DermViT: Diagnosis-Guided Vision Transformer for Robust and Efficient Skin Lesion Classification by Xuejun Zhang, Yehui Liu, Ganxin Ouyang, Wenkang Chen, Aobo Xu, Takeshi Hara, Xiangrong Zhou, Dongbo Wu

“…Dermoscopic Feature Gate (DFG), which simulates the observation–verification operation of doctors through a convolutional gating mechanism and effectively suppresses semantic leakage of artifact regions. …”
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Image Classification Model Based on Contrastive Learning With Dynamic Adaptive Loss by Quandeng Gou, Jingxuan Zhou, Zi Li, Fangrui Zhang, Yuheng Ren

“…Notably, the model achieves high classification accuracy while maintaining a relatively low parameter size (23.9MB) and computational complexity (5.7Mflops). …”
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Information Security and Artificial Intelligence–Assisted Diagnosis in an Internet of Medical Thing System (IoMTS) by Pi-Yun Chen, Yu-Cheng Cheng, Zi-Heng Zhong, Feng-Zhou Zhang, Neng-Sheng Pai, Chien-Ming Li, Chia-Hung Lin

“…Recently, artificial intelligence (AI)- based methods are being increasingly applied to preprocess digital data and extract features. The key physiological parameters and feature patterns can then be incorporated into AI- based tools to help monitor, detect, and diagnose applications. …”
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Deep CNN ResNet-18 based model with attention and transfer learning for Alzheimer's disease detection by Sofia Biju Francis, Sofia Biju Francis, Jai Prakash Verma

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Fault Diagnosis Method of Rolling Bearing Based on 1D Multi-Channel Improved Convolutional Neural Network in Noisy Environment by Huijuan Guo, Dongzhi Ping, Lijun Wang, Weijie Zhang, Junfeng Wu, Xiao Ma, Qiang Xu, Zhongyu Lu

“…By introducing BiLSTM, an attention mechanism and a local sparse structure of a two-channel Convolutional Neural Network, the feature information of the noisy timing signal is fully extracted at different scales while reducing the computational parameters. …”
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逆向法选择渐开线齿轮的变位系数 by 赵振江

“…A new kind of method for the choice of gear modification coefficients is presented.Its main idea is regard gear modification coefficient as a known parameter.The method take full advantage of a computer’s features of quick operation and accurate calculation and judgement function.A computer can find modification coefficients from a lots of modification coefficients which meet the needs of given condition,in the same time user needs input all kinds of given parameters and limited conditions only.…”
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Research on Breast Cancer Detection Methods Based on ODMV-MulDyHead-YOLO by Yanhong Zhang, Pei Li, Yihua Lan, Xiao Jia, Yingjie Lv

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Skin cancer detection using dermoscopic images with convolutional neural network by Khadija Nawaz, Atika Zanib, Iqra Shabir, Jianqiang Li, Yu Wang, Tariq Mahmood, Amjad Rehman

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A Lightweight Direction-Aware Network for Vehicle Detection by Luxia Yang, Yilin Hou, Hongrui Zhang, Chuanghui Zhang

“…Moreover, to further reduce model parameters and computational requirements, a lightweight shared convolutional detection head (SCL-Head) is devised using a parameter-sharing mechanism. …”
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Prediction and evaluation of environmental quality for nursing sow buildings via multisource sensor information fusion by Chong Chen, Xingqiao Liu, Chaoji Liu, Chengyang Yu

“…The Random Forest (RF) model was selected for the feature selection. There were six feature factors that were closely related to environmental quality, including temperature, relative humidity, concentrations of NH3, CO2,H2S and air speed. …”
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SGSNet: a lightweight deep learning model for strawberry growth stage detection by Zhiyu Li, Jianping Wang, Guohong Gao, Yufeng Lei, Chenping Zhao, Yan Wang, Haofan Bai, Yuqing Liu, Xiaojuan Guo, Qian Li

“…An innovative lightweight convolutional neural network, named GrowthNet, is designed as the backbone of SGSNet, facilitating efficient feature extraction while significantly reducing model parameters and computational complexity. …”
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Sea Surface Height Inversion Model Based on Multimodal Deep Learning for the Fusion of Heterogeneous FY-3E GNSS-R Data by Yun Zhang, Ganyao Qin, Shuhu Yang, Yanling Han, Zhonghua Hong

“…Traditional physical altimetry methods based on delay–Doppler mapping (DDM) are subject to errors that are difficult to correct computationally. The current deep-learning-based SSH inversion techniques primarily relying on single-modal data are unable to fully leverage the rich feature information from global navigation satellite system reflectometry (GNSS-R) remote sensing data, therefore limiting the potential accuracy improvement. …”
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Comprehensive Eye Diagram Analysis: A Transfer Learning Approach by Danshi Wang, Yilan Xu, Jianqiang Li, Min Zhang, Jin Li, Jun Qin, Cheng Ju, Zhiguo Zhang, Xue Chen

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Data-driven insights into groundwater quality: machine and deep learning approaches by Gift Mbuzi, Abdur Rashid Sangi, Baha Ihnaini, Anil Carie, Sruthi Sivarajan, Satish Anamalamudi

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Active accessibility: A review of operational measures of walking and cycling accessibility by David S. Vale, Miguel Saraiva, Mauro Pereira

“…While active travel has been shown to be associated with features of the built environment such as density and land-use mix, it is also associated with walking and cycling accessibility—which we designate as active accessibility. …”
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GYS-RT-DETR: A Lightweight Citrus Disease Detection Model Based on Integrated Adaptive Pruning and Dynamic Knowledge Distillation by Linlin Yang, Zhonghao Huang, Yi Huangfu, Rui Liu, Xuerui Wang, Zhiwei Pan, Jie Shi

“…Secondly, the model adopts two model optimization strategies: (1) The Group_taylor local pruning algorithm is used to reduce memory occupation and the number of computing parameters of the model. (2) The feature-logic knowledge distillation framework is proposed and adopted to solve the problem of information loss caused by the structural difference between teachers and students, and to ensure a good detection performance, while realizing the lightweight character of the model. …”
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Characteristics of CoVID-19 in children: the first experience in the hospital of st. Petersburg by E. A. Dondurey, L. N. Isankina, O. I. Afanasyeva, A. V. Titeva, T. V. Vishnevskaya, V. A. Kondrat`ev, I. A. Gryaznova, M. V. Berezina, M. A. Zolotova, V. M. Volzhanin

“…Objective: to identify the clinical, laboratory and epidemiological features of the new coronavirus (CV) infection in the provision of specialized medical care to children in the megalopolis of the Russian Federation. …”
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Design and Research on a Reed Field Obstacle Detection and Safety Warning System Based on Improved YOLOv8n by Yuanyuan Zhang, Zhongqiu Mu, Kunpeng Tian, Bing Zhang, Jicheng Huang

“…The improved model reduces parameter count and computational complexity by 31.9% and 33.4%, respectively, with a model size of only 4.2 MB. …”
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Explainable AI-Driven Quantum Deep Neural Network for Fault Location in DC Microgrids by Amir Hossein Poursaeed, Farhad Namdari

“…The model uses a combination of deep learning and quantum computing techniques to extract features and improve accuracy. …”
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A Lightweight and High-Performance YOLOv5-Based Model for Tea Shoot Detection in Field Conditions by Zhi Zhang, Yongzong Lu, Yun Peng, Mengying Yang, Yongguang Hu

“…Deep learning is well-suited for performing complex tasks due to its robust feature extraction capabilities. However, low-complexity models often suffer from poor detection performance, while high-complexity models are hindered by large size and high computational cost, making them unsuitable for deployment on resource-limited mobile devices. …”
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