AIMC Topic: Neural Networks, Computer

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Overlapped speech detection using phase features.

The Journal of the Acoustical Society of America
Simultaneous speech of multiple speakers is known as overlapped speech, which causes problems for speech recognition and speaker diarization systems. The present work uses previously less utilized signal phase information in the task of overlapped sp...

Analysis of chaotic dynamical systems with autoencoders.

Chaos (Woodbury, N.Y.)
We focus on chaotic dynamical systems and analyze their time series with the use of autoencoders, i.e., configurations of neural networks that map identical output to input. This analysis results in the determination of the latent space dimension of ...

Classification of imbalanced oral cancer image data from high-risk population.

Journal of biomedical optics
SIGNIFICANCE: Early detection of oral cancer is vital for high-risk patients, and machine learning-based automatic classification is ideal for disease screening. However, current datasets collected from high-risk populations are unbalanced and often ...

Deep learning-based method to accurately estimate breast tissue optical properties in the presence of the chest wall.

Journal of biomedical optics
SIGNIFICANCE: In general, image reconstruction methods used in diffuse optical tomography (DOT) are based on diffusion approximation, and they consider the breast tissue as a homogenous, semi-infinite medium. However, the semi-infinite medium assumpt...

Identification of glaucoma from fundus images using deep learning techniques.

Indian journal of ophthalmology
PURPOSE: Glaucoma is one of the preeminent causes of incurable visual disability and blindness across the world due to elevated intraocular pressure within the eyes. Accurate and timely diagnosis is essential for preventing visual disability. Manual ...

Toward High-Throughput Artificial Intelligence-Based Segmentation in Oncological PET Imaging.

PET clinics
Artificial intelligence (AI) techniques for image-based segmentation have garnered much attention in recent years. Convolutional neural networks have shown impressive results and potential toward fully automated segmentation in medical imaging, and p...

Transfer Deep Learning for Dental and Maxillofacial Imaging Modality Classification: A Preliminary Study.

The Journal of clinical pediatric dentistry
OBJECTIVE: To apply the technique of transfer deep learning on a small data set for automatic classification of X-ray modalities in dentistry.

A Web-Based Deep Learning Model for Automated Diagnosis of Otoscopic Images.

Otology & neurotology : official publication of the American Otological Society, American Neurotology Society [and] European Academy of Otology and Neurotology
OBJECTIVES: To develop a multiclass-classifier deep learning model and website for distinguishing tympanic membrane (TM) pathologies based on otoscopic images.

Introduction to Artificial Intelligence and Machine Learning for Pathology.

Archives of pathology & laboratory medicine
CONTEXT.—: Recent developments in machine learning have stimulated intense interest in software that may augment or replace human experts. Machine learning may impact pathology practice by offering new capabilities in analysis, interpretation, and ou...

Corneal Edema Visualization With Optical Coherence Tomography Using Deep Learning: Proof of Concept.

Cornea
PURPOSE: Optical coherence tomography (OCT) is essential for the diagnosis and follow-up of corneal edema, but assessment can be challenging in minimal or localized edema. The objective was to develop and validate a novel automated tool to detect and...