Implementation Of Convolutional Neural Network (Cnn) Based On Mobile Application For Rice Quality Determination by Muhammad Zainal Altim, Abdullah Basalamah, kasman kasman

“…The purpose of this study is to design and build a CNN deep learning program modeling for a mobile application for rice quality classification and analyze the performance of a mobile application-based classification program as a means of halal information in real time. …”
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Squeeze-and-Excitation Vision Transformer for Lung Nodule Classification by Xiaozhong Xue, Yanhe Ma, Weiwei Du, Yahui Peng

“…This study combines 2 attention mechanisms and proposes a novel deep learning model called squeeze-and-excitation vision transformer (SE-ViT). …”
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cigFacies: a massive-scale benchmark dataset of seismic facies and its application by H. Gao, X. Wu, X. Sun, M. Hou, M. Hou, H. Gao, G. Wang, H. Sheng

“…However, unlike the CV domain, the field of seismic exploration lacks a comprehensive benchmark dataset for seismic facies, severely limiting the development, application, and evaluation of deep-learning approaches in seismic facies classification. …”
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Leveraging Comprehensive Echo Data to Power Artificial Intelligence Models for Handheld Cardiac Ultrasound by D.M. Anisuzzaman, PhD, Jeffrey G. Malins, PhD, John I. Jackson, PhD, Eunjung Lee, PhD, Jwan A. Naser, MBBS, Behrouz Rostami, PhD, Grace Greason, BA, Jared G. Bird, MD, Paul A. Friedman, MD, Jae K. Oh, MD, Patricia A. Pellikka, MD, Jeremy J. Thaden, MD, Francisco Lopez-Jimenez, MD, MSc, MBA, Zachi I. Attia, PhD, Sorin V. Pislaru, MD, PhD, Garvan C. Kane, MD, PhD

“…Objective: To develop a fully end-to-end deep learning framework capable of estimating left ventricular ejection fraction (LVEF), estimating patient age, and classifying patient sex from echocardiographic videos, including videos collected using handheld cardiac ultrasound (HCU). …”
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CR-DEQ-SAR: A Deep Equilibrium Sparse SAR Imaging Method for Compound Regularization by Guoru Zhou, Yixin Zuo, Zhe Zhang, Bingchen Zhang, Yirong Wu

“…The experimental results show that the proposed method outperforms existing deep learning-based SAR imaging methods regarding reconstruction performance and memory usage.…”
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InceptionDTA: Predicting drug-target binding affinity with biological context features and inception networks by Mahmood Kalemati, Mojtaba Zamani Emani, Somayyeh Koohi

“…Our results demonstrate that InceptionDTA outperforms various sequence-based, transformer-based, and graph-based deep learning approaches across warm-start, refined, and cold-start splitting settings. …”
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Attention-Based Multi-Learning Approach for Speech Emotion Recognition With Dilated Convolution by Samuel, Kakuba, Alwin, Poulose

“…The success of deep learning in speech emotion recognition has led to its application in resource-constrained devices. …”
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Evaluating GRU Algorithm and Double Moving Average for Predicting USDT Prices: A Case Study 2017-2024 by RAHMAT, Munirul ula, Zara Yunizar

“…While DMA is well-suited for stable trends and GRU excels in volatile conditions, LSTM outperforms both, reinforcing the effectiveness of deep learning for financial time-series forecasting.…”
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Pendeteksi Citra Masker Wajah Menggunakan CNN dan Transfer Learning by Mohammad Farid Naufal, Selvia Ferdiana Kusuma

“…Convolutional Neural Network (CNN) merupakan algoritma deep learning yang memiliki performa bagus dalam klasifikasi citra. …”
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Performance of artificial intelligence on cervical vertebral maturation assessment: a systematic review and meta-analysis by Termeh Sarrafan Sadeghi, Seyed AmirHossein Ourang, Fatemeh Sohrabniya, Soroush Sadr, Parnian Shobeiri, Saeed Reza Motamedian

“…Abstract Background Artificial intelligence (AI) methods, including machine learning and deep learning, are increasingly applied in orthodontics for tasks like assessing skeletal maturity. …”
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Autoencoder untuk Sistem Prediksi Berat Lahir Bayi by Fitra Septia Nugraha, Hilman Ferdinandus Pardede

“…Penelitian bertujuan untuk prediksi berat lahir bayi menggunakan metode Deep Learning autoencoder untuk memprediksi berat lahir bayi. …”
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SMART TRAFFIC SIGNAL CONTROL SYSTEM FOR TWO INTER-DEPENDENT INTERSECTIONS IN AKURE, NIGERIA by AJIBESIN SAMSON, PONNLE AKINLOLU, OYEDEPO OLUGBENGA

“…The system developed in this work uses deep learning and computer vision techniques to estimate the density of traffic and uses this information to adaptively switch traffic signals based on the traffic density estimated. …”
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Neuroeducation meets virtual reality: theoretical analysis and implications for didactic design by Terrenghi Ilaria, Garavaglia Andrea

“…Taking into account the latest research in neuroscience, we want to explore the potential of using immersive virtual environments to facilitate deep learning in educational contexts that invoke the value of experience, imitation and repetition. …”
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Rancang Bangun Alat Pengenal Finger Vein Menggunakan Raspberry Pi dengan Metode Convolutional Neural Network (CNN) by Barlian Henryranu Prasetio, Jevandika, Dahnial Syauqy

“…This research uses a Raspberry Pi 4-based system with the help of IR LEDs and webcams for the acquisition process of finger blood vessel image data, which is expected to be able to carry out the Finger Vein recognition process faster, and the use of the proven Convolutional Neural Network method to produce better accuracy with the Deep Learning process. Of the 30 data used as system testers alongside embedded software and hardware, the accuracy reached 96.66%. …”
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Severe deviation in protein fold prediction by advanced AI: a case study by Jacinto López-Sagaseta, Alejandro Urdiciain

“…Abstract Artificial intelligence (AI) and deep learning are making groundbreaking strides in protein structure prediction. …”
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RETRACTED: Bone Age Assessment Based on Deep Convolutional Features and Fast Extreme Learning Machine Algorithm by Longjun Guo, Juan Wang, Jiaqi Teng, Yukun Chen

“…As the development of deep learning DL-based bone age prediction methods have achieved great success. …”
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Enhancing of teaching and learning through constructive alignment by G. E. Dames

“… This article elucidates issues about practical knowledge/deep learning on the current teaching and learning preaching practices in the Department of Practical Theology at the Faculty of Theology of the University of the Free State. …”
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VisionMD: an open-source tool for video-based analysis of motor function in movement disorders by Gabriela Acevedo, Florian Lange, Carolina Calonge, Robert Peach, Joshua K. Wong, Diego L. Guarin

“…Abstract VisionMD, an open-source software for automated video-based analysis of MDS-UPDRS Part III motor tasks, offers precise, objective, and scalable assessments of motor symptoms in Parkinson’s disease and other movement disorders. Leveraging deep learning, VisionMD tracks body movements to compute kinematic features that quantify symptoms severity and supports longitudinal monitoring. …”
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Ringworm Detection and Diagnosis System. by Asiimwe, Joab, Barigye, Deus Dedet

“…This report presents a novel ringworm detection system utilizing deep learning and image processing. We carried out our research within a period of seven months and our system performed the desired work. …”
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Extracting neutron skin from elastic proton-nucleus scattering with deep neural network by G.H. Yang, Y. Kuang, Z.X. Yang, Z.P. Li

“…Based on the relativistic impulse approximation of proton-nucleus elastic scattering theory, the neutron density distribution and neutron skin thickness of 48Ca are estimated via the deep learning method. The neural-network-generated neutron densities are mainly compressed to be higher inside the nucleus compared with the results from the relativistic PC-PK1 density functional, resulting in a significant improvement on the large-angle scattering observables, both for the differential cross section and analyzing power. …”
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