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Boosting Adversarial Attacks with Momentum
Deep neural networks are vulnerable to adversarial examples, which poses security concerns on these algorithms due to the potentially severe consequences. Adversarial attacks serve as an importantExpand
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Defense Against Adversarial Attacks Using High-Level Representation Guided Denoiser
Neural networks are vulnerable to adversarial examples, which poses a threat to their application in security sensitive systems. We propose high-level representation guided denoiser (HGD) as aExpand
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Evaluate the Malignancy of Pulmonary Nodules Using the 3-D Deep Leaky Noisy-OR Network
Automatic diagnosing lung cancer from computed tomography scans involves two steps: detect all suspicious lesions (pulmonary nodules) and evaluate the whole-lung/pulmonary malignancy. Currently,Expand
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Adversarial Attacks and Defences Competition
To accelerate research on adversarial examples and robustness of machine learning classifiers, Google Brain organized a NIPS 2017 competition that encouraged researchers to develop new methods toExpand
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Discovering Adversarial Examples with Momentum
Machine learning models, especially Deep Neural Networks, are vulnerable to adversarial examples---malicious inputs crafted by adding small noises to real examples, but fool the models. AdversarialExpand
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Geology, geochronology and geochemistry of the Saishitang Cu deposit, East Kunlun Mountains, NW China: Constraints on ore genesis and tectonic setting
Abstract The Saishitang Cu deposit, located on the eastern area of the Eastern Kunlun Orogenic Belt (EKOB), and on the northern margin of the Tibetan Plateau, is one of the most important copperExpand
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Estimation of the Volume of the Left Ventricle From MRI Images Using Deep Neural Networks
Segmenting human left ventricle (LV) in magnetic resonance imaging images and calculating its volume are important for diagnosing cardiac diseases. The latter task became the topic of the SecondExpand
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Somatostatin Neurons in the Basal Forebrain Promote High-Calorie Food Intake.
Obesity has become a global issue, and the overconsumption of food is thought to be a major contributor. However, the regulatory neural circuits that regulate palatable food consumption remainExpand
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Rapid vessel segmentation and reconstruction of head and neck angiograms using 3D convolutional neural network
The computed tomography angiography (CTA) postprocessing manually recognized by technologists is extremely labor intensive and error prone. We propose an artificial intelligence reconstruction systemExpand
Automatic Identification of Coronary Arteries in Coronary Computed Tomographic Angiography
Cardiovascular disease has seriously affected the lives of modern people. One of the most commonly used imaging methods for diagnosing cardiovascular disease is computed tomography angiography (CTA).Expand