Results 51 to 60 of about 1,980,897 (317)
, 2019 Neural circuits can be reconstructed from brain images acquired by serial section electron microscopy. Image analysis has been performed by manual labor for half a century, and efforts at automation date back almost as far.
Wu, Jingpeng +5 more
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A Dimensionality Reduction Approach for Convolutional Neural Networks [PDF]
, 2021 The focus of this paper is the application of classical model order reduction techniques, such as Active Subspaces and Proper Orthogonal Decomposition, to Deep Neural Networks.
Demo, Nicola +8 more
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Convolutional deep rectifier neural nets for phone recognition [PDF]
Interspeech 2013, 2013 Rectifier neurons differ from standard ones only in that the sigmoid activation function is replaced by the rectifier function, max(0, x). Several recent studies suggest that rectifier units may be more suitable building units for deep nets. For example, we found that with deep rectifier networks one can attain a similar speech recognition performance ...
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Efficient Training of Convolutional Neural Nets on Large Distributed Systems [PDF]
2018 IEEE International Conference on Cluster Computing (CLUSTER), 2018 Deep Neural Networks (DNNs) have achieved im- pressive accuracy in many application domains including im- age classification. Training of DNNs is an extremely compute- intensive process and is solved using variants of the stochastic gradient descent (SGD) algorithm. A lot of recent research has focussed on improving the performance of DNN training.
Dheeraj Sreedhar +4 more
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Artificial Neural Nets with Interaction of Afferents [PDF]
, 2011 The aim is to obtain computationally more powerful, neuro physiologically founded, artificial neurons and neural nets. Artificial Neural Nets (ANN) of the Perceptron type evolved from the original proposal by McCulloch an Pitts classical paper [1 ...
Blasio, Gabriel de +2 more
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Arthritis Care &Research, EarlyView.Systemic sclerosis (SSc) is a rare autoimmune disease defined by immune dysregulation, vasculopathy, and progressive fibrosis of the skin and internal organs. Despite advances in care, major complications such as interstitial lung disease (ILD) and myocardial involvement remain the leading causes of morbidity and mortality.
Cristiana Sieiro Santos +2 more
wiley +1 more source
Facial Emotions Recognition using Convolutional Neural Net
CoRR, 2020 Facial expressions vary from person to person, and the brightness, contrast, and resolution of every random image are different. This is why recognizing facial expressions is very difficult. This article proposes an efficient system for facial emotion recognition for the seven basic human emotions (angry, disgust, fear, happy, sad, surprise, and ...
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Arthritis Care &Research, Accepted Article.Objective For cartilage morphology to serve as a scalable endpoint in clinical trials, analyses should be performed automatically without human interaction. To clinically validate artificial intelligence (AI)‐based analysis, we studied cartilage loss from MRI prior to knee replacement.
Felix Eckstein +3 more
wiley +1 more source
SACNet: Shuffling atrous convolutional U‐Net for medical image segmentation
IET Image Processing, 2023 Medical images exhibit multi‐granularity and high obscurity along boundaries. As representative work, the U‐Net and its variants exhibit two shortcomings on medical image segmentation: (a) they expand the range of reception fields by applying addition or
Shaofan Wang +3 more
doaj +1 more source
Seesaw-Net: Convolution Neural Network With Uneven Group Convolution
CoRR, 2019 In this paper, we are interested in boosting the representation capability of convolution neural networks which utilizing the inverted residual structure. Based on the success of Inverted Residual structure[Sandler et al. 2018] and Interleaved Low-Rank Group Convolutions[Sun et al.
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