African manatees (Trichechus senegalensis) are vulnerable, understudied, and difficult to detect. Areas where African manatees are found were acoustically sampled and deep learning techniques were used to develop the first African manatee vocalization detector. A transfer learning approach was used to develop a convolutional neural network (CNN) using a pretrained CNN (GoogLeNet). The network was highly successful, even when applied to recordings collected from a different location. Vocal detections were more common at night and tended to occur within less than 2 min of one another.

Download full-text PDF

Source
http://dx.doi.org/10.1121/10.0016543DOI Listing

Publication Analysis

Top Keywords

transfer learning
8
convolutional neural
8
neural network
8
african manatee
8
trichechus senegalensis
8
african manatees
8
learning convolutional
4
network detect
4
african
4
detect african
4

Similar Publications

Purpose Of Review: There has been an explosion of creative uses of artificial intelligence (AI) in healthcare, with AI being touted as a solution for many problems facing the healthcare system. This review focuses on tools currently available to pediatric urologists, previews up-and-coming technologies, and highlights the latest studies investigating benefits and limitations of AI in practice.

Recent Findings: Imaging-driven AI software and clinical prediction tools are two of the more exciting applications of AI for pediatric urologists.

View Article and Find Full Text PDF

Aim: Rehospitalization of patients with heart failure (HF) incurs high health care costs and increased mortality. Infection-related rehospitalizations in patients with HF occur frequently, and the risk increases with age. This study aimed to identify the factors associated with infection-related rehospitalizations in older patients with HF.

View Article and Find Full Text PDF

ChatGPT and other artificial intelligence (AI) tools can modify nutritional management in clinical settings. These technologies, based on machine learning and deep learning, enable the identification of risks, the proposal of personalized interventions, and the monitoring of patient progress using data extracted from clinical records. ChatGPT excels in areas such as nutritional assessment by calculating caloric needs and suggesting nutrient-rich foods, and in diagnosis, by identifying nutritional issues with technical terminology.

View Article and Find Full Text PDF

Objectives: Given the complexity of temporomandibular joint disorders (TMDs) and their overlapping symptoms with other conditions, an accurate diagnosis necessitates a thorough examination, which can be time-consuming and resource-intensive. Consequently, innovative diagnostic tools are required to increase TMD diagnosis efficiency and precision. Therefore, the purpose of this umbrella review was to examine the existing evidence about the usefulness of artificial intelligence (AI) in TMD diagnosis.

View Article and Find Full Text PDF

Objective 3D virtual models have gained interest in urology, particularly in the context of robotic partial nephrectomy. From these, newly developed "anatomical digital twin models" reproduce both the morphological and anatomical characteristics of the organs, including the texture of the tissues they comprise. The aim of the study was to develop and test the new digital twins in the setting of intraoperative guidance during robotic-assisted partial nephrectomy (RAPN).

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!