Fast Reverse Design of 4D‐Printed Voxelized Composite Structures Using Deep Learning and Evolutionary Algorithm by Mengtao Wang, Zaiyang Liu, Hidemitsu Furukawa, Zhuo Li, Yifei Ge, Yifan Xu, Zhe Qiu, Yang Tian, Zhongkui Wang, Ren Xu, Lin Meng

“…Furthermore, a progressive evolutionary algorithm (PEA) is proposed by integrating the DL model to construct a DL‐PEA framework. This framework supports rapid reverse engineering of the desired shape, and the average design time for specified target shapes is reduced to ≈3.04 s. …”
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A multi-patch-based deep learning model with VGG19 for breast cancer classifications in the pathology images by Anitha Ponraj, Palanigurupackiam Nagaraj, Duraisamy Balakrishnan, Parvathaneni Naga Srinivasu, Jana Shafi, Wonjoon Kim, Muhammad Fazal Ijaz

“…This study introduces a novel method, MPa-DCAE, which uses a multi-patch-based deep convolutional auto-encoder (DCAE) framework combined with VGG19 to detect and classify breast cancer in histopathology images. …”
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IoTShield: Defending IoT Systems Against Prevalent Attacks Using Programmable Networks by Mah-Rukh Fida, Azza H. Ahmed, Ameer Shakayb Arsalaan

“…This paper presents <monospace>IoTShield</monospace>, a Software Defined Network (SDN) based dual-stage defensive framework, designed to mitigate different flow-based attacks targeting IoT systems. …”
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GazeMap: Dual-Pathway CNN Approach for Diagnosing Alzheimer’s Disease from Gaze and Head Movements by Hyuntaek Jung, Shinwoo Ham, Hyunyoung Kil, Jung Eun Shin, Eun Yi Kim

“…This study proposes a novel AD detection framework integrating gaze and head movement analysis via a dual-pathway convolutional neural network (CNN). …”
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VMKLA-UNet: vision Mamba with KAN linear attention U-Net by Chenhong Su, Xuegang Luo, Shiqing Li, Li Chen, Juan Wang

“…Abstract In the domain of medical image segmentation, while convolutional neural networks (CNNs) and Transformer-based architectures have attained notable success, they continue to face substantial challenges. …”
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Federated learning applications in soil spectroscopy by Giannis Gallios, Nikolaos Tsakiridis, Nikolaos Tziolas

“…The results show that the FL framework can match, and in some cases exceed, the performance of centralized models, particularly when using IID data. …”
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Efficient Generative-Adversarial U-Net for Multi-Organ Medical Image Segmentation by Haoran Wang, Gengshen Wu, Yi Liu

“…This paper introduces a novel medical image-segmentation framework named Efficient Generative-Adversarial U-Net (EGAUNet), designed to facilitate rapid and accurate multi-organ labeling. …”
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Toward Adaptive Unsupervised and Blind Image Forgery Localization with ViT-VAE and a Gaussian Mixture Model by Haichang Yin, KinTak U, Jing Wang, Wuyue Ma

“…Recently, several unsupervised approaches based on the variational autoencoder (VAE) framework have been proposed for forged pixel detection. …”
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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. …”
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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. …”
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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.…”
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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. …”
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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). …”
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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. …”
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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. …”
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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. …”
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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. …”
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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. …”
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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. …”
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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. …”
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