Deep Learning-Based Classification of Canine Cataracts from Ocular B-Mode Ultrasound Images by Sanghyeon Park, Seokmin Go, Seonhyo Kim, Jaeho Shim

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An Ensemble Learning Approach for Glaucoma Detection in Retinal Images by Marwah M. Mahdi, Mohammed Abdulkreem Mohammed, Haider Al-Chalibi, Bashar S. Bashar, Hayder Adnan Sadeq, Talib Mohammed Jawad Abbas

“…In this paper, we propose a deep learning-based framework for the detection of glaucoma based on retinal images. …”
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Enhancing Medical Image Classification with Unified Model Agnostic Computation and Explainable AI by Elie Neghawi, Yan Liu

“…<i>Objective</i>: This paper applies the Unified Model Agnostic Computation (UMAC) framework specifically to the medical domain to demonstrate its utility in this critical area. …”
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Multi-species Fish Identification using Hybrid DeepCNN with Refined Squeeze and Excitation Architecture by Jansi Rani Sella Veluswami, Nivetha Panneerselvam

“…To achieve this, a hybrid framework using deep learning is proposed on a large-scale dataset and implemented transfer learning for a small-scale dataset. …”
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Integrating Data Mining, Deep Learning, and Gene Ontology Analysis for Gene Expression-Based Disease Diagnosis Systems by Sergii Babichev, Igor Liakh, Jiri Skvor

“…It outlines a conceptual framework and provides a block diagram of the stepwise procedure for analyzing gene expression data, aiming to enhance the accuracy and objectivity of disease diagnosis. …”
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PIONet: A Positional Encoding Integrated Onehot Feature-Based RNA-Binding Protein Classification Using Deep Neural Network by Mahmood A. Rashid, Mayank Chaturvedi, Kuldip K. Paliwal

“…Here we present PIONet, a deep learning method based on a convolutional neural network (CNN) that accurately classifies RBPs. …”
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A novel seismic inversion method based on multiple attributes and machine learning for hydrocarbon reservoir prediction in Bohai Bay Basin, Eastern China by Zongbin Liu, Jianmin Zhu, Bo Tian, Rui Zhang, Yongheng Fu, Yuan Liu, Lixin Wang

“…In this study, we take the X Oilfield in Eastern China as an example, adopted a novel approach combining spectral decomposition with convolutional neural networks (CNNs) within a genetic algorithm (GA) framework for inversion. …”
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Two-Step Contrast Source Learning Method for Electromagnetic Inverse Scattering Problems by Anran Si, Miao Wang, Fuping Fang, Dahai Dai

“…To overcome these issues, we propose a two-step contrast source learning approach, cascading convolutional neural networks (CNNs) into the inversion framework, to tackle 2D full-wave EM-ISPs. …”
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Machine Learning for Chronic Kidney Disease Detection from Planar and SPECT Scintigraphy: A Scoping Review by Dunja Vrbaški, Boban Vesin, Katerina Mangaroska

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A hybrid inception-dilated-ResNet architecture for deep learning-based prediction of COVID-19 severity by Ali Khalili Fakhrabadi, Mehdi Jafari Shahbazzadeh, Nazanin Jalali, Mahdiyeh Eslami

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Asymmetric Network Based on CNN and Attention Mechanisms for Thyroid Nodule Segmentation by Zhiheng Zhang, Lin Li, Cheng Zhao, Peng Ren, Ran Zhang

“…The framework introduces an Efficient Convolutional Block (ECB) to extract high-level semantic features, constructs a Convolutional Modulation Module (CMM) to enhance feature representation, and incorporates a Spatial Semantic Enhancement Module (SSEM) to optimize detail reconstruction. …”
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Graph Neural Network Classification in EEG-Based Biometric Identification: Evaluation of Functional Connectivity Methods Using Time-Frequency Metric by Roghaieh Ashenaei, Ali Asghar Beheshti Shirazi

“…We propose a realistic experimental framework, recording training and testing signals in separate sessions under varying states, using only 19 EEG channels and single-trial signals. …”
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Robust SOH estimation for Li-ion battery packs of real-world electric buses with charging segments by Heng Li, Shilong Zhuo, Yun Zhou, Muaaz Bin Kaleem, Yu Jiang, Fu Jiang

“…Based on extensive operational data from electric buses, a novel SOH labeling calibration method is proposed, forming the foundation of a robust SOH estimation framework. First, the SOH of the battery pack is labeled using a variant of the ampere-hour integral formula applied to charging data, enhanced by mean filtering over 30 consecutive charge-discharge cycles to mitigate error influence. …”
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Achieving high-accuracy skin cancer classification with deep learning optimized by ant colony algorithm by Amany M. Sarhan, Hesham A. Ali, Shady Yasser, Mohamed Gobara, Ahmed A. Kandil, Ghada Sherif, Esraa Moustafa

“…We focus on utilizing deep learning, specifically convolutional neural networks (CNNs), to enhance the accuracy of skin lesion classification. …”
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F-OSFA: A Fog Level Generalizable Solution for Zero-Day DDOS Attacks Detection by Muhammad Rashid Minhas, Qaisar M. Shafi, Shoab Ahmed Khan, Tahir Ahmad, Subhan Ullah, Attaullah Buriro, Muhammad Azfar Yaqub

“…The first component uses a hybrid machine learning and deep learning framework that combines convolutional neural networks (CNNs) and decision trees to detect traditional DDoS attacks. …”
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MLGFENet: Multiscale Local&#x2013;Global Feature Enhancement Network for High-Resolution Remote Sensing Image Change Detection by Huanhuan Lv, Xianqi Yan, Hui Zhang, Cuiping Shi, Ruiqin Wang

“…The integration of a convolutional neural network (CNN) and a Transformer has become a dominant framework for change detection (CD) in remote sensing images, because of its ability to effectively model both local and global features. …”
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Opposition-Based White Shark Optimizer for Optimizing Modified EfficientNetV2 in Road Crack Classification by Mohammed Al-Shalabi, Mohammed A. Mahdi, Malik Braik, Mohammed Azmi Al-Betar, Shahanawaj Ahamad, Sawsan A. Saad

“…Maintaining reliable and long-lasting road infrastructure requires accurate identification and management of pavement cracks, as these cracks can significantly weaken asphalt and concrete surfaces over time. Although Convolutional Neural Networks (CNNs) and meta-heuristic algorithms have proven effective in solving real-world problems, their use in low-contrast pavement crack images is worth investigating. …”
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Zero-Touch Network Security (ZTNS): A Network Intrusion Detection System Based on Deep Learning by Emad-Ul-Haq Qazi, Tanveer Zia, Muhammad Hamza Faheem, Khurram Shahzad, Muhammad Imran, Zeeshan Ahmed

“…By implementing the DL-NIDS-ZTN methodology, we aim to strengthen the security framework of smart cities and ensure the secure and seamless integration of IoT.…”
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Deep Attention Networks With Multi-Temporal Information Fusion for Sleep Apnea Detection by Meng Jiao, Changyue Song, Xiaochen Xian, Shihao Yang, Feng Liu

“…This study introduces a Deep Attention Network with Multi-Temporal Information Fusion (DAN-MTIF) for SA detection using single-lead electrocardiogram (ECG) signals. This framework utilizes three 1D convolutional neural network (CNN) blocks to extract features from R-R intervals and R-peak amplitudes using segments of varying lengths. …”
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Dual-Stage AI Model for Enhanced CT Imaging: Precision Segmentation of Kidney and Tumors by Nalan Karunanayake, Lin Lu, Hao Yang, Pengfei Geng, Oguz Akin, Helena Furberg, Lawrence H. Schwartz, Binsheng Zhao

“…Methods: The segmentation framework employs a ViT-based model for the kidney organ, followed by a 3D UNet model with enhanced connections and attention mechanisms for tumor detection and segmentation. …”
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