Analysis and Comparison of New-Born Calf Standing and Lying Time Based on Deep Learning.

Standing and lying are the fundamental behaviours of quadrupedal animals, and the ratio of their durations is a significant indicator of calf health. In this study, we proposed a computer vision method for non-invasively monitoring of calves' behaviours. Cameras were deployed at four viewpoints to monitor six calves on six consecutive days.

Confluence: A Robust Non-IoU Alternative to Non-Maxima Suppression in Object Detection.

Confluence is a novel non-Intersection over Union (IoU) alternative to Non-Maxima Suppression (NMS) in bounding box post-processing in object detection. It overcomes the inherent limitations of IoU-based NMS variants to provide a more stable, consistent predictor of bounding box clustering by using a normalized Manhattan Distance inspired proximity metric to represent bounding box clustering. Unlike Greedy and Soft NMS, it does not rely solely on classification confidence scores to select optimal bounding boxes, instead selecting the box which is closest to every other box within a given cluster and removing highly confluent neighboring boxes.

Automated location invariant animal detection in camera trap images using publicly available data sources.

A time-consuming challenge faced by camera trap practitioners is the extraction of meaningful data from images to inform ecological management. An increasingly popular solution is automated image classification software. However, most solutions are not sufficiently robust to be deployed on a large scale due to lack of location invariance when transferring models between sites.

U-Infuse: Democratization of Customizable Deep Learning for Object Detection.

Image data is one of the primary sources of ecological data used in biodiversity conservation and management worldwide. However, classifying and interpreting large numbers of images is time and resource expensive, particularly in the context of camera trapping. Deep learning models have been used to achieve this task but are often not suited to specific applications due to their inability to generalise to new environments and inconsistent performance.

Tomographic reconstruction using tilted Laue analyser-based X-ray phase-contrast imaging.

Analyser-based phase-contrast imaging (ABPCI) is a highly sensitive phase-contrast imaging method that produces high-contrast images of weakly absorbing materials. However, it is only sensitive to phase gradient components lying in the diffraction plane of the analyser crystal [i.e.

: A Field-Scouting Software for the Identification of Wildlife in Camera Trap Images.

We present a software tool for the automated identification of animal species from camera trap images is intended to be used by ecologists both in the field and in the office. Users can download a pre-trained model specific to their location of interest and then upload the images from a camera trap to a laptop or workstation will identify animals and other objects (e.g.

Are we getting the full picture? Animal responses to camera traps and implications for predator studies.

Camera trapping is widely used in ecological studies. It is often considered nonintrusive simply because animals are not captured or handled. However, the emission of light and sound from camera traps can be intrusive.

Camera traps can be heard and seen by animals.

Camera traps are electrical instruments that emit sounds and light. In recent decades they have become a tool of choice in wildlife research and monitoring. The variability between camera trap models and the methods used are considerable, and little is known about how animals respond to camera trap emissions.

Classification of breast tissue using a laboratory system for small-angle x-ray scattering (SAXS).

Structural changes in breast tissue at the nanometre scale have been shown to differentiate between tissue types using synchrotron SAXS techniques. Classification of breast tissues using information acquired from a laboratory SAXS camera source could possibly provide a means of adopting SAXS as a viable diagnostic procedure. Tissue samples were obtained from surgical waste from 66 patients and structural components of the tissues were examined between q = 0.

Mapping structural changes in breast tissue disease using x-ray scattering.

Spread of invasive carcinoma throughout breast tissue is believed to occur at supramolecular levels, beyond the range of standard histopathology identification. Small angle x-ray scattering (SAXS) is capable of characterizing the structural properties of collagen and tissue found in the breast at the scale of tens to hundreds of nanometers. Fifty-six patients who were treated with wide-local excision or mastectomy had tissue biopsy samples analyzed at 2 cm intervals along two perpendicular axes over their excised mass, up to 6 cm away from the primary site of the tumor.

Analysis of collagen fibre shape changes in breast cancer.

Second harmonic generation microscopy was performed on both normal and diseased breast tissue. Differences in the collagen fibre shape between normal, benign and malignant breast tissue were compared and quantified using elliptical Fourier analysis. Principal shape analysis of these coefficients provided an understanding of the key differences in collagen fibre shape between the three tissue types.

X-ray scattering for classifying tissue types associated with breast disease.

Collagen types I and III can be characterized at the molecular level (at the tens to hundreds of nanometers scale) using small angle x-ray scattering (SAXS). Although collagen fibril structural parameters at this length scale have shown differences between diseased and nondiseased breast tissues, a comprehensive analysis involving a multitude of features with a large (>50) patient cohort has not previously been investigated. Breast tissue samples were excised from 80 patients presenting with either a breast lump or reduction mammoplasty.

Myelin structure is a key difference in the x-ray scattering signature between meningioma, schwannoma and glioblastoma multiforme.

Small angle x-ray scattering (SAXS) patterns of benign and malignant brain tumour tissue were examined. Independent component analysis was used to find a feature set representing the images collected. A set of coefficients was then used to describe each image, which allowed the use of the statistical technique of flexible discriminant analysis to discover a hidden order in the data set.

Wavelet-based feature extraction applied to small-angle x-ray scattering patterns from breast tissue: a tool for differentiating between tissue types.

This paper reports on the application of wavelet decomposition to small-angle x-ray scattering (SAXS) patterns from human breast tissue produced by a synchrotron source. The pixel intensities of SAXS patterns of normal, benign and malignant tissue types were transformed into wavelet coefficients. Statistical analysis found significant differences between the wavelet coefficients describing the patterns produced by different tissue types.