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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 7 in Use of open-source object detection algorithms to detect Palmer amaranth (Amoronthus polmeri) in soybean

Figure 7. Image annotation of soybean at the R2 growth stage. As soybean populations were much higher than Amoronthus polmeri populations, there was a high level of soybean overlap. Therefore, it was necessary to include multiple soybean plants in each image. However, A. polmeri plants typically did not have as much overlap, and in most cases, it was much easier to identify and label individual plants.

Figure 3 in Use of open-source object detection algorithms to detect Palmer amaranth (Amoronthus polmeri) in soybean

Figure 3. Intersection over union (IoU) equation, defined as the overlap between the ground truth annotation and the computer prediction bounding box, divided by the total area of the two bounding boxes.IoU overlaps greater than 0.5 were considered true-positive predictions,whereas overlaps less than 0.5 were considered false-positive predictions.

Figure 2 in Use of open-source object detection algorithms to detect Palmer amaranth (Amoronthus polmeri) in soybean

Figure 2. Illustration of the annotation process. Amoronthus polmeri and soybean plants are labeled in this figure with orange and white boxes, respectively. Bounding boxes overlap with neighboring bounding boxes when plant features are irregular. In cases where a single bounding box could not encompass a plant without including a plant of another species, multiple irregular bounding boxes were drawn on a single specimen.

Figure 4 in Use of open-source object detection algorithms to detect Palmer amaranth (Amoronthus polmeri) in soybean

Figure 4. Mean average precision (mAP) results of each model after training. YOLOv5 was considered the best-performing algorithm of each tested model with a mAP of 0.77.

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.

Figure 5 in Use of open-source object detection algorithms to detect Palmer amaranth (Amoronthus polmeri) in soybean

Figure 5. Change in mean average precision (mAP) @ 0.5 over each epoch during training. mAP was reported after the completion of each epoch. Training was terminated after visual inspection of curve and when mAP @ 0.5 curve was seen to "plateau."

Figure 2 in Detection of the Trp-2027-Cys Mutation in Fluazifop-P-butyl-resistant Itchgrass (RottboelliO cochinchinensis) using High-Resolution Melting Analysis (HRMA)

Figure 2. Agarose gel (1,8%) showing polymerase chain reaction products (89 bp) of the chloroplastic acetyl-coenzyme A carboxylase gene carboxyl-transferase domain targeted by HRMA primers RottF and RottR.

Figure 5 in Detection of the Trp-2027-Cys Mutation in Fluazifop-P-butyl-resistant Itchgrass (RottboelliO cochinchinensis) using High-Resolution Melting Analysis (HRMA)

Figure 5. High-resolution melting analysis (HRMA) for detection of the Trp-2027-Cys mutation in Rottboellia cochinchinensis carboxyl-transferase domain of the acetylcoenzyme A carboxylase gene conferring resistance to fluazifop-P-butyl. (B) Normalized plot and (C) difference plot using susceptible (wild type) as the reference genotype.

Figure 4 in Detection of the Trp-2027-Cys Mutation in Fluazifop-P-butyl-resistant Itchgrass (RottboelliO cochinchinensis) using High-Resolution Melting Analysis (HRMA)

Figure 4. High-resolution melting analysis (HRMA) for detection of mutation Trp-2027-Cys in Rottboellia cochinchinensis carboxyl-transferase domain of the acetyl-coenzyme A carboxylase gene conferring resistance to fluazifop-P-butyl. Three genotypes are included: wild type (homozygous TGG, susceptible), mutant homozygous (TGC, resistant), and artificial mutant heterozygous (TGG/TGC, possibly resistant). (A) Representative profiles of the melting curves (derivative melt curves), (B) normalized plot, and (C) difference plot using susceptible (wild type) as the reference genotype.

opencc-by-4.0Jul 2021View details →

Fig. 3 in Molecular detection of Wolbachia endosymbiont in reptiles and their ectoparasites

Fig. 3 Phylogenetic relationship of Wolbachia detected in this study (in bold) and other available from GenBank belonging to different supergroups based on a partial sequence of the 16S rRNA gene. Evolutionary analysis was conducted on 1000 bootstrap replications using Maximum Likelihood method and Kimura 2-parameter model with discrete Gamma distribution (+ G) to model evolutionary rate differences among sites selected by best-fit model. GenBank accession number and host species are indicated

opencc-by-4.0Jan 2019View details →

Fig. 1 in Molecular detection of Angiostrongylus vasorum in gastropods in Surrey, UK

Fig. 1 Neighbour joining tree based on cytochrome oxidase I (COI) sequences representing all clades of the Agriolimacidae family. Values next to branches indicate percentage bootstrap support. The asterisk (*) indicates the Agriolimacidae specimen collected in this study

opencc-by-4.0May 2024View details →

Chang'e 5 Landing Camera Crater Detection Dataset

132 hand-labelled images from the Chang'e 5 Landing Camera. Visible impact craters in each image have their crater rim inscribed by a bounding ellipse. On average, there are approximately 50 labelled craters per image. The first 100 images of the landers descent were labelled - this is the intended training set. Every 10 images of the remaining 313 were then labelled - this is the intended testing set.   File Descriptions: CE5-ellipse-labels: joblib dump of ellipse parameters per image. change5-*.json: Raw labels as produced by the labelling software of choice, Label Studio.   Images: The images used in this work were produced and processed by the Ground Research and Application System (GRAS) of China's Lunar and Planetary Exploration Program (https://moon.bao.ac.cn). Specifically, the first 413 images from the Chang'e 5 landing camera level 2A were used. The images can be downloaded from here: <a href="https://moon.bao.ac.cn/ce5web/searchOrder_hyperSearchData.search?pid=CE5/LCAM/level/2A" target="_blank" rel="noopener">https://dx.doi.org/10.12350/CLPDS.GRAS.CE5.LCAM-2A.vA</a>.   Reference and Acknowledgement: Users of these annotations and associated data are requested to cite both the original dataset source (https://moon.bao.ac.cn) and the following paper: Matthew Rodda, Sofia McLeod, Ky Cuong Pham, and Tat-Jun Chin. (2024). Camera-Pose Robust Crater Detection from Chang'e 5. doi: https://doi.org/10.48550/arXiv.2406.04569   BibTeX: <pre><code>@misc{rodda2024camerapose, title={Camera-Pose Robust Crater Detection from Chang'e 5}, author={Matthew Rodda and Sofia McLeod and Ky Cuong Pham and Tat-Jun Chin}, year={2024}, eprint={2406.04569}, archivePrefix={arXiv}, primaryClass={cs.CV} }</code></pre>

opencc-by-4.0Aug 2023View details →

Fig. 1 in Detection of Escherichia fergusonii - an emerging pathogen harbouring drug resistant genes from seafood samples of Tamil Nadu, India

Fig. 1 — Gene specific PCR amplification of Escherichia fergusonii (lane 1 – 100 bp DNA ladder, lane 2 – positive control (clinical E. fergusonii), lane 3 – negative control, lane 4 – E011, lane 5 – E060)

opencc-by-4.0Feb 2024View details →

Figure 2 in Assessing grass carp (Ctenopharyngodon idella) occupancy and detection probability within Lake Erie from environmental DNA

Figure 2. Mean posterior estimates of the probability of capturing grass carp eDNA from a site in a sample among sites (θ) from the model with the lowest WAIC score [ψ(Site)Θ(Site)p(.)]. Error bars represent 95% credible intervals. DR = Detroit River, HP = Hot Ponds, MB = Maumee Bay. All sites are located in western Lake Erie.

opencc-by-4.0Feb 2024View details →

Figure 1 in Assessing grass carp (Ctenopharyngodon idella) occupancy and detection probability within Lake Erie from environmental DNA

Figure 1. Map denoting all monthly grass carp eDNA sampling events in 2018 (A–C) and 2019 (D–F) aggregated at each sampling location (Hot Ponds, Detroit River, and North Maumee Bay) and acoustic receiver locations (grey circles) in the western basin of Lake Erie. Positive and negative eDNA detections, defined as at least one positive qPCR detection on one replicate among all markers (GCTM10, GCTM22, GCTM32) are denoted by orange crosses and pink triangles, respectively. The 3 grass carp captured from conventional gear (total sampling events = 451) in the Detroit River (October 2018), Hot Pond (July 2019) and North Maumee Bay (July 2019) are denoted by a yellow hexagon.

opencc-by-4.0Dec 2022View details →

Figure 1 in Early detection of alien fern species through the consultation of horticultural catalogues

Figure 1. Prevalence of different (a, c) scales and (b, d) modes of trade expressed as proportions of the total number of traders and total number of species recorded per trade country. Treatment of species that were traded both on-ground and via e-commerce is detailed in the methods. Countries of trade: Canada (CA), United States of America (US), the United Kingdom and the Republic of Ireland (UKI), South Africa (ZA), Australia (AU), New Zealand (NZ).

Figure 1 in Detection of the Trp-2027-Cys Mutation in Fluazifop-P-butyl-resistant Itchgrass (RottboelliO cochinchinensis) using High-Resolution Melting Analysis (HRMA)

Figure 1. Sequence alignment showing the single-nucleotide change (G/C) within the chloroplastic acetyl-coenzyme A carboxylase gene carboxyl-transferase domain fragments from Rottboellia cochinchinensis susceptible (G) and resistant (C) biotypes. The sequences of the HRMA primers are colored in red. Position numbers (Alopecurus myosuroides full ACCase sequence, GenBank AJ310767, numbering) are given above the nucleotide sequences. Conserved nucleotides are indicated by dots.