AIMC Topic: Neural Networks, Computer

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Pixel-Reasoning-Based Robotics Fine Grasping for Novel Objects with Deep EDINet Structure.

Sensors (Basel, Switzerland)
Robotics grasp detection has mostly used the extraction of candidate grasping rectangles; those discrete sampling methods are time-consuming and may ignore the potential best grasp synthesis. This paper proposes a new pixel-level grasping detection m...

A Long Short-Term Memory Network for Plasma Diagnosis from Langmuir Probe Data.

Sensors (Basel, Switzerland)
Electrostatic probe diagnosis is the main method of plasma diagnosis. However, the traditional diagnosis theory is affected by many factors, and it is difficult to obtain accurate diagnosis results. In this study, a long short-term memory (LSTM) appr...

Automated segmentation of head CT scans for computer-assisted craniomaxillofacial surgery applying a hierarchical patch-based stack of convolutional neural networks.

International journal of computer assisted radiology and surgery
PURPOSE: Computer-assisted techniques play an important role in craniomaxillofacial surgery. As segmentation of three-dimensional medical imaging represents a cornerstone for these procedures, the present study was aiming at investigating a deep lear...

An efficient model of residual based convolutional neural network with Bayesian optimization for the classification of malarial cell images.

Computers in biology and medicine
BACKGROUND: Malaria is a disease caused by the Plasmodium parasite, which results in millions of deaths in the human population worldwide each year. It is therefore considered a major global health issue with a massive disease burden. Accurate and ra...

MGLNN: Semi-supervised learning via Multiple Graph Cooperative Learning Neural Networks.

Neural networks : the official journal of the International Neural Network Society
In many machine learning applications, data are coming with multiple graphs, which is known as the multiple graph learning problem. The problem of multiple graph learning is to learn consistent representation by exploiting the complementary informati...

End-systole and end-diastole detection in short axis cine MRI using a fully convolutional neural network with dilated convolutions.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
The correct assessment and characterization of heart anatomy and functionality is usually done through inspection of magnetic resonance image cine sequences. In the clinical setting it is especially important to determine the state of the left ventri...

Sum-Product Networks: A Survey.

IEEE transactions on pattern analysis and machine intelligence
A sum-product network (SPN) is a probabilistic model, based on a rooted acyclic directed graph, in which terminal nodes represent probability distributions and non-terminal nodes represent convex sums (weighted averages) and products of probability d...

LocalDrop: A Hybrid Regularization for Deep Neural Networks.

IEEE transactions on pattern analysis and machine intelligence
In neural networks, developing regularization algorithms to settle overfitting is one of the major study areas. We propose a new approach for the regularization of neural networks by the local Rademacher complexity called LocalDrop. A new regularizat...

Image Segmentation Using Deep Learning: A Survey.

IEEE transactions on pattern analysis and machine intelligence
Image segmentation is a key task in computer vision and image processing with important applications such as scene understanding, medical image analysis, robotic perception, video surveillance, augmented reality, and image compression, among others, ...

APANet: Auto-Path Aggregation for Future Instance Segmentation Prediction.

IEEE transactions on pattern analysis and machine intelligence
Despite the remarkable progress achieved in conventional instance segmentation, the problem of predicting instance segmentation results for unobserved future frames remains challenging due to the unobservability of future data. Existing methods mainl...