Design and Development of an Application for the Generation of Garment Patterns Based on Body Measurements Using CNN by Geraldine Curipaco, Jeiel Tarazona, Daniel Subauste

“…In recent years, the growing consumption of products and services over the Internet has led companies to take their business models to virtual platforms, so retail fashion companies, such as ateliers, need to adapt to new market trends. Ateliers specialize in making garments to the customer's measurements, so this process requires a high level of time, cost and personnel specialized in taking body measurements and pattern making. …”
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Deep Learning Model for COVID-19 Diagnosis: Improving Accuracy and Sensitivity in Early Detection by Ahmed Majid Taha, Munera A. Jabaar, Nadia Mahmood Ali

“…This work presents a deep learning-based system, using convolutional neural networks, for the detection and diagnosis of COVID-19 through computed tomography tests, aiming to assist specialized medical professionals. …”
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Comparative Evaluation of Multimodal Large Language Models for No-Reference Image Quality Assessment with Authentic Distortions: A Study of OpenAI and Claude.AI Models by Domonkos Varga

“…However, more advanced deep learning models, especially those based on deep convolutional networks, surpass LLMs in performance. …”
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Use of Xception Architecture for the Classification of Skin Lesions by Cledmir Tejada, Gustavo Espinoza, Daniel Subauste

“…The Xception architecture, a deep convolutional neural network, serves as the foundational model, supplemented with customized classification layers for specialized features and predictions. …”
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NPP estimation by fusing geodetector and deep spatio-temporal networks by Xiaohui He, Chenqiao Yuan, Panle Li, Xijie Cheng, Mengjia Qiao, Xiaoyu He, Nan Yang, Guangsheng Zhou, Jiandong Shang

“…Finally, we develop a novel decoder by combining self-attention unit (SAU) and 3D convolution (Conv3D) to produce the spatio-temporal distribution of NPP. …”
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Automated Detection of Micro-Scale Porosity Defects in Reflective Metal Parts via Deep Learning and Polarization Imaging by Haozhe Li, Xing Peng, Bo Wang, Feng Shi, Yu Xia, Shucheng Li, Chong Shan, Shiqing Li

“…At the same time, we employ global space construction with a dual-attention mechanism and multi-scale feature refining technique with selection kernel convolution to extract multi-scale defect information from highly reflective surfaces stably. …”
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AI in Endoscopic Gastrointestinal Diagnosis: A Systematic Review of Deep Learning and Machine Learning Techniques by Jovita Relasha Lewis, Sameena Pathan, Preetham Kumar, Cifha Crecil Dias

“…Additionally, Deep Learning (DL) approaches like transfer learning (TL), Convolution Neural Networks (CNN), optimization, transformer, and reinforcement learning have been analyzed for GI diagnosis. …”
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USD-YOLO: An Enhanced YOLO Algorithm for Small Object Detection in Unmanned Systems Perception by Hongqiang Deng, Shuzhe Zhang, Xiaodong Wang, Tianxin Han, Yun Ye

“…To address these issues, we propose a specialized algorithm named Unmanned-system Small-object Detection-You Only Look Once (USD-YOLO). …”
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Rancang Bangun Aplikasi Berbasis Android untuk Perbaikan Kualitas Citra Tanaman Atas Perbedaan Spesifikasi Kamera Smartphone pada Prediksi Kandungan Pigmen Fotosintesis Secara Real... by Felix Adrian Tjokro Atmodjo, Kestrilia Rega Prilianti, Hendry Setiawan

“…The destructive approach of evaluating pigment content is expensive and necessitates specialized handling. An Android based application called Fuzzy Piction could predict the content of those pigments nondestructively using the FP3Net, a Convolutional Neural Network (CNN) model. …”
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Video-Based Plastic Bag Grabbing Action Recognition: A New Video Dataset and a Comparative Study of Baseline Models by Pei Jing Low, Bo Yan Ng, Nur Insyirah Mahzan, Jing Tian, Cheung-Chi Leung

“…Recognizing the action of plastic bag taking from CCTV video footage represents a highly specialized and niche challenge within the broader domain of action video classification. …”
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Text classification model of rare earths patents based on ERNE-CAB-CNN by Liao Liefa, Shi Lijiao

“…Combined with ERNIE and Convolutional Neural Network (CNN), an innovative model ERNE-CAB-CNN for rare earth patent text classification is constructed. …”
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Research Advances in Underground Bamboo Shoot Detection Methods by Wen Li, Qiong Shao, Fan Guo, Fangyuan Bian, Huimin Yang

“…Underground winter bamboo shoots, prized for their high nutritional value and economic significance, face harvesting challenges owing to inefficient manual methods and the lack of specialized detection technologies. This review systematically evaluates current detection approaches, including manual harvesting, microwave detection, resistivity methods, and biomimetic techniques. …”
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Integrating deep learning in stride-to-stride muscle activity estimation of young and old adults with wearable inertial measurement units by Min Khant, Darwin Gouwanda, Alpha A. Gopalai, Chee Choong Foong

“…Conventional gait analysis requires a specialized laboratory setup with markers positioned at anatomical landmarks. …”
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Advancements in the use of AI in the diagnosis and management of inflammatory bowel disease by Dalia Braverman-Jaiven, Luigi Manfredi

“…Therefore, algorithms based on Deep Learning (DL) and Convolutional Neural Networks (CNN) for colonoscopy images and videos are growing in popularity, especially for the detection and classification of colorectal polyps. …”
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Attention-Enhanced Hybrid Automatic Modulation Classification for Advanced Wireless Communication Systems: A Deep Learning-Transformer Framework by Sam Ansari, Khawla A. Alnajjar, Sohaib Majzoub, Eqab Almajali, Anwar Jarndal, Talal Bonny, Abir Hussain, Soliman Mahmoud

“…To address these limitations, this paper presents a novel attention-enhanced hybrid AMC framework that synergistically integrates specialized convolutional layers for efficient temporal feature extraction with a compact transformer encoder for global sequence modeling. …”
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ClassRoom-Crowd: A Comprehensive Dataset for Classroom Crowd Counting and Cross-Domain Baseline Analysis by Wenqian Jiang, Xiaohua Huang, Qun Zhao, Sheng Liu

“…Current methods predominantly employ convolutional neural networks, which require large datasets for training. …”
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ADVANCED NEURAL NETWORKS AND DEEP LEARNING TECHNIQUES IN FINANCIAL MARKET PREDICTION by ENE CEZAR CATALIN

“…The discussion covers key architectures, including feedforward neural networks, convolutional neural networks (CNN), and recurrent neural networks (RNN) with specific emphasis on advanced forms like Long Short-Term Memory (LSTM) networks and Gated Recurrent Units (GRU). …”
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Bridging neuroscience and AI: a survey on large language models for neurological signal interpretation by Sreejith Chandrasekharan, Jisu Elsa Jacob

“…Traditional deep neural networks, such as convolutional networks, sequence-to-sequence networks, and hybrids of such neural networks were proven to be effective for a wide range of neurological disease classifications. …”
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Fine-Tuning Models for Histopathological Classification of Colorectal Cancer by Houda Saif ALGhafri, Chia S. Lim

“…<b>Background/Objectives:</b> This study aims to design and evaluate transfer learning strategies that fine-tune multiple pre-trained convolutional neural network architectures based on their characteristics to improve the accuracy and generalizability of colorectal cancer histopathological image classification. …”
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WDM C-band four channel demultiplexer using cascaded multimode interference on SiN strip waveguide structure by Malka Dror

“…Our design was optimized using AI-enhanced RSoft-CAD simulations that combined the Beam Propagation Method (BPM) and Finite-Difference Time-Domain (FDTD) techniques, integrated with convolutional neural network (CNN) machine learning algorithms. …”
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