Enhancing Marshall stability of asphalt concrete using a hybrid deep neural network and ensemble learning by Henok Desalegn Shikur, Ming-Der Yang, Yared Bitew Kebede

“…This study proposes and evaluates hybrid machine learning models, specifically integrating a deep neural network (DNN) base learner with various ensemble techniques (Random Forest, XGBoost, LightGBM, CatBoost, AdaBoost) through stacking, to enhance the accuracy and efficiency of MS prediction. …”
Get full text

LUCAT1-Mediated Competing Endogenous RNA (ceRNA) Network in Triple-Negative Breast Cancer by Deepak Verma, Sumit Siddharth, Ashutosh S. Yende, Qitong Wu, Dipali Sharma

“…Indeed, LUCAT1 silencing led to mitigated cell growth, migration, and stem-like features in TNBC. This work sheds light on the LUCAT1 ceRNA network in TNBC and implies its involvement in TNBC growth and progression.…”
Get full text

Enhanced Swine Behavior Detection with YOLOs and a Mixed Efficient Layer Aggregation Network in Real Time by Ji-hyeon Lee, Yo Han Choi, Han-sung Lee, Hyun Ju Park, Jun Seon Hong, Ji Hwan Lee, Soo Jin Sa, Yong Min Kim, Jo Eun Kim, Yong Dae Jeong, Hyun-chong Cho

Get full text

Carotid plaque segmentation and classification using MRI-based plaque texture analysis and convolutional neural network by Zakarya Hasan Ahmed Abu Alregal, Gehad Abdullah Amran, Ali A. Al-Bakhrani, Saleh Abdul Amir Mohammad, Amerah Alabrah, Lubna Alkhalil, Abdalla Ibrahim, Maryam Ghaffar, Maryam Ghaffar

Get full text

Enhancing feature selection for multi-pose facial expression recognition using a hybrid of quantum inspired firefly algorithm and artificial bee colony algorithm by Mu Panliang, Sanjay Madaan, Siddiq Ahmed Babikir Ali, Gowrishankar J., Ali Khatibi, Anas Ratib Alsoud, Vikas Mittal, Lalit Kumar, A. Johnson Santhosh

“…The evaluated features are utilized for classifying face expressions by utilizing the deep neural network model, ResNet-50. …”
Get full text

A high-resolution remote sensing land use/land cover classification method based on multi-level features adaptation of segment anything model by Hui Yang, Zhipeng Jiang, Yaobo Zhang, Yanlan Wu, Heng Luo, Peng Zhang, Biao Wang

“…To address this problem, we propose an innovative network model named multi-level feature adaptation-segment anything Model (MLFA-SAM). …”
Get full text

Performance improvement of data offloading using Krill herd optimization algorithm by Maryam Jawad Kadhim, Rasool Sadeghi, Ahmad Shaker Abdalrada, Behdad Arandian, Reihaneh Khorsand

“…Two optimization algorithms are proposed to solve the problem: the Krill Herd Algorithm (KHA) and the Greedy algorithm. The evaluation results indicate that the feature of global optima in the exploration phase of the KHA algorithm leads to finding a better location of the APs than the Greedy algorithm. …”
Get full text

HSTCN-NuSVC: A Homogeneous Stacked Deep Ensemble Learner for Classifying Human Actions Using Smartphones by Sarmela Raja Sekaran, Ying Han Pang, Ooi Shih Yin, Lim Zheng You

“…In this model, multiple enhanced TCN networks with diverse architectures are organised parallelly to capture hierarchical spatial-temporal patterns from raw inertial signals. …”
Get full text

Mitigating the Concurrent Interference of Electrode Shift and Loosening in Myoelectric Pattern Recognition Using Siamese Autoencoder Network by Ge Gao, Xu Zhang, Xiang Chen, Zhang Chen

“…A Siamese auto-encoder network (SAEN) was established to learn robust feature representations against random occurrences of both electrode shift and loosening. …”
Get full text

Surface morphology segmentation and evaluation of diamond lapping pad based on improved Mask R-CNN by Wenlong SUO, Yanfen LIN, Congfu FANG

“…The ResNet50, which serves as the feature extraction network in the backbone, is divided into five stages: Input stem and stages 1 to 4. …”
Get full text

Transcriptome Derived Artificial neural networks predict PRRC2A as a potent biomarker for epilepsy by Wayez Naqvi, Prekshi Garg, Prachi Srivastava

“…After the analysis, out of the 7 genes, the C4A gene was removed as it yielded the lowest feature selection statistics. Lastly, R Studio was used for constructing the Artificial Neural Network of the 6 identified DEGs. …”
Get full text

Hybrid Machine Learning Model for Electricity Consumption Prediction Using Random Forest and Artificial Neural Networks by Witwisit Kesornsit, Yaowarat Sirisathitkul

“…This study presents a hybrid machine learning model by integrating dimensionality reduction and feature selection algorithms with a backpropagation neural network (BPNN) to predict electricity consumption in Thailand. …”
Get full text

RL-Net: a rapid and lightweight network for detecting tiny vehicle targets in remote sensing images by Yaoyao Du, Li Chen, Xingxing Hao

“…First, MobileNetV4 is introduced to optimize initial feature extraction, significantly improving the network’s efficiency. …”
Get full text

Colony-YOLO: A Lightweight Micro-Colony Detection Network Based on Improved YOLOv8n by Meihua Wang, Junhui Luo, Kai Lin, Yuankai Chen, Xinpeng Huang, Jiping Liu, Anbang Wang, Deqin Xiao

“…Firstly, the lightweight backbone network StarNet is employed, aiming to enhance feature extraction capabilities while reducing computational complexity. …”
Get full text

Transformer and Convolutional Neural Network: A Hybrid Model for Multimodal Data in Multiclass Classification of Alzheimer’s Disease by Abdulaziz Alorf

“…The proposed network is a hybrid of two architectures, namely a transformer and a convolutional neural network (CNN). …”
Get full text

Photovoltaic Power Forecasting Based on Variational Mode Decomposition and Long Short-Term Memory Neural Network by Zhijian Hou, Yunhui Zhang, Xuemei Cheng, Xiaojiang Ye

Get full text

Robust Extrinsic Calibration for LiDAR-Camera Systems via Depth and Height Complementary Supervision Network by Chen Yaqing, Wang Huaming

“…Evaluations on the DAIR-V2X and KITTI datasets demonstrate that Co-CalibNet achieves state-of-the-art calibration performance while exhibiting greater robustness to initial misalignment. …”
Get full text

YOLO-BCD: A Lightweight Multi-Module Fusion Network for Real-Time Sheep Pose Estimation by Chaojie Sun, Junguo Hu, Qingyue Wang, Chao Zhu, Lei Chen, Chunmei Shi

Get full text

Unseen Attack Detection in Software-Defined Networking Using a BERT-Based Large Language Model by Mohammed N. Swileh, Shengli Zhang

“…Furthermore, our proposed method is specifically designed to detect previously unseen attacks, offering a solution for identifying threats that the model was not explicitly trained on. To rigorously evaluate our approach, we conducted experiments in two scenarios: one focused on detecting known attacks, achieving an accuracy, precision, recall, and F1-score of 99.96%, and another on detecting previously unseen attacks, where our model achieved 99.96% in all metrics, demonstrating the robustness and precision of our framework in detecting evolving threats, and reinforcing its potential to improve the security and resilience of SDN networks.…”
Get full text

Distributed optimization of lifetime and throughput with power consumption balance opportunistic routing in dynamic wireless sensor networks by Jian Sun, Junni Zou, Liwan Huang

“…Moreover, a fully distributed optimization solution, whose distinctive feature to the Lagrange dual approach is capable of handling the changing network, is developed to achieve joint performance optimization of objectives. …”
Get full text