AIMC Topic: Deep Learning

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Accuracy of deep learning, a machine-learning technology, using ultra-wide-field fundus ophthalmoscopy for detecting rhegmatogenous retinal detachment.

Scientific reports
Rhegmatogenous retinal detachment (RRD) is a serious condition that can lead to blindness; however, it is highly treatable with timely and appropriate treatment. Thus, early diagnosis and treatment of RRD is crucial. In this study, we applied deep le...

Bladder Cancer Treatment Response Assessment in CT using Radiomics with Deep-Learning.

Scientific reports
Cross-sectional X-ray imaging has become the standard for staging most solid organ malignancies. However, for some malignancies such as urinary bladder cancer, the ability to accurately assess local extent of the disease and understand response to sy...

Development and assessment of a lysophospholipid-based deep learning model to discriminate geographical origins of white rice.

Scientific reports
Geographical origin determination of white rice has become the major issue of food industry. However, there is still lack of a high-throughput method for rapidly and reproducibly differentiating the geographical origins of commercial white rice. In t...

Photorealistic Monocular Gaze Redirection Using Machine Learning.

IEEE transactions on pattern analysis and machine intelligence
We propose a general approach to the gaze redirection problem in images that utilizes machine learning. The idea is to learn to re-synthesize images by training on pairs of images with known disparities between gaze directions. We show that such lear...

Faceness-Net: Face Detection through Deep Facial Part Responses.

IEEE transactions on pattern analysis and machine intelligence
We propose a deep convolutional neural network (CNN) for face detection leveraging on facial attributes based supervision. We observe a phenomenon that part detectors emerge within CNN trained to classify attributes from uncropped face images, withou...

Heterogeneous Face Attribute Estimation: A Deep Multi-Task Learning Approach.

IEEE transactions on pattern analysis and machine intelligence
Face attribute estimation has many potential applications in video surveillance, face retrieval, and social media. While a number of methods have been proposed for face attribute estimation, most of them did not explicitly consider the attribute corr...

Using Deep Learning for Classification of Lung Nodules on Computed Tomography Images.

Journal of healthcare engineering
Lung cancer is the most common cancer that cannot be ignored and cause death with late health care. Currently, CT can be used to help doctors detect the lung cancer in the early stages. In many cases, the diagnosis of identifying the lung cancer depe...

Holographic deep learning for rapid optical screening of anthrax spores.

Science advances
Establishing early warning systems for anthrax attacks is crucial in biodefense. Despite numerous studies for decades, the limited sensitivity of conventional biochemical methods essentially requires preprocessing steps and thus has limitations to be...

Two-Stream Transformer Networks for Video-Based Face Alignment.

IEEE transactions on pattern analysis and machine intelligence
In this paper, we propose a two-stream transformer networks (TSTN) approach for video-based face alignment. Unlike conventional image-based face alignment approaches which cannot explicitly model the temporal dependency in videos and motivated by the...

Efficient and robust cell detection: A structured regression approach.

Medical image analysis
Efficient and robust cell detection serves as a critical prerequisite for many subsequent biomedical image analysis methods and computer-aided diagnosis (CAD). It remains a challenging task due to touching cells, inhomogeneous background noise, and l...