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opencc-by-4.0Nov 2019View details →

Correcting Artifacts in Single Molecule Localization Microscopy Analysis Arising from Pixel Quantum Efficiency Differences in sCMOS Cameras

Jupyter notebooks and supplementary data for the paper "Correcting Artifacts in Single Molecule Localization Microscopy Analysis Arising from Pixel Quantum Efficiency Differences in sCMOS Cameras".

opencc-by-4.0Oct 2018View details →

The Plenoptic 2.0 Toolbox: Benchmarking of Depth Estimation Methods for MLA-Based Focused Plenoptic Cameras

Plenoptic 2.0 Images. The Dataset includes both images acquired with different Raytrix Cameras (R29 and R42) and Synthetic Images. The Synthetic Images are quite basic, while real images contain different backgrounds and different challenges for disparity estimation, view synthesis and compression algorithms.

opennotspecifiedAug 2024View details →

Figure 1 in Recording potential predators of herpetofauna in southern Mexico using camera traps and realistic models

Figure 1. Location of the Area de Proteccion y Desarrollo de Ceratozamia (APDC) in south-east Veracruz, Mexico. Black circles show the positions of the 13 camera traps within the study area. Land use layer obtained from Karra et al. (2021) with a resolution of 10 m.

opennotspecifiedAug 2024View details →

Figure 2 in Recording potential predators of herpetofauna in southern Mexico using camera traps and realistic models

Figure 2. Colouration in life of Craugastor loki (a) and Ninia sebae (c) and their respective painted models (b and d) with embedded piece of wire.

opennotspecifiedApr 2024View details →

Figure 1 in First record of albinism in long-nosed mongoose Xenogale naso documented with camera traps in the Yoko Council Forest, Centre Cameroon

Figure 1: Map showing the camera trap stations with mongoose species in the Yoko Council Forest, Cameroon.

Figure 8 in Insights into surveying pangolins using ground and arboreal camera traps

Figure 8: Estimated detection probability with 95 % confidence interval for models run using each combination of cameras for black-bellied pangolins. For example, with 1 camera there are 6 combinations, either only camera 1, 2, 3, 4, 5, or 6. Red X's at 0 represent models that did not have enough detections for model convergence.

Figure 6 in Insights into surveying pangolins using ground and arboreal camera traps

Figure 6: Map showing the location of where black-bellied pangolin were detected during the study. Sites with a black dot were sites where cameras were placed but no black-bellied pangolin were detected, aqua are sites where 1 of the 6 cameras at the site detected the pangolin, and yellow are sites where 3 of the 6 cameras at the site detected pangolin.

Figure 7 in Insights into surveying pangolins using ground and arboreal camera traps

Figure 7: Relationship between the linear (height) effect of camera height (A), the quadratic (height + height2) effect of camera height (B), the linear (zone) effect of camera zone (C), and the quadratic (zone + zone2) effect of camera zone (D) on detection probability for black-bellied pangolin.

opennotspecifiedApr 2024View details →

Figure 2 in First record of albinism in long-nosed mongoose Xenogale naso documented with camera traps in the Yoko Council Forest, Centre Cameroon

Figure 2: The recorded albino long-nosed mongooses in a grassland savannah (a) and in a swamp dominated by raffia palms (b and c) of Yoko Council Forest, Cameroon.

Figure 4 in Insights into surveying pangolins using ground and arboreal camera traps

Figure 4: Relationship between camera zone and detection probability for white-bellied pangolin using the model zone + zone2 on detection probability.

Figure 5 in Insights into surveying pangolins using ground and arboreal camera traps

Figure 5: Estimated detection probability with 95 % confidence interval for models run using each combination of cameras for white-bellied pangolins. For example, with 1 camera there are 6 combinations, either only camera 1, 2, 3, 4, 5, or 6. Red X's at 0 represent models that did not have enough detections for model convergence.

Figure 3 in Insights into surveying pangolins using ground and arboreal camera traps

Figure 3: Map showing white-bellied pangolin detection locations during the study. Black dot are sites where cameras were placed but no white-bellied pangolin were detected,aqua are sites where 1 of the 6 cameras at the site detected the pangolin, and yellow are sites where 3 of the 6 cameras at the site detected pangolin.

Figure 1 in Insights into surveying pangolins using ground and arboreal camera traps

Figure 1: Location of camera trap survey locations for 2022 shown with yellow dots, as well as previous camera trap locations, shown with black dots.The map also shows rivers, roads, as well as the central, buffer, and transition zones of the park.

Figure 2 in Occurrence and temporal activity pattern of Burmese Red Serow (Capricornis rubidus, Bovidae) in Baraiyadhala National Park, Bangladesh: insights from a camera trapping study

Figure 2: Camera trapped photo of Red Serow from the study area. The top image depicts an adult and a juvenile, and the bottom image is of an adult male.

Figure 2 in A treetop diner: camera trapping reveals novel arboreal foraging by fishing cats on colonial nesting birds in Bangladesh

Figure 2: Photo sequence of the arboreal predatory behaviour of the fishing cat captured on camera traps in northeast Bangladesh arranged in a clockwise sequence. (A–F) The first event on 03 August, 2022. (G–L) The second event on 02 October, 2022 (for descriptions see Table 1).

Figure 1 in Occurrence and temporal activity pattern of Burmese Red Serow (Capricornis rubidus, Bovidae) in Baraiyadhala National Park, Bangladesh: insights from a camera trapping study

Figure 1: Study area and camera trap sites, indicating camera trap sites with Burmese Red Serow detection and sites where serows were not detected.

Figure 1 in A treetop diner: camera trapping reveals novel arboreal foraging by fishing cats on colonial nesting birds in Bangladesh

Figure 1: Location of the bird colony where the arboreal predatory behaviour of the fishing cat was captured on camera traps in northeast Bangladesh. (A) Fishing cat range in Bangladesh. (B) Northeast Bangladesh. (C) The Indian Oak/Hijal tree. Red circles denote the placement of the camera traps. The range map in Bangladesh is adapted from Mukherjee et al. (2016).

Figure 4 in Insights into marking behavior of giant anteaters: a camera trap study in the Rupununi savannahs, Guyana

Figure 4: Distribution of marking behaviors in "female with cub," "two adults," and "one adult" social categories, adjusting for survey effort. The Y-axes shows the proportion of marking behaviors recorded per day of camera recording in each month, offering insights into their frequency while accounting for effort variations.

Figure 3 in Insights into marking behavior of giant anteaters: a camera trap study in the Rupununi savannahs, Guyana

Figure 3: Examples of some marking behaviors recorded. Anteater sniffing (A), rubbing (B), climbing (C), and hugging (D) the tree.

Figure 2 in Insights into marking behavior of giant anteaters: a camera trap study in the Rupununi savannahs, Guyana

Figure 2: Histogram showing the number of records for each social category for each behavior identified. (A) Histogram showing number of records for each social category for each behavior identified; with behavior divided into tree marking and non-tree marking behavior. (B) Percentage contribution of each behavior type to the total recorded behaviors within each social category. Note one video can have one or more behaviors recorded.