Kidney Segmentation with LinkNetB7 by Cihan Akyel

“…In studies of kidney segmentation with artificial intelligence, 3d deep learning models are used in the literature. These methods require more training time than 2d models. …”
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A Small Target Detection Method Based on the Improved FCN Model by Guofeng Ma

“…The experimental results on public datasets show that the proposed method outperforms other deep learning algorithms (DLA) in the detection accuracy of small target objects. …”
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A novel oversampling method based on Wasserstein CGAN for imbalanced classification by Hongfang Zhou, Heng Pan, Kangyun Zheng, Zongling Wu, Qingyu Xiang

“…Abstract Class imbalance is a crucial challenge in classification tasks, and in recent years, with the advancements in deep learning, research on oversampling techniques based on GANs has proliferated. …”
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Multi-functional broadband diffractive neural network with a single spatial light modulator by Bolin Li, Yinfei Zhu, Jinlei Fei, Runshi Zheng, Min Gu, Jian Lin

“…Diffractive neural networks (DNNs) are emerging as a novel optical computing architecture that combines wave optics with deep-learning methods for high-speed parallel information processing. …”
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MeTa Learning-Based Optimization of Unsupervised Domain Adaptation Deep Networks by Hsiau-Wen Lin, Trang-Thi Ho, Ching-Ting Tu, Hwei-Jen Lin, Chen-Hsiang Yu

“…MCWMMD offers a promising solution to the persistent challenge of domain adaptation, paving the way for more adaptable and generalizable deep learning models.…”
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Two Improved Methods of Generating Adversarial Examples against Faster R-CNNs for Tram Environment Perception Systems by Shize Huang, Xiaowen Liu, Xiaolu Yang, Zhaoxin Zhang, Lingyu Yang

“…Trams have increasingly deployed object detectors to perceive running conditions, and deep learning networks have been widely adopted by those detectors. …”
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JSTC: Travel Time Prediction with a Joint Spatial-Temporal Correlation Mechanism by Alfateh M. Tag Elsir, Alkilane Khaled, Pengfei Wang, Yanming Shen

“…In this paper, we introduce a unified deep learning-based framework named joint spatial-temporal correlation (JSTC) mechanism to improve the accuracy of OD travel time prediction. …”
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Reducing Training Time in Skin Cancer Classification Using Convolutional Neural Network with Mixed Precision Implementation by Raka Ryandra Guntara, Hendriyana, Indira Syawanodya

“…In the field of skin cancer classification, machine learning and deep learning have been extensively utilized, particularly with convolutional neural network (CNN) architectures. …”
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Avoiding catastrophic overfitting in fast adversarial training with adaptive similarity step size. by Jie-Chao Zhao, Jin Ding, Yong-Zhi Sun, Ping Tan, Ji-En Ma, You-Tong Fang

“…Adversarial training has become a primary method for enhancing the robustness of deep learning models. In recent years, fast adversarial training methods have gained widespread attention due to their lower computational cost. …”
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PharmRL: pharmacophore elucidation with deep geometric reinforcement learning by Rishal Aggarwal, David R. Koes

“…Results In this work, we develop a deep learning method that can identify pharmacophores in the absence of a ligand. …”
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PLncWX: A Machine-Learning Algorithm for Plant lncRNA Identification Based on WOA-XGBoost by Fei Guo, Zhixiang Yin, Kai Zhou, Jiasi Li

“…There have been a large number of identification tools based on machine-learning and deep learning algorithms, mostly using human and mouse gene sequences as training sets, seldom plants, and only using one or one class of feature selection methods after feature extraction. …”
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A large annotated cervical cytology images dataset for AI models to aid cervical cancer screening by Xuan Zhang, Jianxin Ji, Qi Zhang, Xiaohan Zheng, Kaiyuan Ge, Menglei Hua, Lei Cao, Liuying Wang

“…The vigorous development of deep learning methods has established a new ecosystem for cervical cancer screening, which has been proven to effectively improve efficiency and accuracy of cell detection in many studies. …”
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Physical Reservoir Computing Utilizing Ion‐Gating Transistors Operating in Electric Double Layer and Redox Mechanisms by Takashi Tsuchiya, Daiki Nishioka, Wataru Namiki, Kazuya Terabe

“…Abstract The enormous energy consumption of modern machine learning technologies, such as deep learning and generative artificial intelligence, is one of the most critical concerns of the time. …”
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A multi-feature dataset of coated end milling cutter tool wear whole life cycle by Na Li, Xiao Wang, Wanzhen Wang, Miaomiao Xin, Dongfeng Yuan, Mingqiang Zhang

“…Abstract Deep learning methods have shown significant potential in tool wear lifecycle analysis. …”
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Identification of Behavioral Features of Bridge Structure Based on Static Image Sequences by Guojun Deng, Zhixiang Zhou, Xi Chu, Shuai Shao

“…Considering the strong spatiotemporal correlations of the sequence data, the relationships between the time history images in six fixed fields of view were identified through deep learning under spatiotemporal sequences. On this basis, the behavioral features of the bridge structure were obtained under vehicle load. …”
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The Reduced-Order Model for Droplet Drift of Aerial Spraying under Random Lateral Wind by Wencheng Li, Wenyun Wang, Xiaomao Huang, Chenyang Li

“…Based on the input and output dataset of CFD, the recursive algorithm including nonlinear autoregressive exogenous model and surrogate-based recurrence framework and the deep learning method for time-series prediction called long short-term memory neural network are used to build the efficient reduced-order model, respectively. …”
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Skin image analysis for detection and quantitative assessment of dermatitis, vitiligo and alopecia areata lesions: a systematic literature review by Athanasios Kallipolitis, Konstantinos Moutselos, Argyriοs Zafeiriou, Stelios Andreadis, Anastasia Matonaki, Thanos G. Stavropoulos, Ilias Maglogiannis

“…The review examines deep learning architectures and image processing algorithms for segmentation, feature extraction, and classification tasks employed for disease detection. …”
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Prediction of power generation and maintenance using AOC‐ResNet50 network by Yueqiang Chu, Wanpeng Cao, Cheng Xiao, Yubin Song

“…In this article, the deep learning method is selected for photovoltaic power prediction. …”
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Chaotic gradient based optimization with fuzzy temporal optimized CNN for heart failure prediction by G. Kajeeth Kumar, S. Muthurajkumar

“…Furthermore, a tenfold cross-validation process ensures a comprehensive evaluation and the proposed method outperforms different Machine Learning (ML) / Deep Learning (DL) classifiers. The experimental findings reveal that CGBO significantly improves the predictive performance of the FTOCNN classifier by achieving 94% accuracy in EHR and enhances the reliability of heart failure detection compared to existing systems.…”
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Leveraging synthetic data to improve regional sea level predictions by Guanchao Tong, Jiayou Chao, Wenxuan Ma, Ziqi Zhong, Gaurav Gupta, Wei Zhu

“…This study presents a novel deep learning approach that combines TimesGAN with ConvLSTM to enhance regional sea level predictions using the more widely available satellite altimetry data. …”
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