AIMC Topic: Neural Networks, Computer

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Learning feature fusion for target detection based on polarimetric imaging.

Applied optics
We propose a polarimetric imaging processing method based on feature fusion and apply it to the task of target detection. Four images with distinct polarization orientations were used as one parallel input, and they were fused into a single feature m...

Self-supervised stereo depth estimation based on bi-directional pixel-movement learning.

Applied optics
Stereo depth estimation is an efficient method to perceive three-dimensional structures in real scenes. In this paper, we propose a novel self-supervised method, to the best of our knowledge, to extract depth information by learning bi-directional pi...

Hologram classification of occluded and deformable objects with speckle noise contamination by deep learning.

Journal of the Optical Society of America. A, Optics, image science, and vision
Advancements in optical, computing, and electronic technologies have enabled holograms of physical three-dimensional (3D) objects to be captured. The hologram can be displayed with a spatial light modulator to reconstruct a visible image. Although ho...

An influent generator for WRRF design and operation based on a recurrent neural network with multi-objective optimization using a genetic algorithm.

Water science and technology : a journal of the International Association on Water Pollution Research
Nowadays, modelling, automation and control are widely used for Water Resource Recovery Facilities (WRRF) upgrading and optimization. Influent generator (IG) models are used to provide relevant input time series for dynamic WRRF simulations used in t...

Editorial Commentary: Big Data and Machine Learning in Medicine.

Arthroscopy : the journal of arthroscopic & related surgery : official publication of the Arthroscopy Association of North America and the International Arthroscopy Association
Recent research using machine learning and data mining to determine predictors of prolonged opioid use after arthroscopic surgery showed that Artificial Neural Networks showed superior discrimination and calibration. Other machine learning algorithms...

Universal encoding of pan-cancer histology by deep texture representations.

Cell reports
Cancer histological images contain rich biological and clinical information, but quantitative representation can be problematic and has prevented the direct comparison and accumulation of large-scale datasets. Here, we show successful universal encod...

Surveillance of few-mode fiber-communication channels with a single hidden layer neural network.

Optics letters
Multi- and few-mode fibers (FMFs) promise to enhance the capacity of optical communication networks by orders of magnitude. The key for this evolution was the strong advancement of computational approaches that allowed inherent complex light transmis...

Diffractive deep neural network adjoint assist or (DNA): a fast and efficient nonlinear diffractive neural network implementation.

Optics express
The recent advent of diffractive deep neural networks or DNNs has opened new avenues for the design and optimization of multi-functional optical materials; despite the effectiveness of the DNN approach, there is a need for making these networks as we...

Comparison among Four Deep Learning Image Classification Algorithms in AI-based Diatom Test.

Fa yi xue za zhi
OBJECTIVES: To select four algorithms with relatively balanced complexity and accuracy among deep learning image classification algorithms for automatic diatom recognition, and to explore the most suitable classification algorithm for diatom recognit...

Efficient Measure for the Expressivity of Variational Quantum Algorithms.

Physical review letters
The superiority of variational quantum algorithms (VQAs) such as quantum neural networks (QNNs) and variational quantum eigensolvers (VQEs) heavily depends on the expressivity of the employed Ansätze. Namely, a simple Ansatz is insufficient to captur...