOv5 and EfficientNet) of Mangrove Crabs of China
<p>A manually annotated image dataset of crabs collected from 16 mangrove forests in China, and a set of trained detection models based on YOLOv5 and EfficientNet. We provide a simple UI that is designed by us, please cite it if helpful.</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.