Analisis Efek Augmentasi Dataset dan Fine Tune pada Algoritma Pre-Trained Convolutional Neural Network (CNN) by Theopilus Bayu Sasongko, Haryoko Haryoko, Agit Amrullah

“…Kemajuan teknologi deep learning seringkali berbanding lurus dengan keterkaitan metode yang dapat diandalkan dalam penggunaan jumlah data yang besar. …”
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Systematic Literature Review of Machine Learning Models for Detecting DDoS Attacks in IoT Networks by Marcos Luengo Viñuela, Jesús-Ángel Román Gallego

“…It contributes by showcasing current state-of-the-art DDoS detection through deep learning while outlining persistent challenges. …”
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Detection of Crop Damage in Maize Using Red–Green–Blue Imagery and LiDAR Data Acquired Using an Unmanned Aerial Vehicle by Barbara Dobosz, Dariusz Gozdowski, Jerzy Koronczok, Jan Žukovskis, Elżbieta Wójcik-Gront

“…The DSM-based method provided a closer estimation of the total damaged area (9.45% of the field) compared to the reference (10.50%), while the deep learning method underestimated damage (4.01%). Discrepancies arose from differences in how partially damaged areas were classified; the deep learning approach excluded these zones, focusing on fully damaged areas. …”
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Relieve Adversarial Attacks Based on Multimodal Training by Lai Hongjie

“…This paper explores the role of multimodal training in mitigating the problems caused by adversarial attacks, building on the foundations of deep learning. Deep learning models have reached great success in many areas such as image recognition and natural language processing. …”
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Monocular Depth Estimation: A Review on Hybrid Architectures, Transformers and Addressing Adverse Weather Conditions by Kumara Lakindu, Senanayake Nipuna, Poravi Guhanathan

“…Deep learning-based methods have further been enhanced using transformer and hybrid approaches. …”
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A Feature-Extraction-Based Lightweight Convolutional and Recurrent Neural Networks Adaptive Computing Model for Container Terminal Liner Handling Volume Forecasting by Bin Li, Yuqing He

“…The synergy of computational logistics and deep learning provides a new methodology and solution to the operational decisions of container terminal handling systems (CTHS) at the strategic, tactical, and executive levels. …”
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Influence of Intraoral Scanners, Operators, and Data Processing on Dimensional Accuracy of Dental Casts for Unsupervised Clinical Machine Learning: An In Vitro Comparative Study by Taseef Hasan Farook, Saif Ahmed, Jamal Giri, Farah Rashid, Toby Hughes, James Dudley

“…Native scans lacked volumetric depth, preventing their use for deep learning. Conclusion. Scanner, operator, and processing method did not significantly affect the dimensional accuracy of 3D scans for unsupervised deep learning. …”
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Visual Explainable Convolutional Neural Network for Aerodynamic Coefficient Prediction by Yanxuan Zhao, Chengwen Zhong, Fang Wang, Yueqing Wang

“…However, the explainability of deep learning models is poor and has been widely criticized, which limits the further development of deep learning in aerodynamic performance analysis. …”
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Detecting and Predicting Models for QoS Optimization in SDN by Getahun Wassie, Jianguo Ding, Yihenew Wondie

“…Recently, deep learning algorithms and software-defined networking technologies enabled traffic management to be more controllable in IP networking and mobile Internet to yield quality services to subscribers. …”
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Adversarial confound regression and uncertainty measurements to classify heterogeneous clinical MRI in Mass General Brigham. by Matthew Leming, Sudeshna Das, Hyungsoon Im

“…In this work, we introduce a novel deep learning architecture, MUCRAN (Multi-Confound Regression Adversarial Network), to train a deep learning model on clinical brain MRI while regressing demographic and technical confounding factors. …”
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Prostate Cancer Detection from MRI Using Efficient Feature Extraction with Transfer Learning by Rafiqul Islam, Al Imran, Md. Fazle Rabbi

“…It emphasizes utilizing deep learning models, namely VGG16, VGG19, ResNet50, and ResNet50V2, to extract relevant features. …”
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Traffic Flow Prediction Based on Large Language Models and Future Development Directions by Zhang Muhua, Zhao Wenzheng

“…As the application of deep learning in intelligent transportation systems becomes increasingly widespread, the accuracy and reliability of traffic flow prediction have become crucial. …”
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Federated Learning: A Distributed Shared Machine Learning Method by Kai Hu, Yaogen Li, Min Xia, Jiasheng Wu, Meixia Lu, Shuai Zhang, Liguo Weng

“…Finally, this paper discusses possible future developments of FL based on deep learning.…”
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Survei Penelitian Metode Kecerdasan Buatan untuk Mendeteksi Ancaman Teknologi Serangan Siber by Eza Yolanda Fitria, Kusprasapta Mutijarsa

“…Teknik dan metode baru machine learning dan deep learning terus dikembangkan oleh banyak peneliti untuk menangani serangan siber. …”
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Optimasi Convolutional Neural Network Untuk Deteksi Covid-19 pada X-ray Thorax Berbasis Dropout by I Gede Totok Suryawan, I Putu Agus Eka Darma Udayana

“…Salah satunya dengan menggunakan Deep learning yaitu Convolutional Neural Network (CNN) yang sudah terbukti merupakan salah satu metode yang dapat digunakan untuk melakukan skrining pasien dan mendeteksi COVID-19. …”
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Low-Complexity Data-Driven Communication Neural Receivers by Qingle Wu, Yuanhui Liang, Benjamin K. Ng, Chan-Tong Lam, and Yan Ma

“…Communication receivers based on deep learning have become a research hotspot in recent years. …”
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GaitRec-Net: A Deep Neural Network for Gait Disorder Detection Using Ground Reaction Force by Chandrasen Pandey, Diptendu Sinha Roy, Ramesh Chandra Poonia, Ayman Altameem, Soumya Ranjan Nayak, Amit Verma, Abdul Khader Jilani Saudagar

“…A deep learning-based architecture GaitRec-Net is proposed for this classification. …”
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Ensemble learning-based predictor for driver synonymous mutation with sequence representation. by Chuanmei Bi, Yong Shi, Junfeng Xia, Zhen Liang, Zhiqiang Wu, Kai Xu, Na Cheng

“…Notably, the incorporation of DNA shape features and deep learning-derived features from chemical molecule represents a pioneering effect in assessing the impact of synonymous mutations in cancer. …”
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Identification of diabetic retinopathy lesions in fundus images by integrating CNN and vision mamba models. by Zenglei Liu, Ailian Gao, Hui Sheng, Xueling Wang

“…Considering these analyses, this work presents a comprehensive deep learning model that combines convolutional neural network and vision mamba models. …”
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An Efficient Frequency Domain Based Attribution and Detection Network by Junbin Zhang, Yixiao Wang, Hamid Reza Tohidypour, Panos Nasiopoulos

“…Existing deep learning methods attempt to identify and classify GM-specific artifacts but often struggle with content-independence and generalizability. …”
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