Dynamic Path Flow Estimation Using Automatic Vehicle Identification and Probe Vehicle Trajectory Data: A 3D Convolutional Neural Network Model by Can Chen, Yumin Cao, Keshuang Tang, Keping Li

“…Dynamic path flows, referring to the number of vehicles that choose each path in a network over time, are generally estimated with the partial observations as the input. …”
Get full text

Target behavior recognition of fully mechanized mining face based on multi-information self-attention by Yi YANG, Yanlei YANG, Tian WANG, Keping WANG

“…The algorithm is transformed by an ONNX model and accelerated using TensorRT to enable GPU inference, thereby enhancing its value for engineering applications. …”
Get full text

Origin and Variety Identification of Dried Kelp Based on Fluorescence Fingerprinting and Machine Learning Approaches by Kana Suzuki, Rikuto Akiyama, Yvan Llave, Takashi Matsumoto

“…The origin and variety of dried kelp are generally identified based on their morphological characteristics; however, they are difficult to distinguish unless experts are involved. …”
Get full text

Development of an embedded diagnostic tool for visual misalignment screening by Daniel Soto Rodriguez, Andres Eduardo Rivera Gomez, Ruthber Rodriguez Serrezuela

“…The software, developed in Python using PyQt5 and OpenCV, incorporates a NASNetLarge convolutional neural network converted to TensorFlow Lite for real-time inference. …”
Get full text

Different rs-fMRI Data Processing Methods in the Study of Vascular Cognitive Impairment by Ying GUAN, Luwen ZHU, Feng WANG, Danna CAO, Xiaoling LI, Qiang TANG

“…Generalized rs-fMRI includes blood oxygen level-dependent functional magnetic resonance imaging, magnetic resonance spectroscopy, magnetic susceptibility weighted imaging, and diffusion tensor imaging. …”
Get full text

An Extended Closure Relation by LightGBM for Neutrino Radiation Transport in Core-collapse Supernovae by Shota Takahashi, Akira Harada, Shoichi Yamada

“…In this paper, we report the results of this feature engineering in addition to those of the training, validation, and generalization of our model. We find that the flux factor and nonlocal features are among the most relevant features; our LightGBM model can reproduce the Eddington factor better in general than the M1 closure relation, one of the most commonly employed algebraic closure relations at present; the generalization performance is also much improved from our previous model based on the deep neural network.…”
Get full text

Quantum State Designs with Clifford-Enhanced Matrix Product States by Guglielmo Lami, Tobias Haug, Jacopo De Nardis

“…Our findings indicate that combining Clifford unitaries with polynomially complex tensor-network states can generate highly nontrivial quantum states.…”
Get full text

TCE-YOLOv5: Lightweight Automatic Driving Object Detection Algorithm Based on YOLOv5 by Han Wang, Zhenwei Yang, Qiaoshou Liu, Qiang Zhang, Honggang Wang

“…Secondly, the C3 module in the neck is replaced by the Res2Net module, which extracts features at different scales through multiple branches, not only ensuring rich details, but also enhancing the generalization ability of the network. Finally, the EIOU loss function is introduced to measure the overlap between the predicted box and the real box more accurately and improve the detection accuracy. …”
Get full text

Low-light image enhancement method based on retinex theory and dual-tree complex wavelet transform by Yuqian Zhang, Jie Jiang, Zhan Wang, Qi Zhang, Yudi Jiang, Jun Liu, Zeyao Hou

“…This method introduces multi-scale spectral layers for effective frequency decomposition and designs a spectral optimization network that calibrates low-frequency and high-frequency information through tensor fusion and Einstein hybrid methods. …”
Get full text

Far from Perfect: Quantum Error Correction with (Hyperinvariant) Evenbly Codes by Matthew Steinberg, Junyu Fan, Robert J. Harris, David Elkouss, Sebastian Feld, Alexander Jahn

“…We introduce a new class of qubit codes that we call Evenbly codes, building on a previous proposal of hyperinvariant tensor networks. Its tensor network description consists of local, non-perfect tensors describing CSS codes interspersed with Hadamard gates, placed on a hyperbolic $\{p,q\}$ geometry with even $q\geq 4$, yielding an infinitely large class of subsystem codes. …”
Get full text

DBA-RTMDet: A High-Precision and Real-Time Instance Segmentation Method for Identification of Damaged Buildings in Postearthquake UAV Imagery by Kangsan Yu, Shumin Wang, Yitong Wang, Ziying Gu, Yuanhao Wang

“…Three key modules are designed to enhance the network's feature extraction capability for damaged buildings. …”
Get full text

MICROMECHANICS MODELS OF PARTICULATE FILLED ELASTOMER AT FINITE STRAIN DEFORMATION by YANG Hui

“…This paper deals with a micromechanics-based model which is proposed for the finite strain deformation of filled elastomers based on generalized Eshelby ’s tensor and Mori-Tanaka ’s method. …”
Get full text

Mobile detection of cataracts with an optimised lightweight deep Edge Intelligent technique by Dipta Neogi, Mahirul Alam Chowdhury, Mst. Moriom Akter, Md. Ishan Arefin Hossain

“…The proposed Android app, I‐Scan, uses SDLM in the form of TensorFlow Lite for demonstration of the model in Edge devices.…”
Get full text

Almost strong zero modes at finite temperature by Niklas Tausendpfund, Aditi Mitra, Matteo Rizzi

“…We blend two established techniques for states, the Lanczos series expansion and a tensor network ansatz, uplifting them to the level of operator algebra. …”
Get full text

Critical spin models from holographic disorder by Dimitris Saraidaris, Alexander Jahn

“…In this work, we study the behavior of XXZ spin chains with such symmetries, showing that lessons learned from previous non-interacting (matchgate) tensor networks generalize to more generic Hamiltonians under holographic disorder: While the disorder breaks translation invariance, site-averaged correlations and entanglement of the disorder-free critical phase are preserved at a plateau of nonzero disorder even at large system sizes. …”
Get full text

Matrix-product unitaries: Beyond quantum cellular automata by Georgios Styliaris, Rahul Trivedi, David Perez-Garcia, J. Ignacio Cirac

“…Matrix-product unitaries (MPU) are 1D tensor networks describing time evolution and unitary symmetries of quantum systems, while their action on states by construction preserves the entanglement area law. …”
Get full text

Locally Purified Density Operators for Symmetry-Protected Topological Phases in Mixed States by Yuchen Guo, Jian-Hao Zhang, Hao-Ran Zhang, Shuo Yang, Zhen Bi

“…We propose a tensor network approach known as the locally purified density operator (LPDO) to investigate the classification and characterization of symmetry-protected topological phases in open quantum systems. …”
Get full text

Design of an intelligent AI-based multi-layer optimization framework for grid-tied solar PV-fuel cell hybrid energy systems by Prashant Nene, Dolly Thankachan

“…RL-ENN stands for Reinforcement Learning-Driven Evolutionary Neural Network, while T-STFREP is a generalized acronym for Transformer-Based Spatiotemporal Forecasting. …”
Get full text

State-Dependent Mobility Edge in Kinetically Constrained Models by Manthan Badbaria, Nicola Pancotti, Rajeev Singh, Jamir Marino, Riccardo J. Valencia-Tortora

“…Above this energy density, the bond dimension typically grows exponentially, making the simulation practically unfeasible beyond short times, as generally expected in interacting theories. We correlate the polynomial growth of the bond dimension to the presence of many nonthermal eigenstates around that energy density, a subset of which we compute via tensor networks. …”
Get full text

Ground state energy and magnetization curve of a frustrated magnetic system from real-time evolution on a digital quantum processor by Aaron Szasz, Ed Younis, Wibe Albert de Jong

“…Models of interacting many-body quantum systems that may realize new exotic phases of matter, notably quantum spin liquids, are challenging to study using even state-of-the-art classical methods such as tensor network simulations. Quantum computing provides a promising route for overcoming these difficulties to find ground states, dynamics, and more. …”
Get full text