Enhancing chronic wound assessment through agreement analysis and tissue segmentation by Ana C. Morgado, Rafaela Carvalho, Ana Filipa Sampaio, Maria J. M. Vasconcelos

“…The tissue segmentation model is integrated into a framework that combines a wound and reference marker detection model with a wound segmentation model to refine the predicted tissue masks. …”
Get full text

Automated Pneumothorax Segmentation with a Spatial Prior Contrast Adapter by Yiming Jia, Essam A. Rashed

“…This study aims to enhance the accuracy and robustness of pneumothorax segmentation in low-contrast chest radiographs by integrating spatial prior information and attention mechanism into the nnUNet framework. In this study, we introduce the spatial prior contrast adapter (SPCA)-enhanced nnUNet by implementing two modules. …”
Get full text

Understanding and classification of innate immune response through weighted edge representation learning with dual hypergraph transformation by Mallikharjuna Rao Sakhamuri, Shagufta Henna, Leo Creedon, Kevin Meehan, Marion McAfee

“…These results highlight WDHT's effectiveness in capturing peptide-HLA interaction dynamics, providing a robust framework.…”
Get full text

FPGA-QNN: Quantized Neural Network Hardware Acceleration on FPGAs by Mustafa Tasci, Ayhan Istanbullu, Vedat Tumen, Selahattin Kosunalp

“…Recently, convolutional neural networks (CNNs) have received a massive amount of interest due to their ability to achieve high accuracy in various artificial intelligence tasks. …”
Get full text

Enhancing FMCW Radar Gesture Classification With Physically Interpretable Data Augmentation by Alessandra Fusco, Zain Amir Zaman, Souvik Hazra, Lorenzo Servadei, Robert Wille

“…This study introduces a novel, physically interpretable data augmentation framework that improves the robustness and accuracy of hand gesture recognition using Frequency-Modulated Continuous Wave (FMCW) radar and Convolutional Neural Networks (CNN). …”
Get full text

High-Quality Sample Generation for Power System Transient Stability Assessment Based on Data-Driven Methods by Baoqin Li, Pengfei Fan, Qixin Chen, Rong Li, Kaijun Lin

“…This paper proposes a high-quality sample generation framework based on data-driven methods to build a high-quality offline samples database for TSA model training and updating. …”
Get full text

Abnormality detection in nailfold capillary images using deep learning with EfficientNet and cascade transfer learning by Mona Ebadi Jalal, Omar S. Emam, Cristián Castillo-Olea, Begoña García-Zapirain, Adel Elmaghraby

“…This study introduces a robust framework utilizing cascade transfer learning based on EfficientNet-B0 to differentiate between normal and abnormal cases within NFC images. …”
Get full text

TCN-MAML: A TCN-Based Model with Model-Agnostic Meta-Learning for Cross-Subject Human Activity Recognition by Chih-Yang Lin, Chia-Yu Lin, Yu-Tso Liu, Yi-Wei Chen, Hui-Fuang Ng, Timothy K. Shih

“…To address these sensor-related challenges, we propose TCN-MAML, a novel framework that integrates temporal convolutional networks (TCN) with model-agnostic meta-learning (MAML) for efficient cross-subject adaptation in data-scarce conditions. …”
Get full text

Modified Whale Optimization Algorithm for Multiclass Skin Cancer Classification by Abdul Majid, Masad A. Alrasheedi, Abdulmajeed Atiah Alharbi, Jeza Allohibi, Seung-Won Lee

“…To address these challenges, this paper proposes an innovative deep learning-based framework that integrates an ensemble of two pre-trained convolutional neural networks (CNNs), SqueezeNet and InceptionResNet-V2, combined with an improved Whale Optimization Algorithm (WOA) for feature selection. …”
Get full text

Explainable deep learning for age and gender estimation in dental CBCT scans using attention mechanisms and multi task learning by Najmeh Pishghadam, Rasool Esmaeilyfard, Maryam Paknahad

“…This study aims to develop a multi-task deep learning framework that enhances both accuracy and explainability in CBCT-based age estimation and gender classification using attention mechanisms. …”
Get full text

Research on channel estimation based on joint perception and deep enhancement learning in complex communication scenarios by Xin Liu, Shanghong Zhao, Yanxia Liang, Shahid Karim

“…The framework initially acquires the received signal by converting the guide-frequency symbols at the transmitter into time-domain sequences to be transmitted, and after propagating through the direct channel and the IRS reflection channel, processes the data at the receiver. …”
Get full text

Ground Segmentation for LiDAR Point Clouds in Structured and Unstructured Environments Using a Hybrid Neural–Geometric Approach by Antonio Santo, Enrique Heredia, Carlos Viegas, David Valiente, Arturo Gil

“…This paper introduces a hybrid framework that synergizes multi-resolution polar discretization with sparse convolutional neural networks (SCNNs) to address these challenges. …”
Get full text

Deteksi Dan Klasifikasi Hama Potato Beetle Pada Tanaman Kentang Menggunakan YOLOV8 by Daniel Geoffrey Manurung, Mohammad Ryan Pinasthika, Muhammad Azka Obila Vasya, Rania Aprilia Dwi Setya Putri, Agustinus Parasian Tampubolon, Rakan Fadhil Prayata, Septia Khoirin Nisa, Novanto Yudistira

“…Data yang digunakan untuk pelatihan adalah menggunakan framework PyTorch yang telah dipecah menjadi data training, data validation, dan data test. …”
Get full text

An Intelligent Path Planning System for Urban Airspace Monitoring: From Infrastructure Assessment to Strategic Optimization by Qianyu Liu, Wei Dai, Zichun Yan, Claudio J. Tessone

“…This study proposes a unified framework that integrates infrastructure readiness assessment with Deep Reinforcement Learning (DRL)-based UAV path planning. …”
Get full text

An Anomaly Detection Method for Industrial System Cybersecurity Based on GGL-WAVE-CNN by Bing Zou, Ke jun Zhang, Xin Ying Yu, Yu han Jin, Jun Wang, Ling yu Liu

“…This paper introduces a novel two-level anomaly detection framework that combines the generalized graph Laplacian (GGL), wavelet decomposition (WAVE), and an enhanced convolutional neural network (CNN). …”
Get full text

UAV Small Target Detection Model Based on Dual Branches and Adaptive Feature Fusion by Guogang Wang, Mingxing Gao, Yunpeng Liu

“…The model first constructs a small target detection framework with dual branches to improve the detection accuracy while reducing the number of parameters. …”
Get full text

Efficient slice anomaly detection network for 3D brain MRI Volume. by Zeduo Zhang, Yalda Mohsenzadeh

“…We propose a framework called Simple Slice-based Network (SimpleSliceNet), which utilizes a model pre-trained on ImageNet and fine-tuned on a separate MRI dataset as a 2D slice feature extractor to reduce computational cost. …”
Get full text

Residual Network with Triple-Attention Mechanisms for Knee Osteoarthritis Severity Classification by Tian Hongyu, Cao Wenming, Ran Qiyu

“…The proposed architec- ture demonstrated statistically improvements over other existing convolutional networks (VGG-19, Dense- Net-121, GoogleNet, etc.).…”
Get full text

Semi-supervised gearbox fault diagnosis under variable working conditions based on masked contrastive learning by ZHANG Huiyun, ZUO Fangjun, LI Hang, YU Xi

“…Then, a contrastive learning framework was constructed with the optimization goal of maximizing the similarity between features of different masked instances. …”
Get full text

A Deep Learning Inversion Method for 3D Temperature Structures in the South China Sea with Physical Constraints by Dongcan Xu, Yahao Liu, Yuan Kong

“…The proposed approach advances ocean remote sensing by synergizing data-driven learning with thermodynamic principles, offering a robust framework for understanding the South China Sea’s thermal variability.…”
Get full text