AIMC Topic: Neural Networks, Computer

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Explainability of deep neural networks for MRI analysis of brain tumors.

International journal of computer assisted radiology and surgery
PURPOSE: Artificial intelligence (AI), in particular deep neural networks, has achieved remarkable results for medical image analysis in several applications. Yet the lack of explainability of deep neural models is considered the principal restrictio...

Improving neural network classification of indigenous forest in New Zealand with phenological features.

Journal of environmental management
Accurate and up-to-date land cover maps inform and support effective management and policy decisions. Describing phenological changes in spectral response using time-series data may help to distinguish vegetation types, thereby allowing for more spec...

Research on Impulse Power Load Forecasting Based on Improved Recurrent Neural Networks.

Computational intelligence and neuroscience
Deep learning is good at extracting the required feature quantity from the massive input information through multiple hidden layers and completing the learning through training to achieve the task of load forecasting. The impulse power load data cont...

Sparse factorization of square matrices with application to neural attention modeling.

Neural networks : the official journal of the International Neural Network Society
Square matrices appear in many machine learning problems and models. Optimization over a large square matrix is expensive in memory and in time. Therefore an economic approximation is needed. Conventional approximation approaches factorize the square...

Predicting brain structural network using functional connectivity.

Medical image analysis
Uncovering the non-trivial brain structure-function relationship is fundamentally important for revealing organizational principles of human brain. However, it is challenging to infer a reliable relationship between individual brain structure and fun...

TOD-CNN: An effective convolutional neural network for tiny object detection in sperm videos.

Computers in biology and medicine
The detection of tiny objects in microscopic videos is a problematic point, especially in large-scale experiments. For tiny objects (such as sperms) in microscopic videos, current detection methods face challenges in fuzzy, irregular, and precise pos...

Artificial neural networks for the prediction of biochar yield: A comparative study of metaheuristic algorithms.

Bioresource technology
In this study, an integrated framework of artificial neural networks (ANNs) and metaheuristic algorithms have been developed for the prediction of biochar yield using biomass characteristics and pyrolysis process conditions. Comparative analysis of s...

Prediction of Disordered Regions in Proteins with Recurrent Neural Networks and Protein Dynamics.

Journal of molecular biology
The role of intrinsically disordered protein regions (IDRs) in cellular processes has become increasingly evident over the last years. These IDRs continue to challenge structural biology experiments because they lack a well-defined conformation, and ...

Dynamic Instability and Time Domain Response of a Model Halide Perovskite Memristor for Artificial Neurons.

The journal of physical chemistry letters
Memristors are candidate devices for constructing artificial neurons, synapses, and computational networks for brainlike information processing and sensory-motor autonomous systems. However, the dynamics of natural neurons and synapses are challengin...