Optimized classification of potato leaf disease using EfficientNet-LITE and KE-SVM in diverse environments by Gopal Sangar, Velswamy Rajasekar

“…EfficientNet-LITE improves the model's emphasis on pertinent features through Channel Attention (CA) and 1-D Local Binary Pattern (LBP), while preserving computational economy with a reduced model size of 12.46 MB, fewer parameters at 3.11M, and a diminished FLOP count of 359.69 MFLOPs.ResultsBefore optimization, the SVM classifier attained an accuracy of 79.38% on uncontrolled data and 99.07% on laboratory-controlled data. …”
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A Review of Degradation and Reliability Analysis of a Solar PV Module by Zafar Ullah Khan, Adnan Daud Khan, Khalid Khan, Soliman Abdul Karim Al Khatib, Shahbaz Khan, Muhammad Qasim Khan, Abid Ullah

“…Data-driven analytical methods, such as DL (Deep Learning) ML (Machine Learning) models, have astounding computational abilities to process large amounts of data, with diverse features, and with minimal computation time. …”
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Quantum Kernel Machine Learning With Continuous Variables by Laura J. Henderson, Rishi Goel, Sally Shrapnel

“…We derive a general closed form solution for all CV quantum kernels and show every such kernel can be expressed as the product of a Gaussian and an algebraic function of the parameters of the feature map. Furthermore, in the multi-mode case, we present quantification of a quantum-classical separation for all quantum kernels via a hierarchical notion of the “stellar rank" of the quantum kernel feature map. …”
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Lightweight defocus deblurring network for curved-tunnel line scanning using wide-angle lenses by Shaojie Qin, Taiyue Qi, Xiaodong Huang, Xiao Liang

“…The proposed depthwise ResBlocks significantly improves the parameter efficiency of the network. Additionally, the proposed feature refinement block captures the structurally similar features to enhance the image details, increasing the peak signal-to-noise ratio (PSNR). …”
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Multiple sclerosis diagnosis with brain MRI retrieval: A deep learning approach by R.M. Haggag, Eman M. Ali, M.E. Khalifa, Mohamed Taha

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Addressing Hybrid Confounder Issue for Causal Session-Based Recommendation by Quan Li, Xinhua Xu, Jinjun Liu, Guangmin Li

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Development and validation of a CT-based multi-omics nomogram for predicting hospital discharge outcomes following mechanical thrombectomy by Feifan Liu, Jiayi Hong, Yuhan Chen, Huan Liu, Yue Wang, Lijian Su, Sheng Hu, Jingjing Fu

“…ObjectiveThis study aimed to develop a multi-omics nomogram that combines clinical parameters, radiomics, and deep transfer learning (DTL) features of hyperattenuated imaging markers (HIM) from computed tomography scans immediately following mechanical thrombectomy (MT) to predict functional outcomes at discharge.MethodsThis study enrolled 246 patients with HIM who underwent MT. …”
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Data Mining Techniques for Early Detection and Classification of Plant Diseases: An Optimization-Based Approach by Wagh Swapnil, Sharma Ruchi

“…Furthermore, low-level optimization techniques like genetic algorithms as well as particle swarm optimization are used to fine tune the specific model parameters and to reduce the computational overhead for improving the detection efficacy still more. …”
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Non-Invasive Bioelectrical Characterization of Strawberry Peduncles for Post-Harvest Physiological Maturity Classification by Jonnel Alejandrino, Ronnie Concepcion, Elmer Dadios, Ryan Rhay Vicerra, Argel Bandala, Edwin Sybingco, Laurence Gan Lim, Raouf Naguib

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Eagle-YOLOv8: UAV Object Detection Inspired by the Eagle-Eye Vision System by Dianwei Wang, Zehao Gao, Jie Fang, Yuanqing Li, Zhijie Xu

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Leveraging hybrid model of ConvNextBase and LightGBM for early ASD detection via eye-gaze analysis by Ranjeet Bidwe, Sashikala Mishra, Simi Bajaj, Ketan Kotecha

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A lightweight semantic segmentation method for concrete bridge surface diseases based on improved DeeplabV3+ by Zhiyuan Yu, Chunquan Dai, Xiaoming Zeng, Yunlong Lv, Haisheng Li

“…Abstract Due to the similar features of different diseases and insufficient semantic information of small area diseases in the surface disease image of concrete bridges, the existing semantic segmentation models for identifying surface diseases in concrete bridges suffer from problems such as large number of parameters, insufficient feature extraction, and low segmentation accuracy. …”
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An analytical approach to modeling conjunctival viral disease using fuzzy logic and time-delay dynamics by Muhammad Tashfeen, Hothefa Shaker Jassim, Fazal Dayan, Muhammad Azizur Rehman, Alwahab Dhulfiqar Zoltán, Husam A. Neamah

“…Simulation results confirm that the NSFD approach maintains the qualitative features of the model even under larger time steps. …”
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Spatial and Spectral Structure-Aware Mamba Network for Hyperspectral Image Classification by Jie Zhang, Ming Sun, Sheng Chang

“…Extensive experiments on four benchmark HSI datasets demonstrate that DADFMamba outperforms state-of-the-art deep learning models in classification accuracy while maintaining low computational costs and parameter efficiency. Notably, it achieves superior performance with only 30 training samples per class, highlighting its data efficiency. …”
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A wave-resolving two-dimensional vertical Lagrangian approach to model microplastic transport in nearshore waters based on TrackMPD 3.0 by I. Jalón-Rojas, D. Sous, D. Sous, V. Marieu

“…This approach introduces novel features such as coupling with advanced turbulence models, simulating resuspension and bedload processes, implementing advanced settling and rising velocity formulations, and enabling parallel computation. …”
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Temporal Convolutional Network Approach to Secure Open Charge Point Protocol (OCPP) in Electric Vehicle Charging by Ikram Benfarhat, Vik Tor Goh, Chun Lim Siow, Muhammad Sheraz, Teong Chee Chuah

“…Additionally, we conducted a comparative analysis with a hybrid model, demonstrating that the proposed TCN delivers superior performance with lower computational complexity, fewer parameters, a smaller model size, and shorter computation times. …”
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Target Detection and Image Enhancement for Underwater Environment: Research on Improving YOLOv7 by Yang Luo, Wen Feng

“…To further enhance the computational efficiency, a deep decomposition feature expression module is designed, which significantly reduces the computational complexity and the number of parameters of the model. …”
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IVP-YOLOv5: an intelligent vehicle-pedestrian detection method based on YOLOv5s by Yang Sun, Jiankun Song, Yong Li, Yi Li, Song Li, Zehao Duan

“…Computer vision is now vital in intelligent vehicle environment perception systems. …”
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Research on Defect Detection in Lightweight Photovoltaic Cells Using YOLOv8-FSD by Chao Chen, Zhuo Chen, Hao Li, Yawen Wang, Guangzhou Lei, Lingling Wu

“…A thin neck structure designed based on hybrid convolution technology is adopted to reduce model parameters and computational load further. A lightweight dynamic feature upsampling operator improves the feature map quality. …”
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A dual-branch model combining convolution and vision transformer for crop disease classification. by Qingduan Meng, Jiadong Guo, Hui Zhang, Yaoqi Zhou, Xiaoling Zhang

“…A learnable parameter is used to achieve a linear weighted fusion of these two types of features. …”
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