Outputs (15317)

A 50-million-year-old, three-dimensionally preserved bat skull supports an early origin for modern echolocation (2023)
Journal Article
Hand, S. J., Maugoust, J., Beck, R. M., & Orliac, M. J. (2023). A 50-million-year-old, three-dimensionally preserved bat skull supports an early origin for modern echolocation. Current Biology, 33(21), 4624-4640. https://doi.org/10.1016/j.cub.2023.09.043

Bats are among the most recognizable, numerous, and widespread of all mammals. But much of their fossil record is missing, and bat origins remain poorly understood, as do the relationships of early to modern bats. Here, we describe a new early Eocene... Read More about A 50-million-year-old, three-dimensionally preserved bat skull supports an early origin for modern echolocation.

A new deep CNN for 3D text localization in the wild through shadow removal (2023)
Journal Article
Shivakumara, P., Banerjee, A., Nandanwar, L., Pal, U., Antonacopoulos, A., Lu, T., & Blumenstein, M. (2024). A new deep CNN for 3D text localization in the wild through shadow removal. Computer Vision and Image Understanding, 238, https://doi.org/10.1016/j.cviu.2023.103863

Text localization in the wild is challenging due to the presence of 2D and 3D texts, the presence of shadows, arbitrary orientated text with non-linear arrangements, varying lighting conditions as well as complex background. This paper proposes the f... Read More about A new deep CNN for 3D text localization in the wild through shadow removal.

Silica sources for arsenic mitigation in rice: machine learning-based predictive modeling and risk assessment. (2023)
Journal Article

Arsenic (As) is a well-known human carcinogen, and the consumption of rice is the main pathway for the South Asian people. The study evaluated the impact of the amendments involving CaSiO , SiO nanoparticles, silica solubilizing bacteria (SSB), and... Read More about Silica sources for arsenic mitigation in rice: machine learning-based predictive modeling and risk assessment..

Optimizing Inference Distribution for Efficient Kidney Tumor Segmentation Using a UNet-PWP Deep-Learning Model with XAI on CT Scan Images (2023)
Journal Article
Rao, P. K., Chatterjee, S., Janardhan, M., Nagaraju, K., Khan, S. B., Almusharraf, A., & Alharbe, A. I. (in press). Optimizing Inference Distribution for Efficient Kidney Tumor Segmentation Using a UNet-PWP Deep-Learning Model with XAI on CT Scan Images. Diagnostics, 13(20), 3244. https://doi.org/10.3390/diagnostics13203244

Kidney tumors represent a significant medical challenge, characterized by their often-asymptomatic nature and the need for early detection to facilitate timely and effective intervention. Although neural networks have shown great promise in disease p... Read More about Optimizing Inference Distribution for Efficient Kidney Tumor Segmentation Using a UNet-PWP Deep-Learning Model with XAI on CT Scan Images.

What do we know about noise impacts on birds? A systematic review focusing on acoustic methodology (2023)
Presentation / Conference Contribution

In recent years, several studies have shown how anthropogenic noise impacts wildlife. The methodologies used to quantify noise appear to influence data reliability and subsequent findings. Therefore, it is appropriate to review the robustness of acou... Read More about What do we know about noise impacts on birds? A systematic review focusing on acoustic methodology.

Habitats: Developments in managing the ecological impacts of noise on wildlife habitats for sustainable development (2023)
Presentation / Conference Contribution

The Habitats project integrates research in the fields of ecological impacts and environmental noise to facilitate development of management tools and processes needed for sustainable development. This conference paper summarises the content and outc... Read More about Habitats: Developments in managing the ecological impacts of noise on wildlife habitats for sustainable development.

Towards disentangling the classification of freshwater fish trypanosomes (2023)
Journal Article

Currently, new species of freshwater fish trypanosomes, which are economically important parasites, are being described based on subjectively selected features, i.e., their cell morphology and the host species. We have performed detailed phylogenetic... Read More about Towards disentangling the classification of freshwater fish trypanosomes.

Hand Recognition Dataset for Machine Vision Researchers (YOLOv8 Format) (2023)
Data

This hand recognition dataset comprises a comprehensive collection of hand images from 65 individuals, including both left and right hands, annotated with YOLOv8 formatting.

The dataset encompasses 17 distinct classes, denoted as L-L1 to L-L9 for... Read More about Hand Recognition Dataset for Machine Vision Researchers (YOLOv8 Format).

Facial Emotion Recognition Datasets for YOLOv8 Annotation (2023)
Data

Computer Vision Scientist-Collected Dataset:

This facial emotion recognition dataset has been meticulously curated by computer vision scientists using mobile phone cameras to capture candid moments of individuals expressing a spectrum of emotions,... Read More about Facial Emotion Recognition Datasets for YOLOv8 Annotation.

Thorley Lane, Wythenshawe (2023)
Data

Data and results from excavations and post-excavation analysis of archaeological investigations at Thorley Lane, Wythenshawe, including site records, drawings, photographs and technical report.