Gum Disease Detection in the Front Part of the Mouth Using Convolutional Neural Network Through the Use of Keras with TensorFlow as Backend

Carillo, Edgardo Raphael; Dispo, Shalom; Fallarco, Renfroe Von Harlagee; Mateo, Karen Faye; Garcia, Ramon G.; Sejera, Marianne M.; Valiente, Flordeliza L.

doi:10.1145/3397391.3397429

Cited by 4 publications

(1 citation statement)

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“…Among the existing models for the evaluation and validation of classifiers, the K-folds Cross-Validation method was used [ 38 ]. This method has as a principle the division of the data set into k complementary parts where k-1 of these parts are used for training and the last part is used for testing.…”

Section: Software Application Developmentmentioning

confidence: 99%

Development of a Virtual Reality Simulator for an Intelligent Robotic System Used in Ankle Rehabilitation

Covaciu

Pîslă

Iordan

2021

Sensors

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The traditional systems used in the physiotherapy rehabilitation process are evolving towards more advanced systems that use virtual reality (VR) environments so that the patient in the rehabilitation process can perform various exercises in an interactive way, thus improving the patient’s motivation and reducing the therapist’s work. The paper presents a VR simulator for an intelligent robotic system of physiotherapeutic rehabilitation of the ankle of a person who has had a stroke. This simulator can interact with a real human subject by attaching a sensor that contains a gyroscope and accelerometer to identify the position and acceleration of foot movement on three axes. An electromyography (EMG) sensor is also attached to the patient’s leg muscles to measure muscle activity because a patient who is in a worse condition has weaker muscle activity. The data collected from the sensors are taken by an intelligent module that uses machine learning to create new levels of exercise and control of the robotic rehabilitation structure of the virtual environment. Starting from these objectives, the virtual reality simulator created will have a low dependence on the therapist, this being the main improvement over other simulators already created for this purpose.

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Section: Software Application Developmentmentioning

confidence: 99%