AIMC Topic: Photography

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Big Data Driven Detection of Trees in Suburban Scenes Using Visual Spectrum Eye Level Photography.

Sensors (Basel, Switzerland) May 28, 2020
The aim of the work described in this paper is to detect trees in eye level view images. Unlike previous work that universally considers highly constrained environments, such as natural parks and wooded areas, or simple scenes with little clutter and...
Data Collection Pattern Recognition, Automated Photography Machine Learning Big Data Trees
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Real-Time Human Action Recognition with a Low-Cost RGB Camera and Mobile Robot Platform.

Sensors (Basel, Switzerland) May 19, 2020
Human action recognition is an important research area in the field of computer vision that can be applied in surveillance, assisted living, and robotic systems interacting with people. Although various approaches have been widely used, recent studie...
Movement Human Activities Skeleton Humans Neural Networks, Computer Algorithms Robotics Joints Photography
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A deep learning system for differential diagnosis of skin diseases.

Nature medicine May 18, 2020
Skin conditions affect 1.9 billion people. Because of a shortage of dermatologists, most cases are seen instead by general practitioners with lower diagnostic accuracy. We present a deep learning system (DLS) to provide a differential diagnosis of sk...
Female Melanoma Skin Neoplasms Carcinoma, Basal Cell Carcinoma, Squamous Cell Humans Indians, North American Psoriasis Diagnosis, Differential Dermatologists Skin Diseases Adult Male Middle Aged Deep Learning Asian Photography Nurse Practitioners Keratosis, Seborrheic Warts Dermatitis, Seborrheic Folliculitis Alaska Natives Native Hawaiian or Pacific Islander Black or African American Eczema Acne Vulgaris Hispanic or Latino Telemedicine White People Physicians, Primary Care
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Automatic Grading System for Diabetic Retinopathy Diagnosis Using Deep Learning Artificial Intelligence Software.

Current eye research May 15, 2020
: To describe the development and validation of an artificial intelligence-based, deep learning algorithm (DeepDR) for the detection of diabetic retinopathy (DR) in retinal fundus photographs. : Five hundred fundus images, which had detailed labellin...
Humans Diabetic Retinopathy Neural Networks, Computer Software Reproducibility of Results Sensitivity and Specificity Diagnosis, Computer-Assisted Fluorescein Angiography Retinal Hemorrhage Photography Microaneurysm Deep Learning Predictive Value of Tests Area Under Curve Exudates and Transudates
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A deep learning algorithm to detect chronic kidney disease from retinal photographs in community-based populations.

The Lancet. Digital health May 12, 2020
BACKGROUND: Screening for chronic kidney disease is a challenge in community and primary care settings, even in high-income countries. We developed an artificial intelligence deep learning algorithm (DLA) to detect chronic kidney disease from retinal...
Eye Diseases Photography Renal Insufficiency, Chronic Singapore Fundus Oculi Image Interpretation, Computer-Assisted Algorithms Female Reproducibility of Results Sensitivity and Specificity Cross-Sectional Studies Humans Male Middle Aged Deep Learning China
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A novel vision-based real-time method for evaluating postural risk factors associated with musculoskeletal disorders.

Applied ergonomics May 4, 2020
Real-time risk assessment for work-related musculoskeletal disorders (MSD) has been a challenging research problem. Previous methods such as using depth cameras suffered from limited visual range and wearable sensors could cause intrusiveness to the ...
Occupational Diseases Lifting Posture Musculoskeletal Diseases Ergonomics Photography Upper Extremity Male Risk Assessment Deep Learning Image Processing, Computer-Assisted Humans Female Risk Factors Adult
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BPBSAM: Body part-specific burn severity assessment model.

Burns : journal of the International Society for Burn Injuries May 4, 2020
BACKGROUND AND OBJECTIVE: Burns are a serious health problem leading to several thousand deaths annually, and despite the growth of science and technology, automated burns diagnosis still remains a major challenge. Researchers have been exploring vis...
Trauma Severity Indices Back Injuries Hand Injuries Facial Injuries Forearm Injuries Support Vector Machine Burns Automation Photography Humans Deep Learning
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CycleGAN-based deep learning technique for artifact reduction in fundus photography.

Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie May 2, 2020
PURPOSE: A low quality of fundus photograph with artifacts may lead to false diagnosis. Recently, a cycle-consistent generative adversarial network (CycleGAN) has been introduced as a tool to generate images without matching paired images. Therefore,...
Fundus Oculi Retina Artifacts Diagnostic Techniques, Ophthalmological Photography Humans Algorithms Deep Learning Image Processing, Computer-Assisted
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Technological advances for the detection of melanoma: Advances in diagnostic techniques.

Journal of the American Academy of Dermatology Apr 26, 2020
Managing the balance between accurately identifying early stage melanomas while avoiding obtaining biopsy specimens of benign lesions (ie, overbiopsy) is the major challenge of melanoma detection. Decision making can be especially difficult in patien...
Humans Photography Machine Learning Imaging, Three-Dimensional Melanoma Microscopy, Confocal Skin Neoplasms Biomedical Technology Dermoscopy Dielectric Spectroscopy
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Artificial intelligence for teleophthalmology-based diabetic retinopathy screening in a national programme: an economic analysis modelling study.

The Lancet. Digital health Apr 23, 2020
BACKGROUND: Deep learning is a novel machine learning technique that has been shown to be as effective as human graders in detecting diabetic retinopathy from fundus photographs. We used a cost-minimisation analysis to evaluate the potential savings ...
Diagnostic Techniques, Ophthalmological Diabetes Mellitus Aged Humans Health Care Costs Singapore Adult Mass Screening Diabetic Retinopathy Photography Models, Biological Sensitivity and Specificity Decision Trees Artificial Intelligence Physical Examination Retina Ophthalmology Machine Learning Middle Aged Telemedicine Image Processing, Computer-Assisted Cost-Benefit Analysis
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