A5037232795- Animal Vocal Communication and Behavior
- Cutaneous Melanoma Detection and Management
- Underwater Acoustics Research
- Marine animal studies overview
- Nonmelanoma Skin Cancer Studies
- AI in cancer detection
- Vehicle License Plate Recognition
- Environmental DNA in Biodiversity Studies
- Lepidoptera: Biology and Taxonomy
- Handwritten Text Recognition Techniques
- Advanced Image and Video Retrieval Techniques
- Species Distribution and Climate Change
- Noise Effects and Management
- Image and Object Detection Techniques
- Aquatic Ecosystems and Phytoplankton Dynamics
- Microbial Community Ecology and Physiology
- Cell Image Analysis Techniques
- Ecology and biodiversity studies
- Freshwater macroinvertebrate diversity and ecology
- COVID-19 and healthcare impacts
- Identification and Quantification in Food
- Advanced Neural Network Applications
- Skin Protection and Aging
- Hydrology and Sediment Transport Processes
- Amphibian and Reptile Biology
Instituto Pirenaico de Ecología
2024-2025
University of Bristol
2012-2024
DePaul University
2024
Hospital Israelita Albert Einstein
2024
Stanford University
2024
University of Lübeck
2024
Barnet and Chase Farm NHS Hospitals Trust
2024
Royal Free London NHS Foundation Trust
2024
Universidad Nacional Autónoma de México
2024
Chase Farm Hospital
2024
This paper proposes a novel system for the automatic detection and recognition of traffic signs. The proposed detects candidate regions as maximally stable extremal (MSERs), which offers robustness to variations in lighting conditions. Recognition is based on cascade support vector machine (SVM) classifiers that were trained using histogram oriented gradient (HOG) features. training data are generated from synthetic template images freely available an online database; thus, real footage road...
A high proportion of suspicious pigmented skin lesions referred for investigation are benign. Techniques to improve the accuracy melanoma diagnoses throughout patient pathway needed reduce pressure on secondary care and pathology services.To determine an artificial intelligence algorithm in identifying dermoscopic images taken with smartphone digital single-lens reflex (DSLR) cameras.This prospective, multicenter, single-arm, masked diagnostic trial took place dermatology plastic surgery...
We propose a novel system for the automatic detection and recognition of text in traffic signs. Scene structure is used to define search regions within image, which sign candidates are then found. Maximally stable extremal (MSERs) hue, saturation, value color thresholding locate large number candidates, reduced by applying constraints based on temporal structural information. A stage interprets contained detected candidate regions. Individual characters as MSERs grouped into lines, before...
Abstract The urgency for remote, reliable, and scalable biodiversity monitoring amidst mounting human pressures on climate ecosystems has sparked worldwide interest in Passive Acoustic Monitoring (PAM), but there been no comprehensive overview of its coverage across realms. We present metadata from 358 datasets recorded since 1991 above land water constituting the first global synthesis sampling spatial, temporal, ecological scales. compiled summary statistics (sampling locations, deployment...
Background: Malignant melanoma can most successfully be cured when diagnosed at an early stage in the natural history. However, there is controversy over screening programs and many advocate only for high-risk individuals.
 Objectives: This study aimed to evaluate accuracy of artificial intelligence neural network (Deep Ensemble Recognition Melanoma [DERM]) identify malignant from dermoscopic images pigmented skin lesions show how this compared doctors’ performance assessed by...
Introduction Deep Ensemble for Recognition of Malignancy (DERM) is an artificial intelligence as a medical device (AIaMD) tool skin lesion assessment. Methods We report prospective real-world performance from its deployment within cancer pathways at two National Health Service hospitals (UK) between July 2021 and October 2022. Results A total 14,500 cases were seen, including patients 18–100 years old with Fitzpatrick types I–VI represented. Based on 8,571 lesions assessed by DERM confirmed...
Abstract Long‐term biodiversity monitoring is needed to track progress towards ambitious global targets reduce species loss and restore ecosystems. The recent development of cheap robust acoustic recording devices offers a cost‐effective means gathering standardised long‐term datasets. Accounting for sources bias in ecological research fundamental part the study design process. To highlight this issue context terrestrial ecoacoustic monitoring, here we collate discuss arising from (i)...
Aquatic insects are a major indicator used to assess ecological condition in freshwater environments. However, current methods collect and identify aquatic require advanced taxonomic expertise rely on invasive techniques that lack spatio-temporal replication. Passive acoustic monitoring (PAM) is emerging as non-invasive complementary sampling method allowing broad coverage. The application of PAM ecosystems has already proved useful, revealing unexpected diversity produced by fishes,...
Abstract Conventional methodologies used to estimate biodiversity in freshwater ecosystems can be nonselective and invasive, sometimes leading capture potential injury of vulnerable species. Therefore, interest noninvasive surveying techniques is growing among ecologists. Passive acoustic monitoring, the recording environmental sounds, has been shown effectively survey biota terrestrial marine ecosystems. However, knowledge sounds produced by species relatively scarce. Furthermore, little...
Abstract Ecoacoustics is increasingly being used to monitor species populations and estimate biodiversity in marine ecosystems, but the underwater soundscapes of freshwater environments remain largely unexplored this respect. Few studies exist concerning acoustic diversity ponds, because aquatic plants many arthropods such as Coleoptera Hemiptera are known produce sound, there potential use ecoacoustic techniques changes conservation value. This pilot study compares recently restored...
Introduction Identification of skin cancer by an Artificial Intelligence (AI)-based Digital Health Technology could help improve the triage and management suspicious lesions. Methods The DERM-003 study (NCT04116983) was a prospective, multi-center, single-arm, masked that aimed to demonstrate effectiveness AI as Medical Device (AIaMD) identify Squamous Cell Carcinoma (SCC), Basal (BCC), pre-malignant benign lesions from dermoscopic images Suspicious were suitable for photography photographed...
A method for the automatic detection and recognition of text symbols painted on road surface is presented. Candidate regions are detected as maximally stable extremal (MSER) in a frame which has been transformed into an inverse perspective mapping (IPM) image, showing with the effects distortion removed. Detected candidates then sorted words symbols, before they interpreted using separate stages. Symbol-based markings recognised using histogram oriented gradient (HOG) features...
Abstract Aquatic invasive species, such as the signal crayfish ( Pacifastacus leniusculus ), present a major threat to freshwater ecosystems. However, these species can be challenging detect in recently invaded habitats. Environmental DNA (eDNA)–based methods are highly sensitive and capable of detecting just few copies target from non‐invasively collected samples. Therefore, they have considerable potential for broad‐scale use mapping monitoring spread species. In this study, we aimed...
Abstract Passive acoustic monitoring has been used for decades as a non‐invasive tool quantifying biodiversity in terrestrial and marine ecosystems. Recently, there increased interest the potential method to survey freshwater biodiversity. Fundamental aspects of soundscape phenology, however, often remain poorly understood, despite their importance suitable design. To gain greater understanding daily variation aquatic insect‐dominated temperate pond soundscapes, 840 hr underwater sound...
Abstract Freshwater conservation is vital to the maintenance of global biodiversity. Ponds are a critical, yet often under‐recognized, part this, contributing overall ecosystem functioning and diversity. They provide habitats for range aquatic, terrestrial, amphibious life, including rare declining species. Effective, rapid, accessible survey methods needed enable evidence‐based action, but freshwater taxa viewed as “difficult”—and few specialist surveyors available. Datasets on ponds...
Abstract The introduction of the signal crayfish Pacifastacus leniusculus to British rivers has led ecological degradation and decline native white‐clawed Austropotamobius pallipes . To manage mitigate impact crayfish, conservation agencies government bodies employ multiple strategies. These take form proactive breeding stocking programs reactive invasive control programs. Here, we used eDNA assess populations species across 50 sites in 10 river catchments Norfolk, United Kingdom (UK). were...
Abstract Squamous cell carcinoma (SCC) and basal (BCC) are common types of nonmelanoma skin cancer (NMSC). The DERM-003 study was a prospective, multicentre, single-arm, masked that aimed to demonstrate the effectiveness an artificial intelligence-based digital health technology (AI-DHT) identify SCC, BCC premalignant conditions in dermoscopic images suspicious lesions. Patients with at least one lesion suitable for photography were eligible. Each photographed three smartphone cameras...
Abstract Squamous cell carcinoma (SCC) and basal (BCC) are common types of nonmelanoma skin cancer (NMSC). The DERM-003 study was a prospective multicentre single-arm masked that aimed to demonstrate the effectiveness an artificial intelligence-based digital health technology (AI-DHT) identify SCC, BCC premalignant conditions in dermoscopic images suspicious lesions. Patients with at least one lesion suitable for photography were eligible. Each photographed three smartphone cameras (iPhone...
Abstract Background The US FDA recently stated in its Proposed Regulatory Framework for software as a medical device (SaMD) that “One of the greatest benefits AI/ML resides ability to learn from real-world use and experience, capability improve performance.” This study follows two previous publications which addressed accuracy machine learning algorithm detection malignant melanoma. aim this was quantify change following modifications (DERM) non-melanoma skin cancers potential precursors...