AIMC Topic: Neural Networks, Computer

Clear Filters Showing 9421 to 9430 of 31376 articles

Targeting operational regimes of interest in recurrent neural networks.

PLoS computational biology
Neural computations emerge from local recurrent neural circuits or computational units such as cortical columns that comprise hundreds to a few thousand neurons. Continuous progress in connectomics, electrophysiology, and calcium imaging require trac...

Diffusion characteristics classification framework for identification of diffusion source in complex networks.

PloS one
The diffusion phenomena taking place in complex networks are usually modelled as diffusion process, such as the diffusion of diseases, rumors and viruses. Identification of diffusion source is crucial for developing strategies to control these harmfu...

E2EFP-MIL: End-to-end and high-generalizability weakly supervised deep convolutional network for lung cancer classification from whole slide image.

Medical image analysis
Efficient and accurate distinction of histopathological subtype of lung cancer is quite critical for the individualized treatment. So far, artificial intelligence techniques have been developed, whose performance yet remained debatable on more hetero...

Design of continuous-time recurrent neural networks with piecewise-linear activation function for generation of prescribed sequences of bipolar vectors.

Neural networks : the official journal of the International Neural Network Society
A recurrent neural network (RNN) can generate a sequence of patterns as the temporal evolution of the output vector. This paper focuses on a continuous-time RNN model with a piecewise-linear activation function that has neither external inputs nor hi...

Deep Transfer Learning Technique for Multimodal Disease Classification in Plant Images.

Contrast media & molecular imaging
Rice () is India's major crop. India has the most land dedicated to rice agriculture, which includes both brown and white rice. Rice cultivation creates jobs and contributes significantly to the stability of the gross domestic product (GDP). Recogniz...

Input-to-state stability of positive delayed neural networks via impulsive control.

Neural networks : the official journal of the International Neural Network Society
This paper is concerned with the positivity and impulsive stabilization of equilibrium points of delayed neural networks (DNNs) subject to bounded disturbances. With the aid of the continuous dependence theorem for impulsive delay differential equati...

Exploring the Advantages of Quantum Generative Adversarial Networks in Generative Chemistry.

Journal of chemical information and modeling
De novo drug design with desired biological activities is crucial for developing novel therapeutics for patients. The drug development process is time- and resource-consuming, and it has a low probability of success. Recent advances in machine learni...

Segmentation and classification of brain tumors using fuzzy 3D highlighting and machine learning.

Journal of cancer research and clinical oncology
PURPOSE: Brain tumors are among the most lethal forms of cancer, so early diagnosis is crucial. As a result of machine learning algorithms, radiologists can now make accurate diagnoses of tumors without resorting to invasive procedures. There are, ho...

EpiTEAmDNA: Sequence feature representation via transfer learning and ensemble learning for identifying multiple DNA epigenetic modification types across species.

Computers in biology and medicine
Methylation is a major DNA epigenetic modification for regulating the biological processes without altering the DNA sequence, and multiple types of DNA methylations have been discovered, including 6mA, 5hmC, and 4mC. Multiple computational approaches...

Robust and efficient abdominal CT segmentation using shape constrained multi-scale attention network.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
PURPOSE: Although many deep learning-based abdominal multi-organ segmentation networks have been proposed, the various intensity distributions and organ shapes of the CT images from multi-center, multi-phase with various diseases introduce new challe...