Yo3RL-Net:A fusion of two-phase end-to-end deep net framework for hand detection and gesture recognition by Xiang Wu, Yuanhao Ma, Shijie Zhang, Tianfei Chen, He Jiang

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Semantic Segmentation of Rice Fields in Sub-Meter Satellite Imagery Using an HRNet-CA-Enhanced DeepLabV3+ Framework by Yifan Shao, Pan Pan, Hongxin Zhao, Jiale Li, Guoping Yu, Guomin Zhou, Jianhua Zhang

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Speech Emotion Recognition on MELD and RAVDESS Datasets Using CNN by Gheed T. Waleed, Shaimaa H. Shaker

“…This research presents a high-performance SER framework based on a lightweight 1D Convolutional Neural Network (1D-CNN) and a multi-feature fusion technique. …”
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Deep automatic soil roughness estimation from digital images by M. Ivanovici, S. Popa, K. Marandskiy, C. Florea

“…In this paper, we propose a framework that combines a specific setup for data acquisition with deep convolutional networks for actual estimation. …”
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GCBRGCN: Integration of ceRNA and RGCN to Identify Gastric Cancer Biomarkers by Peng Zhi, Yue Liu, Chenghui Zhao, Kunlun He

“…Our work offers a novel framework for GC biomarker identification, highlighting the critical role of multiple types RNA interaction in oncological research.…”
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A dual encoder network with multiscale feature fusion and multiple pooling channel spatial attention for skin scar image segmentation by Weiyuan Yang, Xiaolin Wang, Guangwei Chen, Jianming Wen, Dexing Kong, Jianfeng Zhang, Xinyang Ge, Hao Xu, Jianhua Qin

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FCEEG: federated learning-based seizure diagnosis through electroencephalogram (EEG) analysis by Zheng You Lim, Ying Han Pang, Shih Yin Ooi, Sarmela Raja Sekaran, Yee Jian Chew

“…Thus, we propose FCEEG, a convolutional-based deep learning with federated learning (FL) to diagnose seizures with EEG signals while preserving data privacy. …”
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Deep learning based identification of rock minerals from un-processed digital microscopic images of undisturbed broken-surfaces by M.A. Dalhat, Sami A. Osman

“…This study employed convolutional neural networks (CNNs) for the classification of rock minerals based on 3179 RGB-scale original microstructural images of undisturbed broken surfaces. …”
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Predicting abnormality-guided multimodal linguistic semantics Arabic image captioning by Nahla Aljojo, Hanin Ardah, Araek Tashkandi, Safa Habibullah

“…This research provides a novel, end-to-end Arabic image captioning framework, addressing linguistic challenges through deep learning. …”
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PSDA: Pyramid Spatial Deformable Aggregation for Building Segmentation in Multiview Remote Sensing Images by Xuejun Huang, Yi Wan, Yongjun Zhang, Xinyi Liu, Bin Zhang, Yameng Wang, Haoyu Guo, Yingying Pei, Zhonghua Hu

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Optimization of energy acquisition system in smart grid based on artificial intelligence and digital twin technology by Zhen Jing, Qing Wang, Zhiru Chen, Tong Cao, Kun Zhang

“…Firstly, a smart grid data transmission framework integrating digital twin technology is proposed. …”
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CSTFNet: A CNN and Dual Swin-Transformer Fusion Network for Remote Sensing Hyperspectral Data Fusion and Classification of Coastal Areas by Dekai Li, Harold Neira-Molina, Mengxing Huang, Syam M.S., Yu Zhang, Zhang Junfeng, Uzair Aslam Bhatti, Muhammad Asif, Nadia Sarhan, Emad Mahrous Awwad

“…In recent years, the convolutional neural network (CNN) framework and transformer models have demonstrated strong performance in HSI classification, especially in applications requiring precise change detection and analysis. …”
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Unraveling Parkinson's disease motor subtypes: A deep learning approach based on spatiotemporal dynamics of EEG microstates by Lin Meng, Deyu Wang, Jun Ma, Yu Shi, Hongbo Zhao, Yanlin Wang, Qingqing Shi, Xiaodong Zhu, Dong Ming

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Predicting Index Trend Using Hybrid Neural Networks with a Focus on Multi-Scale Temporal Feature Extraction in the Tehran Stock Exchange by Mohammad Osoolian, Ali Nikmaram, Mahdi Karimi

“…The primary focus of this research endeavor revolves around the predictive analysis of the Tehran Stock Exchange (TSE) Composite Index, wherein a novel hybrid neural network framework is employed. This approach seamlessly integrates multiscale temporal features, with the ultimate objective of bolstering prediction precision and offering profound insights into prevailing market trends and dynamics. …”
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A Novel Federated Learning Framework for Sustainable and Efficient Breast Cancer Classification System (FL-L₂CNN-BCDet) by Nesma Abd El-Mawla, Mohamed A. Berbar, Nawal A. El-Fishawy, Mohamed A. El-Rashidy

“…The proposed FL framework is evaluated on three benchmark datasets. …”
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Artificial intelligence based classification and prediction of medical imaging using a novel framework of inverted and self-attention deep neural network architecture by Junaid Aftab, Muhammad Attique Khan, Sobia Arshad, Shams ur Rehman, Dina Abdulaziz AlHammadi, Yunyoung Nam

“…In this work, we proposed a novel deep-learning framework for classifying several medical imaging modalities. …”
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Deep learning framework based on ITOC optimization for coal spontaneous combustion temperature prediction: a coupled CNN-BiGRU-CBAM model by Xuming Shao, Wenhao Liu, Gang Bai, Yan Chen, Yu Liu, Jiahe Guang

“…Based on these variables, a deep learning framework combining an Improved Tornado Optimization with Coriolis force (ITOC) strategy and a CNN-BiGRU-CBAM model is proposed. …”
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A hybrid 1DCNN-GRU deep learning framework for classifying caprine granulosa cell fertility potential using single-cell transcriptomics by Thanida Sananmuang, Denis Puthier, Kaj Chokeshaiusaha

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A Temporal–Spatial–Spectral Fusion Framework for Coastal Wetland Mapping on Time-Series Remote Sensing Imagery by Xiang Li, Shenfu Zhang, Qiang Liu, Liang Chen, Gang Yang, Rui Zhao, Weiwei Sun, Feng Shao, Xiangchao Meng

“…A hybrid transformer-convolution module enhances fine-grained feature extraction. …”
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A machine learning-based framework for predicting metabolic syndrome using serum liver function tests and high-sensitivity C-reactive protein by Bahareh Behkamal, Fatemeh Asgharian Rezae, Amin Mansoori, Rana Kolahi Ahari, Sobhan Mahmoudi Shamsabad, Mohammad Reza Esmaeilian, Gordon Ferns, Mohammad Reza Saberi, Habibollah Esmaily, Majid Ghayour-Mobarhan

“…The framework integrated diverse ML algorithms, including Linear Regression (LR), Decision Trees (DT), Support Vector Machine (SVM), Random Forest (RF), Balanced Bagging (BG), Gradient Boosting (GB), and Convolutional Neural Networks (CNNs). …”
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