Learning Architecture for Brain Tumor Classification Based on Deep Convolutional Neural Network: Classic and ResNet50 by Rabei Raad Ali, Noorayisahbe Mohd Yaacob, Marwan Harb Alqaryouti, Ala Eddin Sadeq, Mohamed Doheir, Musab Iqtait, Eko Hari Rachmawanto, Christy Atika Sari, Siti Salwani Yaacob

“…In this paper, we investigate the application of Convolutional Neural Networks (CNN) as a powerful tool for enhancing diagnostic accuracy using a Magnetic Resonance Imaging (MRI) dataset. …”
Get full text

Revolutionizing Clear-Sky Humidity Profile Retrieval with Multi-Angle-Aware Networks for Ground-Based Microwave Radiometers by Yinshan Yang, Zhanqing Li, Jianping Guo, Yuying Wang, Hao Wu, Yi Shang, Ye Wang, Langfeng Zhu, Xing Yan

“…Feature analysis and evaluations of the “multi-angle-aware” module indicate that optimal RH retrieval performance is achieved by combining zenith-angle BTs with oblique angles at 30° and 19.2°. …”
Get full text

Diagnosis and activity prediction of SLE based on serum Raman spectroscopy combined with a two-branch Bayesian network by Qianxi Xu, Qianxi Xu, Qianxi Xu, Xue Wu, Xue Wu, Xue Wu, Xinya Chen, Ziyang Zhang, Jinrun Wang, Jinrun Wang, Zhengfang Li, Zhengfang Li, Zhengfang Li, Xiaomei Chen, Xiaomei Chen, Xiaomei Chen, Xin Lei, Xin Lei, Zhuoyu Li, Zhuoyu Li, Zhuoyu Li, Mengsi Ma, Mengsi Ma, Mengsi Ma, Chen Chen, Lijun Wu, Lijun Wu

“…However, applying spectral data in the classification and activity assessment of SLE reveals a high degree of spectral overlap and significant challenges in feature extraction. Consequently, this paper presents a rapid and accurate method for disease diagnosis and activity assessment, which has significant clinical implications for achieving early diagnosis of the disease and improving patient prognosis.MethodsIn this study, a two-branch Bayesian network (DBayesNet) based on Raman spectroscopy was developed for the rapid identification of SLE. …”
Get full text

Measuring what matters: Building impact pathways to actionable information for the weADAPT platform by S. Bharwani, K. Williamson, R. Butterfield

“…These findings informed a recent platform upgrade (2022–2024), the refinement of weADAPT’s Theory of Change, and the development of a tailored monitoring, evaluation, and learning (MEL) framework featuring custom progress indicators. …”
Get full text

Performance Comparison of Facial Emotion Recognition: Introducing a Model within the Driver Assistance Framework based on Deep Learning with LBP Feature Extraction for In-Vehicle A... by Ehsan Ghasemi, Seyyed Mohammad Razavi, Sajad Mohamadzadeh

“…Using 3 RGB channels, the extracted features from these three regions are fed into RessNet-50 and EfficientNet deep networks. …”
Get full text

SED-NET: Real-Time Suspicious Event Detection via Deep Learning-Based Di-Stream Neural Network by D. Siva Senthil, T. S. Sivarani

“…The weighted Average Fusion method is used to combine pose and motion features to classify suspicious activities using the Simplified Spiking Neural Network (SSNN). …”
Get full text

A Hybrid CNN-LSTM Model With Attention Mechanism for Improved Intrusion Detection in Wireless IoT Sensor Networks by Pendukeni Phalaagae, Adamu Murtala Zungeru, Abid Yahya, Boyce Sigweni, Selvaraj Rajalakshmi

“…Additionally, the improved dynamic PSO algorithm optimizes feature selection in real time, enhancing classification accuracy and adaptability to evolving IoT network threats. …”
Get full text

Non-Uniformity Correction of Spatial Object Images Using Multi-Scale Residual Cycle Network (CycleMRSNet) by Chunfeng Jiang, Zhengwei Li, Yubo Wang, Tao Chen

“…This design improves the efficiency of feature extraction and increases the focus on multi-scale information in high-dimensional feature maps, enabling the network to more comprehensively understand and concentrate on key areas within images, thereby capably correcting non-uniform backgrounds. …”
Get full text

CXR-Seg: A Novel Deep Learning Network for Lung Segmentation from Chest X-Ray Images by Sadia Din, Muhammad Shoaib, Erchin Serpedin

“…In this context, we propose a novel architecture named CXR-Seg, tailored for semantic segmentation of lungs from chest X-ray images. The proposed network mainly consists of four components, including a pre-trained EfficientNet as an encoder to extract feature encodings, a spatial enhancement module embedded in the skip connection to promote the adjacent feature fusion, a transformer attention module at the bottleneck layer, and a multi-scale feature fusion block at the decoder. …”
Get full text

Comparative evaluation of titanium-prepared platelet-rich fibrin with and without herbal extract: A histological study by Gummaluri Shiva Shankar, Gurumoorthy Kaarthikeyan, Damera Trinath Kishore, Boddeda Anusha, Kodem Tejaswi, Lekkala Sivaram

“…Regarding the fibrin network features (dense vs. loose), no statistical significance was found among the studied groups (p = 0.172). …”
Get full text

Design of advanced intrusion detection systems based on hybrid machine learning techniques in hierarchically wireless sensor networks by Gebrekiros Gebreyesus Gebremariam, J. Panda, S. Indu

“…Different attack detection metrics were compared against various benchmark datasets to evaluate the quality of this work. The proposed system is efficient in simulations for feature extraction and route discovery and detection attacks achieving an accuracy of 99.46%.…”
Get full text

An explainable AI-driven transformer model for spoofing attack detection in Internet of Medical Things (IoMT) networks by Mohammad A. Alsharaiah, Mohammed Amin Almaiah, Rami Shehab, Mansour Obeidat, Fuad Ali El-Qirem, Theyazn Aldhyani

“…The core of our novel model is a Transformer neural network, enhanced with a custom attention mechanism to improve feature extraction and classification accuracy. …”
Get full text

A Scalable Hybrid Autoencoder–Extreme Learning Machine Framework for Adaptive Intrusion Detection in High-Dimensional Networks by Anubhav Kumar, Rajamani Radhakrishnan, Mani Sumithra, Prabu Kaliyaperumal, Balamurugan Balusamy, Francesco Benedetto

“…The rapid expansion of network environments has introduced significant cybersecurity challenges, particularly in handling high-dimensional traffic and detecting sophisticated threats. …”
Get full text

A Novel Bearing Fault Diagnosis Method Based on Improved Convolutional Neural Network and Multi-Sensor Fusion by Zhongyao Wang, Xiao Xu, Dongli Song, Zejun Zheng, Weidong Li

“…To address the issue that the limited information contained in the single-source signal of the bearing leads to the limited accuracy of the single-source fault diagnosis method, a multi-sensor fusion fault diagnosis method is proposed to improve the reliability of bearing fault diagnosis. Firstly, the feature extraction process of the convolutional neural network (CNN) is improved based on the theory of variational Bayesian inference, which forms the variational Bayesian inference convolutional neural network (VBICNN). …”
Get full text

DeeWaNA: An Unsupervised Network Representation Learning Framework Integrating Deepwalk and Neighborhood Aggregation for Node Classification by Xin Xu, Xinya Lu, Jianan Wang

“…Extensive evaluations on real-world networks demonstrate that DeeWaNA outperforms four widely used unsupervised network representation learning methods, underscoring its effectiveness and broader applicability.…”
Get full text

Optimized predictive maintenance for streaming data in industrial IoT networks using deep reinforcement learning and ensemble techniques by K. Varalakshmi, J. Kumar

“…Abstract Predictive maintenance in Industrial IoT (IIoT) networks faces challenges due to dynamic conditions, device heterogeneity, and evolving data patterns. …”
Get full text

Remaining Useful Life Prediction Across Conditions Based on a Health Indicator-Weighted Subdomain Alignment Network by Zhiqing Xu, Christopher W. K. Chow, Md. Mizanur Rahman, Raufdeen Rameezdeen, Yee Wei Law

“…This paper proposes a novel model, called the health indicator-weighted subdomain alignment network (HIWSAN), which first learns feature representations at multiple scales, then constructs health indicators as temporal weights, and finally performs subdomain-level alignment. …”
Get full text

Performance Analysis of MobileNetV3-based Convolutional Neural Network for Facial Skin Disorder Classification by Herimanto, Arie Satia Dharma, Junita Amalia, David Largo, Christin Adelia Pratiwi Sihite

Get full text

Drug repositioning framework using embedding drug-protein-disease similarities with graph convolution network and ensemble learning by Hanaa Torkey, Heba El-Behery, Abdel-Fattah Atti, Nawal El-Fishawy

“…The approach extracts embedding feature vectors of drugs and targets from a heterogeneous multi-source network to predict unknown drug-target interactions (DTIs). …”
Get full text

Vibration Signal-Based Fault Diagnosis of Rotary Machinery Through Convolutional Neural Network and Transfer Learning Method by Chirag Mongia, Shankar Sehgal

“…After achieving high classification performance at source domain conditions, the performance of the model is re-evaluated by applying it to the Case Western Reserve University (CWRU) dataset as the target domain through the TL method. short-time Fourier transform is employed for signal preprocessing, enhancing feature extraction and model performance. …”
Get full text