Assessment of Artificial Intelligence Models for Developing Single-Value and Loop Rating Curves by Majid Niazkar, Mohammad Zakwan

“…As a result, the rating curves of eight different rivers were developed using the conventional method, evolutionary algorithm (EA), the modified honey bee mating optimization (MHBMO) algorithm, artificial neural network (ANN), MGGP, and the hybrid MGGP-GRG technique. …”
Get full text

Early Diagnosis and Severity Assessment of Weligama Coconut Leaf Wilt Disease and Coconut Caterpillar Infestation Using Deep Learning-Based Image Processing Techniques by Samitha Vidhanaarachchi, Janaka L. Wijekoon, W. A. Shanaka P. Abeysiriwardhana, Malitha Wijesundara

“…This paper presents a study conducted in Sri Lanka, demonstrating the effectiveness of employing transfer learning-based Convolutional Neural Network (CNN) and Mask Region-based-CNN (Mask R-CNN) to identify WCWLD and CCI at their early stages and to assess disease progression. …”
Get full text

Bioinsecticide Production from Cigarette Wastes by Badhane Gudeta, Solomon K, M. Venkata Ratnam

“…In addition, artificial neural network (ANN) studies with MATLAB were used to accurately forecast extraction yield. …”
Get full text

Unfolder: fast localization and image rectification of a document with a crease from folding in half by A.M. Ershov, D.V. Tropin, E.E. Limonova, D.P. Nikolaev, V.V. Arlazarov

“…The Unfolder algorithm allowed for a recognition error rate of 0.33, which is better than the advanced neural network methods DocTr (0.44) and DewarpNet (0.57). …”
Get full text

Embedded Rough-Neck Helmholtz Resonator Low-Frequency Acoustic Attenuator by Xianming Sun, Tao Yu, Lipeng Wang, Yunshu Lu, Changzheng Chen

“…A back-propagation (BP) neural network models and predicts how structural parameters impact the acoustic transmission coefficient, elucidating the effects of geometric variations. …”
Get full text

High-Dose Neural Stem/Progenitor Cell Transplantation Increases Engraftment and Neuronal Distribution and Promotes Functional Recovery in Rats after Acutely Severe Spinal Cord Inju... by Taoyang Yuan, Qian Liu, Jie Kang, Hua Gao, Songbai Gui

“…At 8 weeks postgrafting, subjects that received the higher cell dose exhibited abundant nerve regeneration, extensive neuronal distribution, increased proportions of neurons and oligodendrocytes, and nascent functional neural network formation in the lesion area. Notably, a significant functional recovery was also observed. …”
Get full text

Apply a deep learning hybrid model optimized by an Improved Chimp Optimization Algorithm in PM2.5 prediction by Ming Wei, Xiaopeng Du

“…Subsequently, a one-dimensional convolutional neural network (1DCNN) with efficient feature extraction capability is used to extract dynamic features from sequences. …”
Get full text

STeInFormer: Spatial–Temporal Interaction Transformer Architecture for Remote Sensing Change Detection by Xiaowen Ma, Zhenkai Wu, Mengting Ma, Mengjiao Zhao, Fan Yang, Zhenhong Du, Wei Zhang

“…Convolutional neural networks and attention mechanisms have greatly benefited remote sensing change detection (RSCD) because of their outstanding discriminative ability. …”
Get full text

Prediction of Grade Classification of Rock Burst Based on PCA-SSA-PNN Architecture by Zhenyi Wang, Yalei Wang, Xiaoliang Jin

“…In order to estimate the risk grades of rock burst, an integrated method combining principal component analysis (PCA) and sparrow search algorithm (SSA) with probabilistic neural network (PNN) was proposed. Considering that the in situ stress of rock mass, the strength of rock, and the strength of rock mass are the key influencing factors of rock bursts, the maximum in situ stress σmax, maximum tangential stress σθ, rock strength σci, rock mass strength σcm, and three rock burst evaluation indexes (σθ/σci, σci/σmax, and σcm/σmax) were selected to constitute the rock burst grade evaluation index system. …”
Get full text

Pre-trained artificial intelligence-aided analysis of nanoparticles using the segment anything model by Gabriel A. A. Monteiro, Bruno A. A. Monteiro, Jefersson A. dos Santos, Alexander Wittemann

“…The automated segmentation of whole particles, as well as their individual subdivisions, is investigated using the Segment Anything Model, which is based on a pre-trained neural network. The subdivisions of the particles are organized into sets, which presents a novel approach in this field. …”
Get full text

Enhancing prostate cancer segmentation in bpMRI: Integrating zonal awareness into attention-guided U-Net by Chao Wei, Zheng Liu, Yibo Zhang, Lianhui Fan

“…First, pretraining a convolutional neural network (CNN)-based attention-guided U-Net model for segmenting the region of interest which is carried out in the prostate zone. …”
Get full text

Research on the Spread Path and Evolution Causes of Oral Language in the Digital Era by Zhiqiang Li

“…At the same time, according to the hierarchical characteristics of neural networks, a heterodimensional multifactor neural evolution algorithm HD-MFEA neuro-evolution is proposed to train multiple neural networks simultaneously. …”
Get full text

Identification and Characterization of Novel Perivascular Adventitial Cells in the Whole Mount Mesenteric Branch Artery Using Immunofluorescent Staining and Scanning Confocal Micro... by Chandra Somasundaram, Rahul K. Nath, Richard D. Bukoski, Debra I. Diz

“…In summary, CGRP, and NCAM-containing neural cells in the perivascular adventitia also express palladin and CaSR, and coexpress Gap-43 which may participate in response to stress/injury and vasodilator mechanisms as part of a perivascular sensory neural network.…”
Get full text

ADA-NAF: Semi-Supervised Anomaly Detection Based on the Neural Attention Forest by Andrey Ageev, Andrei Konstantinov, Lev Utkin

“…In this study, we present a novel model called ADA-NAF (Anomaly Detection Autoencoder with the Neural Attention Forest) for semi-supervised anomaly detection that uniquely integrates the Neural Attention Forest (NAF) architecture which has been developed to combine a random forest classifier with a neural network computing attention weights to aggregate decision tree predictions. …”
Get full text

SiameseNet based on multiple instance learning for accurate identification of the histological grade of ICC tumors by Zhizhan Fu, Fazhi Feng, Xingguang He, Tongtong Li, Xiansong Li, Jituome Ziluo, Zixing Huang, Jinlin Ye

“…Timely and accurate identification of ICC histological grade is critical for guiding clinical diagnosis and treatment planning.MethodWe proposed a dual-branch deep neural network (SiameseNet) based on multiple-instance learning and cross-attention mechanisms to address tumor heterogeneity in ICC histological grade prediction. …”
Get full text

Indoor Positioning System in Learning Approach Experiments by Dodo Zaenal Abidin, Siti Nurmaini, Erwin, Errissya Rasywir, Yovi Pratama

“…The test was conducted with a deep learning approach using a deep neural network (DNN) algorithm. The DNN method can estimate the actual space and get better position results, whereas machine learning methods such as the DNN algorithm can handle more effectively large data and produce more accurate data. …”
Get full text

Multi-Resolution Multimedia QoE Models for IPTV Applications by Prasad Calyam, Prashanth Chandrasekaran, Gregg Trueb, Nathan Howes, Rajiv Ramnath, Delei Yu, Ying Liu, Lixia Xiong, Daoyan Yang

“…In this paper, we develop psycho-acoustic-visual models that can predict user QoE of multimedia applications in real time based on online network status measurements. Our models are neural network based and cater to multi-resolution IPTV applications that include QCIF, QVGA, SD, and HD resolutions encoded using popular audio and video codec combinations. …”
Get full text

Detecting Subtle Cyberattacks on Adaptive Cruise Control Vehicles: A Machine Learning Approach by Tianyi Li, Mingfeng Shang, Shian Wang, Raphael Stern

“…The proposed approach is observed to outperform contemporary neural network models in detecting irregular driving patterns of ACC vehicles.…”
Get full text

Distance Measurement and Error Compensation of High-Speed Coaxial Rotor Blades Based on Coded Ultrasonic Ranging by Yaohuan Lu, Shan Zhang, Wenchuan Hu, Zhen Qiu, Zurong Qiu, Yongqiang Qiu

“…The measurement error characteristics under different trigger phases and different rotational speeds are studied, and the error model is fitted by the back-propagation neural network method. After compensation, the vertical distance measurement errors are within ±2 mm in the range of 100–1000 mm under the condition that the rotational speed of the blade is up to 1020 RPM. …”
Get full text

Real-Time Quality Monitoring and Anomaly Detection for Vision Sensors in Connected and Autonomous Vehicles by Elena Politi, Charalampos Davalas, Christos Chronis, George Dimitrakopoulos, Dimitrios Michail, Iraklis Varlamis

“…On this basis we adopt a two-stage approach to validate the performance of the proposed methods against a baseline Convolutional Neural Network (CNN) in a controlled low-criticality environment, as well as in more complex real-world scenarios. …”
Get full text