Channel computation based on multi-scale attention residual network by Wengang Li, Deli Zhou, Qiong Ye

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An improved EAE-DETR model for defect detection of server motherboard by Jian Chi, Mingke Zhang, Puhon Zhang, Guowang Niu, Zhihao Zheng

“…Furthermore, the model demonstrates a reduction in parameter count by 21.7% and a decrease in computational load by 12.0%. …”
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False-Alarm-Controllable Detection of Marine Small Targets via Improved Concave Hull Classifier by Sainan Shi, Jiajun Wang, Jie Wang, Tao Li

“…On the other hand, in 3D feature space, an improved concave hull classifier is developed to further shrink the decision region, where a fast two-stage parameter search is designed for low computational cost and accurate control of false alarm rate. …”
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ELD-YOLO: A Lightweight Framework for Detecting Occluded Mandarin Fruits in Plant Research by Xianyao Wang, Yutong Huang, Siyu Wei, Weize Xu, Xiangsen Zhu, Jiong Mu, Xiaoyan Chen

“…Our method incorporates edge-aware processing to strengthen feature representation, introduces a streamlined detection head that balances accuracy with computational cost, and employs an adaptive upsampling strategy to minimize information loss during feature scaling. …”
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A genetic programming approach with adaptive region detection to skin cancer image classification by Kunjie Yu, Jintao Lian, Ying Bi, Jing Liang, Bing Xue, Mengjie Zhang

“…In recent years, the development of computer vision and machine learning has provided new methods for assisted diagnosis. …”
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Speech emotion recognition algorithm of intelligent robot based on ACO-SVM by Xueliang Kang

“…In the feature selection stage, ACO algorithm is introduced to explore the optimal combination of emotion features, aiming at improving the efficiency and robustness of emotion recognition. …”
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Copula Approximate Bayesian Computation Using Distribution Random Forests by George Karabatsos

“…This <i>Stats</i> invited feature article introduces and provides an extensive simulation study of a new approximate Bayesian computation (ABC) framework for estimating the posterior distribution and the maximum likelihood estimate (MLE) of the parameters of models defined by intractable likelihoods, that unifies and extends previous ABC methods proposed separately. …”
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A lightweight multi-path convolutional neural network architecture using optimal features selection for multiclass classification of brain tumor using magnetic resonance images by Amreen Batool, Yung-Cheol Byun

“…Pre-trained models like AlexNet, Residual Networks (ResNet), and Inception V3 are effective but has high computational costs due to trainable parameters. Therefore, a lightweight Multi -path Convolutional Neural Network (M-CNN) is introduced to extract features using varying convolutional filters at each convolutional layer. …”
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Machine Learning Approach to Characterize Ferromagnetic La0.7Sr0.3MnO3 Thin Films via Featurization of Surface Morphology by Sanghyeok Ryou, Jihyun Lim, Minwoo Jang, Kitae Eom, Sunwoo Lee, Hyungwoo Lee

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Matrix computation over homomorphic plaintext-ciphertext and its application by Yang LIU, Linhan YANG, Jingwei CHEN, Wenyuan WU, Yong FENG

“…Those homomorphic encryption schemes supporting single instruction multiple data (SIMD) operations effectively enhance the amortized efficiency of ciphertext computations, yet the structure of ciphertexts leads to high complexity in matrix operations.In many applications, employing plaintext-ciphertext matrix operations can achieve privacy-preserving computing.Based on this, a plaintext-ciphertext matrix multiplication scheme for matrices of arbitrary dimension was proposed.The resulting ciphertext was computed through steps such as encoding the plaintext matrix, transforming the dimensions of the encrypted matrix, etc.Compared to the best-known encrypted matrix multiplication algorithm for square matrices proposed by Jiang et al., the proposed scheme supported matrix multiplication of arbitrary dimension, and consecutive matrix multiplications.Both theoretical analysis and experimental results show that the proposed scheme requires less rotations on ciphertexts and hence features higher efficiency.When applied to a privacy-preserving Bayesian classifier, the proposed scheme can complete classification tasks with higher security parameters and reduced running time.…”
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Enhancing sarcasm detection in sentiment analysis for cyberspace safety using advanced deep learning techniques by Raghu Dhumpati, Archana Sasi, Shaik Johny Basha, Suryanarayana Vadhri, P. Saroja, Swathi Alluri, Ramesh Vatambeti

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Global miniaturization of broadband antennas by prescreening and machine learning by Slawomir Koziel, Anna Pietrenko-Dabrowska, Ubaid Ullah

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Lightweight Pyramid Cross-Attention Network for No-Service Rail Surface Defect Detection by Sixu Guo, Jiyou Fei, Liying Wang, Hua Li, Xiaodong Liu

“…However, many existing methods face challenges such as high parameters, complex computation, slow inspection speed, and low accuracy. …”
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Small target detection in coal mine underground based on improved RTDETR algorithm by Feng Tian, Cong Song, Xiaopei Liu

“…This decreased the number of network parameters and computation. By introducing Deformable Attention in the coding part of the RTDETR algorithm, the deformable feature of this attention mechanism is used to improve the network’s ability to extract effective image features. …”
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PCLC-Net: Parallel Connected Lateral Chain Networks for Infrared Small Target Detection by Jielei Xu, Xinheng Han, Jiacheng Wang, Xiaoxue Feng, Zhenxu Li, Feng Pan

“…Given the widespread influence of U-Net and FPN network architectures on infrared small target detection tasks on existing models, these structures frequently incorporate a significant number of downsampling operations, thereby rendering the preservation of small target information and contextual interaction both challenging and computation-consuming. To tackle these challenges, we introduce a parallel connected lateral chain network (PCLC-Net), an innovative architecture in the domain of infrared small target detection, that preserves large-scale feature maps while minimizing downsampling operations. …”
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Insect Bio-inspired Neural Network Provides New Evidence on How Simple Feature Detectors Can Enable Complex Visual Generalization and Stimulus Location Invariance in the Miniature... by Mark Roper, Chrisantha Fernando, Lars Chittka

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GhostConv+CA-YOLOv8n: a lightweight network for rice pest detection based on the aggregation of low-level features in real-world complex backgrounds by Fei Li, Yang Lu, Qiang Ma, Shuxin Yin, Rui Zhao

“…To overcome these limitations, this paper introduces GhostConv+CA-YOLOv8n, a lightweight object detection framework was proposed, which incorporates several innovative features: GhostConv replaces standard convolutional operations with computationally efficient ghost modules in the YOLOv8n’s backbone structure, reducing parameters by 40,458 while maintaining feature richness; a Context Aggregation (CA) module is applied after the large and medium-sized feature maps were output by the YOLOv8n’s neck structure. …”
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Multi-objective predictive control of cascaded H-bridge multilevel inverter based grid integrated PV based distributed generation system with improved power quality features by Avismit Dutta, Roshan Pradhan, Aurobinda Panda

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Multimodal recurrence risk prediction model for HR+/HER2- early breast cancer following adjuvant chemo-endocrine therapy: integrating pathology image and clinicalpathological featu... by Xiaoyan Wu, Yiman Li, Jilong Chen, Jie Chen, Wenchuan Zhang, Xunxi Lu, Xiaorong Zhong, Min Zhu, Yuhao Yi, Hong Bu

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AERO: Adaptive Edge-Cloud Orchestration With a Sub-1K-Parameter Forecasting Model by Berend J. D. Gort, Godfrey M. Kibalya, Angelos Antonopoulos

“…With fewer than 1,000 parameters, AERO is highly suitable for deployment on edge devices with limited computational capacity. …”
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