AIMC Topic: Photography

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Applying artificial intelligence to disease staging: Deep learning for improved staging of diabetic retinopathy.

PloS one
PURPOSE: Disease staging involves the assessment of disease severity or progression and is used for treatment selection. In diabetic retinopathy, disease staging using a wide area is more desirable than that using a limited area. We investigated if d...

Deep Learning for Plant Identification in Natural Environment.

Computational intelligence and neuroscience
Plant image identification has become an interdisciplinary focus in both botanical taxonomy and computer vision. The first plant image dataset collected by mobile phone in natural scene is presented, which contains 10,000 images of 100 ornamental pla...

Grain classifier with computer vision using adaptive neuro-fuzzy inference system.

Journal of the science of food and agriculture
BACKGROUND: A computer vision-based classifier using an adaptive neuro-fuzzy inference system (ANFIS) is designed for classifying wheat grains into bread or durum. To train and test the classifier, images of 200 wheat grains (100 for bread and 100 fo...

An extensive analysis of various texture feature extractors to detect Diabetes Mellitus using facial specific regions.

Computers in biology and medicine
INTRODUCTION: Researchers have recently discovered that Diabetes Mellitus can be detected through non-invasive computerized method. However, the focus has been on facial block color features. In this paper, we extensively study the effects of texture...

Dermatologist-level classification of skin cancer with deep neural networks.

Nature
Skin cancer, the most common human malignancy, is primarily diagnosed visually, beginning with an initial clinical screening and followed potentially by dermoscopic analysis, a biopsy and histopathological examination. Automated classification of ski...

Neuro-Analogical Gate Tuning of Trajectory Data Fusion for a Mecanum-Wheeled Special Needs Chair.

PloS one
Trajectory tracking of mobile wheeled chairs using internal shaft encoder and inertia measurement unit(IMU), exhibits several complications and accumulated errors in the tracking process due to wheel slippage, offset drift and integration approximati...

Area Determination of Diabetic Foot Ulcer Images Using a Cascaded Two-Stage SVM-Based Classification.

IEEE transactions on bio-medical engineering
The standard chronic wound assessment method based on visual examination is potentially inaccurate and also represents a significant clinical workload. Hence, computer-based systems providing quantitative wound assessment may be valuable for accurate...

A Discriminatively Trained Fully Connected Conditional Random Field Model for Blood Vessel Segmentation in Fundus Images.

IEEE transactions on bio-medical engineering
GOAL: In this work, we present an extensive description and evaluation of our method for blood vessel segmentation in fundus images based on a discriminatively trained fully connected conditional random field model.

Human Collaborative Localization and Mapping in Indoor Environments with Non-Continuous Stereo.

Sensors (Basel, Switzerland)
A new approach to the monocular simultaneous localization and mapping (SLAM) problem is presented in this work. Data obtained from additional bearing-only sensors deployed as wearable devices is fully fused into an Extended Kalman Filter (EKF). The w...

Automatic tracking of laparoscopic instruments for autonomous control of a cameraman robot.

Minimally invasive therapy & allied technologies : MITAT : official journal of the Society for Minimally Invasive Therapy
BACKGROUND: An automated instrument tracking procedure was designed and developed for autonomous control of a cameraman robot during laparoscopic surgery.