AIMC Topic: Neural Networks, Computer

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Depth with nonlinearity creates no bad local minima in ResNets.

Neural networks : the official journal of the International Neural Network Society
In this paper, we prove that depth with nonlinearity creates no bad local minima in a type of arbitrarily deep ResNets with arbitrary nonlinear activation functions, in the sense that the values of all local minima are no worse than the global minimu...

Approximating the Architecture of Visual Cortex in a Convolutional Network.

Neural computation
Deep convolutional neural networks (CNNs) have certain structural, mechanistic, representational, and functional parallels with primate visual cortex and also many differences. However, perhaps some of the differences can be reconciled. This study de...

When Not to Classify: Anomaly Detection of Attacks (ADA) on DNN Classifiers at Test Time.

Neural computation
A significant threat to the recent, wide deployment of machine learning-based systems, including deep neural networks (DNNs), is adversarial learning attacks. The main focus here is on evasion attacks against DNN-based classifiers at test time. While...

Lung Cancer Detection using Probabilistic Neural Network with modified Crow-Search Algorithm.

Asian Pacific journal of cancer prevention : APJCP
Objective: Lung cancer is a type of malignancy that occurs most commonly among men and the third most common type of malignancy among women. The timely recognition of lung cancer is necessary for decreasing the effect of death rate worldwide. Since t...

Brain Tumour Segmentation Using Convolutional Neural Network with Tensor Flow.

Asian Pacific journal of cancer prevention : APJCP
Introduction: The determination of tumour extent is a major challenging task in brain tumour planning and quantitative evaluation. Magnetic Resonance Imaging (MRI) is one of the non-invasive technique has emanated as a front- line diagnostic tool for...

Automated diagnosis of ear disease using ensemble deep learning with a big otoendoscopy image database.

EBioMedicine
BACKGROUND: Ear and mastoid disease can easily be treated by early detection and appropriate medical care. However, short of specialists and relatively low diagnostic accuracy calls for a new way of diagnostic strategy, in which deep learning may pla...

Approaching coupled cluster accuracy with a general-purpose neural network potential through transfer learning.

Nature communications
Computational modeling of chemical and biological systems at atomic resolution is a crucial tool in the chemist's toolset. The use of computer simulations requires a balance between cost and accuracy: quantum-mechanical methods provide high accuracy ...

A feature agnostic approach for glaucoma detection in OCT volumes.

PloS one
Optical coherence tomography (OCT) based measurements of retinal layer thickness, such as the retinal nerve fibre layer (RNFL) and the ganglion cell with inner plexiform layer (GCIPL) are commonly employed for the diagnosis and monitoring of glaucoma...

An adaptive Kalman filtering algorithm based on back-propagation (BP) neural network applied for simultaneously detection of exhaled CO and NO.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
A compact high-resolution spectroscopic sensor using a thermoelectrically (TE) cooled continuous-wave (CW) room temperature (RT) quantum cascade laser (QCL) was demonstrated for simultaneous measurements of exhaled carbon monoxide (CO) and nitrous ox...

Segmenting and tracking cell instances with cosine embeddings and recurrent hourglass networks.

Medical image analysis
Differently to semantic segmentation, instance segmentation assigns unique labels to each individual instance of the same object class. In this work, we propose a novel recurrent fully convolutional network architecture for tracking such instance seg...