AIMC Topic: Neural Networks, Computer

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Motor decoding from the posterior parietal cortex using deep neural networks.

Journal of neural engineering
Motor decoding is crucial to translate the neural activity for brain-computer interfaces (BCIs) and provides information on how motor states are encoded in the brain. Deep neural networks (DNNs) are emerging as promising neural decoders. Nevertheless...

Recurrent neural network modeling of multivariate time series and its application in temperature forecasting.

PloS one
Temperature forecasting plays an important role in human production and operational activities. Traditional temperature forecasting mainly relies on numerical forecasting models to operate, which takes a long time and has higher requirements for the ...

Sequence based local-global information fusion framework for vertebrae detection under pathological and FOV variation challenges.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Automated vertebrae detection (identification and localization) aims to identify vertebrae and locate their centroids in medical images, which is a critical step of spinal computer-aided systems. However, due to unpredictable field-of-view and variou...

Approximate spectral decomposition of Fisher information matrix for simple ReLU networks.

Neural networks : the official journal of the International Neural Network Society
We argue the Fisher information matrix (FIM) of one hidden layer networks with the ReLU activation function. For a network, let W denote the d×p weight matrix from the d-dimensional input to the hidden layer consisting of p neurons, and v the p-dimen...

Predicting 3D soft tissue dynamics from 2D imaging using physics informed neural networks.

Communications biology
Tissue dynamics play critical roles in many physiological functions and provide important metrics for clinical diagnosis. Capturing real-time high-resolution 3D images of tissue dynamics, however, remains a challenge. This study presents a hybrid phy...

Single-frame deep-learning super-resolution microscopy for intracellular dynamics imaging.

Nature communications
Single-molecule localization microscopy (SMLM) can be used to resolve subcellular structures and achieve a tenfold improvement in spatial resolution compared to that obtained by conventional fluorescence microscopy. However, the separation of single-...

An object detection algorithm combining self-attention and YOLOv4 in traffic scene.

PloS one
Automobile intelligence is the trend for modern automobiles, of which environment perception is the key technology of intelligent automobile research. For autonomous vehicles, the detection of object information, such as vehicles and pedestrians in t...

Optimizing Representations of Multiple Simultaneous Attributes for Gait Generation Using Deep Learning.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Rich variations in gait are generated according to several attributes of the individual and environment, such as age, athleticism, terrain, speed, personal "style", mood, etc. The effects of these attributes can be hard to quantify explicitly, but re...

Molecular Generation with Reduced Labeling through Constraint Architecture.

Journal of chemical information and modeling
In the past few years, a number of machine learning (ML)-based molecular generative models have been proposed for generating molecules with desirable properties, but they all require a large amount of label data of pharmacological and physicochemical...