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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Noncoding variants and sulcal patterns in congenital heart disease: Machine learning to predict functional impact by Enrique Mondragon-Estrada, Jane W. Newburger, Steven R. DePalma, Martina Brueckner, John Cleveland, Wendy K. Chung, Bruce D. Gelb, Elizabeth Goldmuntz, Donald J. Hagler, Jr., Hao Huang, Patrick McQuillen, Thomas A. Miller, Ashok Panigrahy, George A. Porter, Jr., Amy E. Roberts, Caitlin K. Rollins, Mark W. Russell, Martin Tristani-Firouzi, P. Ellen Grant, Kiho Im, Sarah U. Morton

“…This highlights the potential of deep learning models to generate hypotheses about the role of noncoding variants in brain development.…”
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Transformer-based modeling of Clonal Selection and Expression Dynamics reveals resistance mechanisms in breast cancer by Nathan D Maulding, Jun Zou, Wei Zhou, Ciara Metcalfe, Joshua M Stuart, Xin Ye, Marc Hafner

“…We present TraCSED (Transformer-based modeling of Clonal Selection and Expression Dynamics), a dynamic deep learning approach for modeling clonal selection. …”
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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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The Prediction of Storm‐Time Thermospheric Mass Density by LSTM‐Based Ensemble Learning by Peian Wang, Zhou Chen, Xiaohua Deng, Jingsong Wang, Rongxing Tang, Haimeng Li, Sheng Hong, Zhiping Wu

“…However, the generalization ability of the deep learning model is often suspicious since training data and testing data are from the same data set in the conventional method. …”
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Bright and stable anti-counterfeiting devices with independent stochastic processes covering multiple length scales by Junfang Zhang, Adam Creamer, Kai Xie, Jiaqing Tang, Luke Salter, Jonathan P. Wojciechowski, Molly M. Stevens

“…With the assistance of a deep-learning model, the resulting PUFs show both near-ideal performance and accessibility for general end users, offering a strategy for next-generation security devices.…”
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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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Analyzing urban public sports facilities for recognition and optimization using intelligent image processing by Zhongqian Zhang

“…The images captured systematically using photographic equipment identify such key information as facility usage, viewer demographics, and activity levels by deep learning algorithms. Sports facilities’ effectiveness evaluation for improvement and optimization has been done using metaheuristics and SE-DEA model. …”
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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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SAILOR: perceptual anchoring for robotic cognitive architectures by Miguel Á. González-Santamarta, Francisco J. Rodrıguez-Lera, Vicente Matellan-Olivera, Virginia Riego del Castillo, Lidia Sánchez-González

“…It provides a semantic world modeling approach using two deep learning-based sub-symbolic robotic skills: object recognition and matching function. …”
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Storm‐Time Characteristics of Ionospheric Model (MSAP) Based on Multi‐Algorithm Fusion by Zhou Chen, Kang Wang, Haimeng Li, Wenti Liao, Rongxin Tang, Jing‐song Wang, Xiaohua Deng

“…We use the Multi‐Step Auxiliary Prediction (MSAP) model, a deep learning algorithm, to forecast TEC during geomagnetic storms. …”
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Accurate localization of indoor high similarity scenes using visual slam combined with loop closure detection algorithm. by Zhuoheng Xiang, Jiaxi Guo, Jin Meng, Xin Meng, Yan Li, Jonghyuk Kim, Shifeng Wang, Bo Lu, Yu Chen

“…To address this issue, this paper proposes an improved visual SLAM loop closure detection algorithm that integrates deep learning techniques. Using the TUM f3 loh, Lip6 Indoor, and Bicocca Indoor datasets as experimental bases, a detailed comparison of the proposed algorithm against other methods was conducted across various evaluation metrics. …”
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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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Supervised multi-frame dual-channel denoising enables long-term single-molecule FRET under extremely low photon budget by Yu Miao, Yuxiao Cheng, Yushi Xia, Yongzhen Hei, Wenjuan Wang, Qionghai Dai, Jinli Suo, Chunlai Chen

“…In this work, we introduce MUFFLE, a supervised deep-learning denoising method that enables single-molecule FRET with up to 10-fold reduction in photon requirement per frame. …”
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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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