YOLO-UNet Architecture for Detecting and Segmenting the Localized MRI Brain Tumor Image by Nur Iriawan, Anindya A. Pravitasari, Ulfa S. Nuraini, Nur I. Nirmalasari, Taufik Azmi, Muhammad Nasrudin, Adam F. Fandisyah, Kartika Fithriasari, Santi W. Purnami, null Irhamah, Widiana Ferriastuti

“…This paper employed deep learning to detect and segment brain tumor MRI images by combining the convolutional neural network (CNN) and fully convolutional network (FCN) methodology in serial. …”
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Histopathology and proteomics are synergistic for high-grade serous ovarian cancer platinum response prediction by Oz Kilim, Alex Olar, András Biricz, Lilla Madaras, Péter Pollner, Zoltán Szállási, Zsofia Sztupinszki, István Csabai

“…Our study demonstrates that combining H&E-stained whole slide images (WSIs) with proteomic signatures using a multimodal deep learning framework significantly improves the prediction of platinum response in both discovery and validation cohorts. …”
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Dynamics and triggers of misinformation on vaccines. by Emanuele Brugnoli, Marco Delmastro

“…We first use the symbolic transfer entropy analysis of news production time-series to dynamically determine which category of sources, questionable or reliable, causally drives the agenda on vaccines. Then, leveraging deep learning models capable to accurately classify vaccine-related content based on the conveyed stance and discussed topic, respectively, we evaluate the focus on various topics by news sources promoting opposing views and compare the resulting user engagement. …”
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Investigating the effect of loss functions on single-image GAN performance by Eyyup YİLDİZ, Mehmet Erkan YUKSEL, Selcuk SEVGEN

“…GAN models, which typically handle large datasets, have been successful in the field of deep learning. However, exploring the factors that influence the success of GAN models developed for limited data problems is an important area of research. …”
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A Feature-Enhanced Small Object Detection Algorithm Based on Attention Mechanism by Zhe Quan, Jun Sun

“…With the rapid development of AI algorithms and computational power, object recognition based on deep learning frameworks has become a major research direction in computer vision. …”
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Segmentasi Citra X-Ray Dada Menggunakan Metode Modifikasi Deeplabv3+ by Rima Tri Wahyuningrum, Maughfirotul Jannah, Budi Dwi Satoto, Amillia Kartika Sari, Anggraini Dwi Sensusiati

“…To make it easier to make a diagnosis, we need a deep learning model that can help with this. DeepLabV3+ is a method that can carry out the segmentation process. …”
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A Review of Multi-Source Data Fusion and Analysis Algorithms in Smart City Construction: Facilitating Real Estate Management and Urban Optimization by Binglin Liu, Qian Li, Zhihua Zheng, Yanjia Huang, Shuguang Deng, Qiongxiu Huang, Weijiang Liu

“…Data analysis algorithms help urban management in areas such as spatial analysis and deep learning. Algorithm collaboration can improve decision-making accuracy and efficiency and promote the rational allocation of urban resources. …”
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Enhancing adversarial transferability with local transformation by Yang Zhang, Jinbang Hong, Qing Bai, Haifeng Liang, Peican Zhu, Qun Song

“…Abstract Robust deep learning models have demonstrated significant applicability in real-world scenarios. …”
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Blink Detection Using 3D Convolutional Neural Architectures and Analysis of Accumulated Frame Predictions by George Nousias, Konstantinos K. Delibasis, Georgios Labiris

“…In this work, we propose and compare deep learning architectures for the task of detecting blinks in video frame sequences. …”
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A Comparative Analysis of YOLOv9, YOLOv10, YOLOv11 for Smoke and Fire Detection by Eman H. Alkhammash

“…This study explores recent YOLO (You Only Look Once) deep-learning object detection models YOLOv9, YOLOv10, and YOLOv11 for detecting smoke and fire in forest environments. …”
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Towards AI-Based Traffic Counting System with Edge Computing by Duc-Liem Dinh, Hong-Nam Nguyen, Huy-Tan Thai, Kim-Hung Le

“…First, a vehicle detection dataset (VDD) representing traffic conditions in Vietnam was created. Several deep learning models for VDD were then examined on two different edge device types. …”
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An End-to-End Rumor Detection Model Based on Feature Aggregation by Aoshuang Ye, Lina Wang, Run Wang, Wenqi Wang, Jianpeng Ke, Danlei Wang

“…Furthermore, the features used by the deep learning method based on natural language processing are heavily limited. …”
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Implementasi Algoritma Convolutional Neural Network untuk Klasifikasi Jenis Keris by Maria Mediatrix Sebatubun, Cosmas Haryawan

“…Penelitian ini akan mengimplementasikan metode deep learning dengan algoritma Convolutional Neural Network (CNN) yang dapat melakukan tugas klasifikasi secara langsung pada citra, untuk membangun sebuah model untuk klasifikasi jenis keris berdasarkan dhapur. …”
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Early Detection of Pancreatic Cancer: Opportunities Provided by Cancer-induced Paraneoplastic Phenomena and Artificial Intelligence by Wei-Chih Liao

“…Novel computer-aided detection tools based on AI technologies, including deep learning and radiomic analysis with machine learning, have achieved accurate detection and might supplement human interpretation to improve the sensitivity for early PDAC on CT images. …”
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Distributed Compressed Hyperspectral Sensing Imaging Incorporated Spectral Unmixing and Learning by Hua Xiao, Zhongliang Wang, Xueying Cui, Liping Wang, Hongsheng Yang, Yingbiao Jia

“…Traditional model-based reconstruction approaches are computationally burdensome and achieve limited success. Deep learning-based approaches, while improving in reconstruction accuracy and speed, depend heavily on data, which is a major challenge for satellite-borne hyperspectral compressed imaging. …”
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Local and Deep Features Based Convolutional Neural Network Frameworks for Brain MRI Anomaly Detection by Sajad Einy, Hasan Saygin, Hemrah Hivehch, Yahya Dorostkar Navaei

“…In this research, we proposed three different end-to-end deep learning approaches for analyzing effects of local and deep features for brain MRI images anomaly detection. …”
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Unsupervised Image Super-Resolution for High-Resolution Satellite Imagery via Omnidirectional Real-to-Synthetic Domain Translation by Minkyung Chung, Yongil Kim

“…Image super-resolution (SR) aims to enhance the spatial resolution of images and overcome the hardware limitations of imaging systems. While deep-learning networks have significantly improved SR performance, obtaining paired low-resolution (LR) and high-resolution (HR) images for supervised learning remains challenging in real-world scenarios. …”
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Sublemma-Based Neural Machine Translation by Thien Nguyen, Huu Nguyen, Phuoc Tran

“…Powerful deep learning approach frees us from feature engineering in many artificial intelligence tasks. …”
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A deep neural network for general scattering matrix by Jing Yongxin, Chu Hongchen, Huang Bo, Luo Jie, Wang Wei, Lai Yun

“…Our work proposes a convenient solution of deep learning for scattering problems.…”
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An Artificial-Intelligence- and Telemedicine-Based Screening Tool to Identify Glaucoma Suspects from Color Fundus Imaging by Alauddin Bhuiyan, Arun Govindaiah, R. Theodore Smith

“…Then, using CDR below 0.5 (nonsuspect) and CDR above 0.5 (glaucoma suspect), deep-learning architectures were used to train and test a binary classifier system. …”
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