Emotion recognition with multiple physiological parameters based on ensemble learning by Yilong Liao, Yuan Gao, Fang Wang, Li Zhang, Zhenrong Xu, Yifan Wu

“…We proposed a hybrid model framework combining Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) networks, trained and optimized using a random seed initialization strategy and a cosine annealing warm restart strategy. …”
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Deep learning approach based on a patch residual for pediatric supracondylar subtle fracture detection by Qingming Ye, Zhilu Wang, Yi Lou, Yang Yang, Jue Hou, Zheng Liu, Weiguang Liu, Jiayu Li

“…To address this issue, this paper introduces a deep learning-based multiscale patch residual network (MPR) for the automatic detection and localization of subtle pediatric supracondylar fractures. The MPR framework combines a CNN for automatic feature extraction with a multiscale generative adversarial network (GAN) to model skeletal integrity using healthy samples. …”
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Non-Contact Blood Pressure Monitoring Using Radar Signals: A Dual-Stage Deep Learning Network by Pengfei Wang, Minghao Yang, Xiaoxue Zhang, Jianqi Wang, Cong Wang, Hongbo Jia

“…We present a hierarchical neural framework that synergizes spatial and temporal feature learning for radar-driven, contactless BP monitoring. …”
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Astronomical Pointlike Source Detection via Deep Feature Matching by Ma Long, Xin Jiarong, Du Jiangbin, Zhao Jiayao, Wang Xiaotian, Zhang Yu

“…The feature extraction module is built on residual blocks and adopts an encoder–decoder framework to distill features from images robustly. …”
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DSIT UNet a dual stream iterative transformer based UNet architecture for segmenting brain tumors from FLAIR MRI images by Shakib Al Hasan, S. M. Mahim, Md Emamul Hossen, Md Olid Hasan, Md Khairul Islam, Patrizia Livreri, Salah Uddin Khan, Mohammad Alibakhshikenari, Md Sipon Miah

“…We propose Dual-Stream Iterative Transformer UNet (DSIT-UNet), a novel framework that combines Iterative Transformer (IT) modules with a dual-stream encoder–decoder architecture. …”
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Deep Learning-Based Imagery Style Evaluation for Cross-Category Industrial Product Forms by Jianmin Zhang, Yuliang Li, Mingxing Zhou, Sixuan Chu

“…This research provides a robust framework for cross-category industrial product style evaluation, enhancing design efficiency and shortening development cycles.…”
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Neural signals, machine learning, and the future of inner speech recognition by Adiba Tabassum Chowdhury, Ahmed Hassanein, Aous N. Al Shibli, Youssuf Khanafer, Mohannad Natheef AbuHaweeleh, Shona Pedersen, Muhammad E. H. Chowdhury

“…Building on prior literature, this work synthesizes and organizes existing ISR methodologies within a structured mathematical framework, reviews cognitive models of inner speech, and presents a detailed comparative analysis of existing ML approaches, thereby offering new insights into advancing the field.…”
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Towards Efficient SAR Ship Detection: Multi-Level Feature Fusion and Lightweight Network Design by Wei Xu, Zengyuan Guo, Pingping Huang, Weixian Tan, Zhiqi Gao

“…Firstly, the backbone network integrates depthwise separable convolutions and a Convolutional Block Attention Module (CBAM) to suppress background clutter and extract effective features. …”
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LungDxNet: AI-Powered Low-Dose CT Analysis for Early Lung Cancer Detection by Jyoti Parashar, Rituraj Jain, Mahesh K. Singh, Ashwani Kumar, Premananda Sahu, Kamal Upreti

“…This study introduces LungDxNet, a deep learning-based framework that integrates transfer learning to enhance diagnostic accuracy and efficiency. …”
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Research on insider threat detection based on personalized federated learning and behavior log analysis by Xiaoyun Ye, Faqin Luo, Huangrongbin Cui, Jinlong Wang, Xiaoyun Xiong, Wencui Zhang, Jiawei Yu, Wenhao Zhao

“…As a distributed machine learning framework, FL enables collaborative model building and analysis while safeguarding data privacy. …”
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An Autism Spectrum Disorder Identification Method Based on 3D-CNN and Segmented Temporal Decision Network by Zhiling Liu, Ye Chen, Xinrui Dong, Jing Liu

“…This study aims to improve the ability to capture spatiotemporal dynamics of brain activity by proposing an advanced framework. (2) Methods: This study proposes an ASD recognition method that combines 3D Convolutional Neural Networks (3D-CNNs) and segmented temporal decision networks. …”
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Lightweight Insulator and Defect Detection Method Based on Improved YOLOv8 by Yanxing Liu, Xudong Li, Ruyu Qiao, Yu Chen, Xueliang Han, Agyemang Paul, Zhefu Wu

“…Secondly, to address the issue of the network model’s complexity hindering its application on UAV equipment, depthwise separable convolution is incorporated for lightweight enhancement within the YOLOv8 algorithm framework. …”
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Thermal canopy segmentation in tomato plants: A novel approach with integration of YOLOv8-C and FastSAM by Hemamalini P, Chandraprakash MK, Laxman RH, Rathinakumari C, Senthil Kumaran G, Suneetha K

“…Advancing this methodology, we introduce a masked region of interest (ROI) temperature extraction technique, enabling targeted temperature extraction of segmented plant regions. This integrated framework, combining YOLOv8-C's detection capabilities with FastSAM's segmentation, is collectively called TCSegNet (Thermal Canopy Segmentation Network). …”
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LEAD-YOLO: A Lightweight and Accurate Network for Small Object Detection in Autonomous Driving by Yunchuan Yang, Shubin Yang, Qiqing Chan

“…To address this dilemma, this paper proposes LEAD-YOLO (Lightweight Efficient Autonomous Driving YOLO), an enhanced network architecture based on YOLOv11n that achieves superior small object detection while maintaining computational efficiency. The proposed framework incorporates three innovative components: First, the Backbone integrates a lightweight Convolutional Gated Transformer (CGF) module, which employs normalized gating mechanisms with residual connections, and a Dilated Feature Fusion (DFF) structure that enables progressive multi-scale context modeling through dilated convolutions. …”
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An enhanced BERT model with improved local feature extraction and long-range dependency capture in promoter prediction for hearing loss by Jing Sun, Yangfan Huang, Jiale Fu, Li Teng, Xiao Liu, Xiaohua Luo

“…Overall, DNABERT-CBL provides an effective framework for accurate promoter prediction, offers valuable insights into gene regulatory mechanisms, and supports the development of gene therapies for hearing loss and related diseases.…”
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Automated Measurement of Air Bubbles Dispersion in Ice Cream Using Machine Learning Methods by Igor A. Korolev

“…The automatic markup program employed the Python programming language, the Keras machine learning library, and the TensorFlow framework. The models were trained using the NVIDIA GTX video accelerator. …”
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Lightweight Brain Tumor Segmentation Through Wavelet-Guided Iterative Axial Factorization Attention by Yueyang Zhong, Shuyi Wang, Yuqing Miao, Tao Zhang, Haoliang Li

“…Methods: This paper presents a lightweight deep learning framework that uses adaptive discrete wavelet decomposition and iterative axial attention to improve 3D brain tumor segmentation. …”
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FR-CapsNet: Enhancing Low-Resolution Image Classification via Frequency Routed Capsules by Hasindu Dewasurendra, Kunmin Yeo, Nhan Thi Cao, Taejoon Kim

“…Furthermore, our method utilizes a global routing framework that considerably reduces computational demands, enabling FR-CapsNet to scale effectively to larger and more diverse datasets. …”
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Enhancing paddy leaf disease diagnosis -a hybrid CNN model using simulated thermal imaging by Jagamohan Padhi, Kunal Mishra, Ashoka Kumar Ratha, Santi Kumari Behera, Prabira Kumar Sethy, Aziz Nanthaamornphong

“…This research underscores the value of integrating thermal imaging with Deep Learning for advancing crop disease management and offers a framework for addressing other crop pathologies.…”
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Joint feature representation optimization and anti-occlusion for robust multi-vessel tracking in inland waterways by Shenjie Zou, Jin Liu, Xiliang Zhang, Zhongdai Wu, Jing Liu, Bing Han

“…To address the issues above, this paper proposes a novel Vessel Status Augmented Track (VSATrack) framework for multi-vessel detection and tracking. …”
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