A Hybrid Deep Learning Approach for Skin Lesion Segmentation With Dual Encoders and Channel-Wise Attention by Asaad Ahmed, Guangmin Sun, Anas Bilal, Yu Li, Shouki A. Ebad

Get full text

Ultra-short-term Multi-region Power Load Forecasting Based on Spearman-GCN-GRU Model by Junying WU, Xin LU, Hong LIU, Bin ZHANG, Shouliang CHAI, Yunchun LIU, Jianan WANG

“…And then, the graph convolutional network (GCN) and gated recurrent unit (GRU) are used to respectively extract the spatial and temporal features from the data. …”
Get full text

Enhanced Signal-to-Noise Ratio Estimation in Optical Fiber Communications: A Pilot-Based Approach by Mohamed Al-Nahhal, Ibrahim Al-Nahhal, Sunish Kumar Orappanpara Soman, Octavia A. Dobre

“…This paper presents two innovative, pilot-assisted, neural network (NN)-based signal-to-noise ratio (SNR) estimators for application in optical fiber communications. …”
Get full text

Exploration of the Ignition Delay Time of RP-3 Fuel Using the Artificial Bee Colony Algorithm in a Machine Learning Framework by Wenbo Liu, Zhirui Liu, Hongan Ma

“…Ignition delay time (IDT) is a critical parameter for evaluating the autoignition characteristics of aviation fuels. …”
Get full text

A Deep Learning-Based Ensemble Framework for Robust Android Malware Detection by Sainag Nethala, Pronoy Chopra, Khaja Kamaluddin, Shahid Alam, Soltan Alharbi, Mohammad Alsaffar

“…The extracted byte data is converted into 1D vectors and reshaped into 2D grayscale images, enabling efficient feature learning through CNNs. The proposed ensemble of CNN-based models undergoes comprehensive training, validation, and evaluation, demonstrating superior performance compared to existing approaches. …”
Get full text

Precision and efficiency in skin cancer segmentation through a dual encoder deep learning model by Asaad Ahmed, Guangmin Sun, Anas Bilal, Yu Li, Shouki A. Ebad

“…DuaSkinSeg leverages a pre-trained MobileNetV2 for efficient local feature extraction. Subsequently, a Vision Transformer-Convolutional Neural Network (ViT-CNN) encoder-decoder architecture extracts higher-level features focusing on long-range dependencies. …”
Get full text

RQPool: A Novel Multi-Branch Graph-Level Anomaly Detection by Aaron Alex Philip, Ziad Kobti

“…Moreover, existing Graph Neural Network (GNN) algorithms focus primarily on spatial domain features while neglecting spectral properties. …”
Get full text

Towards scalable medical image compression using hybrid model analysis by Shunlei Li, Jiajie Lu, Yingbai Hu, Leonardo S. Mattos, Zheng Li

“…Meanwhile, Convolutional Neural Networks (CNN) have shown promising results for medical image compression. …”
Get full text

Variational Methods in Optical Quantum Machine Learning by Marco Simonetti, Damiano Perri, Osvaldo Gervasi

“…The selected dataset is a set of 2D points creating two interleaved semicircles and is based on a 2D binary classification generator, which aids in evaluating the performance of particular methods. The two coordinates of each unique point, <inline-formula> <tex-math notation="LaTeX">$x_{1}$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$x_{2}$ </tex-math></inline-formula>, serve as the features since they present two disparate data sets in a two-dimensional representation space. …”
Get full text

LatentResNet: An Optimized Underwater Fish Classification Model with a Low Computational Cost by Muhab Hariri, Ercan Avsar, Ahmet Aydın

Get full text

System-Level Assessment of Ka-Band Digital Beamforming Receivers and Transmitters Implementing Large Thinned Antenna Array for Low Earth Orbit Satellite Communications by Giovanni Lasagni, Alessandro Calcaterra, Monica Righini, Giovanni Gasparro, Stefano Maddio, Vincenzo Pascale, Alessandro Cidronali, Stefano Selleri

Get full text

Quantification of Flavonoid Contents in Holy Basil Using Hyperspectral Imaging and Deep Learning Approaches by Apichat Suratanee, Panita Chutimanukul, Kitiporn Plaimas

Get full text

Advanced deep learning and transfer learning approaches for breast cancer classification using advanced multi-line classifiers and datasets with model optimization and interpretabi... by Xiang Zhang, Wei Shao, Ming Qiu, Chenglin Xiao, Liming Ma

“…This study evaluated machine learning (ML) models on the Wisconsin Breast Cancer Dataset (WBCD), refined to 554 unique instances after addressing 5% missing values via mean imputation, removing 15 duplicates, and normalizing features with Min–Max scaling. …”
Get full text

BrainTumNet: multi-task deep learning framework for brain tumor segmentation and classification using adaptive masked transformers by Cheng Lv, Xu-Jun Shu, Xu-Jun Shu, Quan Liang, Jun Qiu, Zi-Cheng Xiong, Jing bo Ye, Shang bo Li, Cheng Qing Liu, Jing Zhen Niu, Sheng-Bo Chen, Hong Rao

“…Recently, deep learning technologies, particularly Convolutional Neural Networks (CNN), have achieved breakthrough advances in medical image analysis, offering a new paradigm for automated precise diagnosis. …”
Get full text

A Robust Deep Learning Framework for Mitigating Label Noise With Dual Selective Attention by Hasnain Hyder, Gulsher Baloch, Amreen Batool, Yong-Woon Kim, Yung-Cheol Byun

“…DSAN was evaluated alongside four baseline models Visual Geometry Group Network (VGG16), Convolutional Neural Network (CNN), Artificial Neural Network (ANN), and ResNet-50 on three datasets, with label noise introduced at 0%, 5%, 10%, 15%, and 20% to simulate real-world mislabeling scenarios. …”
Get full text

MCR-PFNet: A novel InSAR interferometric phase filtering method for complex noise and large gradient deformations by Shuai Wang, Yu Chen, Kaiwen Ding, Yandong Gao, Kun Tan, Peijun Du

Get full text

A hybrid deep learning framework for skin disease localization and classification using wearable sensors by Xiaoling Zhao, Huixin Zhang, Qian Zheng, Caihong Jing

“…Specifically, a fully convolutional residual neural network (FCRN) is employed to extract local features from high-resolution skin images captured via wearable sensors, using a patch-level training approach. …”
Get full text

Enhanced Conditional GAN for High-Quality Synthetic Tabular Data Generation in Mobile-Based Cardiovascular Healthcare by Malak Alqulaity, Po Yang

“…This paper presents an enhanced Conditional Generative Adversarial Network (GAN) architecture designed for generating high-quality synthetic tabular data, with a focus on cardiovascular disease datasets that encompass mixed data types and complex feature relationships. …”
Get full text

Histopathological-based brain tumor grading using 2D-3D multi-modal CNN-transformer combined with stacking classifiers by Naira Elazab, Fahmi Khalifa, Wael Gab Allah, Mohammed Elmogy

“…An efficient method of learning hierarchical patterns within the tissue is the 2D-3D hybrid convolution neural network (CNN), which extracts contextual and spatial features. …”
Get full text

Analyzing the Efficacy of Computer-Aided Detection in Cerebral Aneurysm Diagnosis Using MRI Modality: A Review by Keerthi A. S. Pillai, Preena K. P., Madhu S. Nair

“…The research papers selected for this review focus on research utilizing TOF MRA as the imaging modality and emphasize computer-aided detection through both traditional and deep learning techniques, with a particular emphasis on Convolutional Neural Networks (CNNs). CNNs have proven to be a crucial component in improving the accuracy and efficiency of aneurysm detection by automatically learning features from raw imaging data, bypassing the need for manual feature extraction. …”
Get full text