Deep TPS-PSO: Hybrid Deep Feature Extraction and Global Optimization for Precise 3D MRI Registration by Gayathri Ramasamy, Tripty Singh, Xiaohui Yuan, Ganesh R Naik

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Hybrid face recognition under adverse conditions using appearance‐based and dynamic features of smile expression by Murat Taskiran, Nihan Kahraman, Cigdem Eroglu Erdem

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Baby Cry Classification Using Structure-Tuned Artificial Neural Networks with Data Augmentation and MFCC Features by Tayyip Ozcan, Hafize Gungor

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Clinical features and outcomes of pseudolithiasis induced by ceftriaxone in Chinese children: a single-center observational study by Chen Jin, Chen Jin, Wen-Li Xiu, Wen-Li Xiu, Yao Liu, Yao Liu, Xi-Wei Hao, Qian Dong, Qian Dong

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MorphoCellSorter is an Andrews plot-based sorting approach to rank microglia according to their morphological features by Sarah Benkeder, Son-Michel Dinh, Paul Marchal, Priscille De Gea, Muriel Thoby-Brisson, Violaine Hubert, Ines Hristovska, Gabriel Pitollat, Kassandre Combet, Laura Cardoit, Bruno Pillot, Christelle Leon, Marlene Wiart, Serge Marthy, Jérôme Honnorat, Olivier Pascual, Jean-Christophe Comte

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A novel lightweight model for tea disease classification based on feature reuse and channel focus attention mechanism by Junjie Liang, Renjie Liang, Dongxia Wang

“…Second, we propose the feature reuse module (FRM). The FRM significantly reduces the parameters and computational costs of the model, making the model more lightweight. …”
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LMSFA-YOLO: A lightweight target detection network in Remote sensing images based on Multiscale feature fusion by Yuanbo Chu, Jiahao Wang, Longhui Ma, Chenxing Wu

“…These methods optimize convolutional computation cost and enhance multiscale information extraction, significantly reducing computational cost and parameters, while improving feature representation and fusion without sacrificing accuracy. …”
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Slim-YOLO: An Improved Sugarcane Tail Tip Recognition Algorithm Based on YOLO11n for Complex Field Environments by Chunming Wen, Yang Cheng, Shangping Li, Leilei Liu, Qingquan Liang, Kaihua Li, Youzong Huang

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Fusion of non-iterative deep neural network feature extraction with kernel extreme learning machine for plant disease classification by Kirti Kirti, Navin Rajpal, Virendra P. Vishwakarma, Pramod Kumar Soni

“…The method extracts deep, discriminative features via ResNet-50 and feeds them into a lightweight KELM for final classification. …”
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Predicting epidermal growth factor receptor (EGFR) mutation status in non-small cell lung cancer (NSCLC) patients through logistic regression: a model incorporating clinical charac... by Jimin Hao, Man Liu, Zhigang Zhou, Chunling Zhao, Liping Dai, Songyun Ouyang

“…This study presents a predictive model integrating clinical parameters, computed tomography (CT) characteristics, and serum tumor markers to forecast EGFR mutation status in NSCLC patients. …”
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A lightweight hyperspectral image multi-layer feature fusion classification method based on spatial and channel reconstruction. by Yuping Yin, Haodong Zhu, Lin Wei

“…Firstly, this method reduces redundant computations of spatial and spectral features by introducing Spatial and Channel Reconstruction Convolutions (SCConv), a novel convolutional compression method. …”
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A Blueberry Maturity Detection Method Integrating Attention-Driven Multi-Scale Feature Interaction and Dynamic Upsampling by Haohai You, Zhiyi Li, Zhanchen Wei, Lijuan Zhang, Xinhua Bi, Chunguang Bi, Xuefang Li, Yunpeng Duan

“…Built on the YOLOv8n architecture, ADE-YOLO features a dimensionality-reducing convolution at the backbone’s end, reducing computational complexity while optimizing input features. …”
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A Lightweight Multi-Scale Context Detail Network for Efficient Target Detection in Resource-Constrained Environments by Kaipeng Wang, Guanglin He, Xinmin Li

“…Extensive evaluations highlight the effectiveness of MSCDNet, which achieves 40.1% mAP50-95, 86.1% precision, and 68.1% recall while maintaining a low computational load with only 2.22 M parameters and 6.0 G FLOPs. …”
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LCD-Net: A Lightweight Remote Sensing Change Detection Network Combining Feature Fusion and Gating Mechanism by Wenyu Liu, Jindong Li, Haoji Wang, Run Tan, Yali Fu, Qichuan Tian

“…While traditional CNN-based methods have improved detection accuracy, they often suffer from high computational complexity and large parameter counts, limiting their use in resource-constrained environments. …”
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A Lightweight Multi-Frequency Feature Fusion Network with Efficient Attention for Breast Tumor Classification in Pathology Images by Hailong Chen, Qingqing Song, Guantong Chen

“…At the same time, the incorporation of a linear attention (LA) mechanism lowers the model’s computational complexity and further enhances its global feature extraction capability. …”
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Brain image registration optimization method via SAM-Med3D multi-scale feature migration by Mo Nan

“…A cross-attention mechanism was designed to achieve hierarchical fusion of anatomical features and local details. Innovative introduction of lightweight channel attention adapter, complete feature space mapping with few parameters, reduce the computational overhead. …”
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Multiclass Crop Interpretation via a Lightweight Attentive Feature Fusion Network Using Vehicle-View Images by Wenyue Li, Bingfang Wu, Runyu Fan, Fuyou Tian, Miao Zhang, Zhaoying Zhou, Jun Hu, Ruyi Feng, Fangming Wu

“…The experimental results show that CropNet has better semantic segmentation results with fewer model parameters and lower computational costs.…”
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Advanced bearing fault detection at varying rotational speeds using PSO-optimized SVM and CDET feature selection by Hongxu Chai, Xiaoshi Ma, Feng Zhu, Yandong Hu

“…Critically, we present an enhanced distance compensation evaluation technique (CDET) for feature selection, in which the threshold parameter is automatically optimized using particle swarm optimization (PSO) rather than being set arbitrarily. …”
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HFF-Net: A hybrid convolutional neural network for diabetic retinopathy screening and grading by Muhammad Hassaan Ashraf, Hamed Alghamdi

“…This approach can lead to information loss in the initial stages due to limited feature utilization across adjacent layers. To address this limitation, we propose a Hierarchical Features Fusion Convolutional Neural Network (HFF-Net) within a Diabetic Retinopathy Screening and Grading (DRSG) framework. …”
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EMHANet: Lightweight Salient Object Detection for Remote Sensing Images via Edge-Aware Multiscale Feature Fusion by Qian Tang, Zhen Wang, Xuqi Wang, Shan-Wen Zhang

“…To address these issues, we propose EMHANet, a lightweight network that integrates edge texture detail extraction, multi-scale feature fusion, and hybrid attention mechanism. EMHANet consists of MobileNetV3 for feature extraction, an Edge Feature Integration Module (EFIM) for low-level edge details, a Multi-scale Contextual Information Enhancement Module (MCIEM) for high-level feature refinement, and a lightweight decoder for saliency prediction. …”
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