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Experimental validation of computer-vision methods for the successful detection of endodontic treatment obturation and progression from noisy radiographs.

Oral radiology
PURPOSE: (1) To evaluate the effects of denoising and data balancing on deep learning to detect endodontic treatment outcomes from radiographs. (2) To develop and train a deep-learning model and classifier to predict obturation quality from radiomics...

Microbiological Quality Estimation of Meat Using Deep CNNs on Embedded Hardware Systems.

Sensors (Basel, Switzerland)
Spectroscopic sensor imaging of food samples meta-processed by deep machine learning models can be used to assess the quality of the sample. This article presents an architecture for estimating microbial populations in meat samples using multispectra...

Biological Robots: Perspectives on an Emerging Interdisciplinary Field.

Soft robotics
Advances in science and engineering often reveal the limitations of classical approaches initially used to understand, predict, and control phenomena. With progress, conceptual categories must often be re-evaluated to better track recently discovered...

The value of deep learning-based computer aided diagnostic system in improving diagnostic performance of rib fractures in acute blunt trauma.

BMC medical imaging
BACKGROUND: To evaluate the value of a deep learning-based computer-aided diagnostic system (DL-CAD) in improving the diagnostic performance of acute rib fractures in patients with chest trauma.

CHARLES: A C++ fixed-point library for Photonic-Aware Neural Networks.

Neural networks : the official journal of the International Neural Network Society
In this paper we present CHARLES (C++ pHotonic Aware neuRaL nEtworkS), a C++ library aimed at providing a flexible tool to simulate the behavior of Photonic-Aware Neural Network (PANN). PANNs are neural network architectures aware of the constraints ...

Overview of Spiking Neural Network Learning Approaches and Their Computational Complexities.

Sensors (Basel, Switzerland)
Spiking neural networks (SNNs) are subjects of a topic that is gaining more and more interest nowadays. They more closely resemble actual neural networks in the brain than their second-generation counterparts, artificial neural networks (ANNs). SNNs ...

Developing Edge AI Computer Vision for Smart Poultry Farms Using Deep Learning and HPC.

Sensors (Basel, Switzerland)
This research describes the use of high-performance computing (HPC) and deep learning to create prediction models that could be deployed on edge AI devices equipped with camera and installed in poultry farms. The main idea is to leverage an existing ...

: Quantification of user-defined animal behaviors using learning-based holistic assessment.

Cell reports methods
Quantifying animal behavior is important for biological research. Identifying behaviors is the prerequisite of quantifying them. Current computational tools for behavioral quantification typically use high-level properties such as body poses to ident...

Development of a Real-Time 6-DOF Motion-Tracking System for Robotic Computer-Assisted Implant Surgery.

Sensors (Basel, Switzerland)
In this paper, we investigate a motion-tracking system for robotic computer-assisted implant surgery. Failure of the accurate implant positioning may result in significant problems, thus an accurate real-time motion-tracking system is crucial for avo...