SmartPod: An Automated Framework for High-Precision Soybean Pod Counting in Field Phenotyping by Fei Liu, Shudong Wang, Shanchen Pang, Zhongzhi Han, Longgang Zhao

“…We present SmartPod, an advanced deep learning framework that addresses these challenges through three key innovations: (1) a novel vision Transformer architecture for enhanced feature representation, (2) an efficient attention mechanism for the improved detection of overlapping pods, and (3) a semi-supervised learning strategy that maximizes performance with limited annotated data. …”
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Recent advances of plant growth promoting rhizobacteria (PGPR) for eco-restoration of polluted soil by Mohd. Zobair Iqbal, Kshitij Singh, Ram Chandra

“…Recent advances in metagenomic approaches have allowed for the detection of rhizospheric bacterial communities from polluted soils revealing their contributions to the degradation of complex pollutants through the production of potential enzymes as a novel technique. …”
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Effective Classification of Plant Diseases Using Blend Unity Resqueeze With ResNet Model by Reena S, Rathinasabapathy

“…However, the task becomes complex and erroneous due to the complex nature of data. …”
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Infrared and Visible Image Fusion Using a State-Space Adversarial Model with Cross-Modal Dependency Learning by Qingqing Hu, Yiran Peng, KinTak U, Siyuan Zhao

“…The results confirm the robustness and generalizability of our framework for complex scene understanding and downstream tasks such as object detection under adverse conditions.…”
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Liquid Crystal Microcavity Biosensors for Real-Time Liver Injury Monitoring via Whispering Gallery Mode Laser by Jianwei Wang, Yeshuai Song, Xinyu Dou, Jiapeng Sun, Xinghua Yang, Yu Zhang, Zhihai Liu, Yanzeng Li, Hanyang Li

“…However, existing detection methods often suffer from complex operation, high costs, and limited sensitivity. …”
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Innovative Peptide-Based Plasmonic Optical Biosensor for the Determination of Cholesterol by Ana Lia Bernardo, Anne Parra, Virginia Cebrián, Óscar Ahumada, Sergio Oddi, Enrico Dainese

“…Plasmonic-based biosensors have gained prominence as potent optical biosensing platforms in both scientific and medical research, attributable to their enhanced sensitivity and precision in detecting biomolecular and chemical interactions. However, the detection of low molecular weight analytes with high sensitivity and specificity remains a complex and unresolved issue, posing significant limitations for the advancement of clinical diagnostic tools and medical device technologies. …”
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Improvement of the sensitivity of circulating tumor DNA-based liquid biopsy: current approaches and future perspectives by Ekaterina S. Kuligina, Grigoriy A. Yanus, Evgeny N. Imyanitov

“…Liquid biopsy (LB) is a complex of procedures aimed at the detection of tumor-derived fragments (nucleic acids, proteins, cells, etc.) persisting in the blood or other body fluids. …”
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Real-Time Recognition and Localization of Kiwifruit Based on Improved YOLOv5s Algorithm by Jin-Sui Dai, Zhi-Qin He

“…First, data enhancement is implemented in the training strategy to ensure the model’s efficient learning and generalization ability in complex environments; then the Coordinate Attention mechanism is introduced to highlight the key features of the image and improve detail detection; Secondly, the Bidirectional Feature Pyramid Network structure is used to optimize the feature fusion and strengthen the information exchange between different layers through bidirectional connectivity; then, the loss function is optimized to improve the bounding box localization accuracy; and finally, the combined with the binocular vision stereo matching algorithm Semi-Global Block Matching to obtain the spatial location information of Kiwifruit. …”
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Privacy-Preserving Machine Learning for IoT-Integrated Smart Grids: Recent Advances, Opportunities, and Challenges by Mazhar Ali, Moharana Suchismita, Syed Saqib Ali, Bong Jun Choi

“…Ensuring the safe, reliable, and energy-efficient provision of electricity is a complex task for smart grid (SG) management applications. …”
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DA-YOLOv7: A Deep Learning-Driven High-Performance Underwater Sonar Image Target Recognition Model by Zhe Chen, Guohao Xie, Xiaofang Deng, Jie Peng, Hongbing Qiu

“…New modules such as the Omni-Directional Convolution Channel Prior Convolutional Attention Efficient Layer Aggregation Network (OA-ELAN), Spatial Pyramid Pooling Channel Shuffling and Pixel-level Convolution Bilat-eral-branch Transformer (SPPCSPCBiFormer), and Ghost-Shuffle Convolution Enhanced Layer Aggregation Network-High performance (G-ELAN-H) are central to its design, which reduce the computational burden and enhance the accuracy in detecting small targets and capturing local features and crucial information. …”
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Advanced finite segmentation model with hybrid classifier learning for high-precision brain tumor delineation in PET imaging by K. Murugan, SatheeshKumar Palanisamy, N. Sathishkumar, Tagrid Abdullah N. Alshalali

“…Abstract Brain tumor segmentation plays a crucial role in clinical diagnostics and treatment planning, yet accurate and efficient segmentation remains a significant challenge due to complex tumor structures and variations in imaging modalities. …”
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WORKING ANALYSIS OF SPACE TIME TRELLIS CODE ON WIFI MIMO(2X2) SYSTEM OFDM by Wisnu Broto, Noor Suryaningsih, Adhi Mahendra

“…In addition, the application of Orthogonal Frequency Division Multiplexing (OFDM) on MIMO-STC will more efficiently use bandwidth. The Space-Time Trellis Code (STTC) method is one of the diverse techniques in sending data with complex coding so that coding reinforcement is achieved and applied to the OFDM MIMO system. …”
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CerviXpert: A multi-structural convolutional neural network for predicting cervix type and cervical cell abnormalities by Rashik Shahriar Akash, Radiful Islam, SM Saiful Islam Badhon, KSM Tozammel Hossain

“…This study aims to develop CerviXpert, a multi-structural convolutional neural network designed to classify cervix types and detect cervical cell abnormalities efficiently. Methods We introduced CerviXpert, a computationally efficient convolutional neural network model that classifies cervical cancer using images from the publicly available SiPaKMeD dataset. …”
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A Fire Segmentation Method with Flame Detail Enhancement U-Net in Multispectral Remote Sensing Images Under Category Imbalance by Rui Zou, Zhihui Xin, Guisheng Liao, Penghui Huang, Rui Wang, Yuhu Qiao

“…Additionally, Haar wavelet downsampling is applied to retain image detail and improve the detection of small-scale flame regions. Experimental results show that the FDE U-Net model exhibits robust performance in fire detection, accurately extracting flame regions even when their proportion is low and the background is complex. …”
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A mutual mapping model of cross-sections between the axial and normal planes of ball screws based on the forming of helical ball track by Chaoqun Qian, Yi Ou, Hutian Feng, Jian Wu

“…This high precision and efficiency underscore the algorithm’s value in enhancing design, manufacturing, and inspection processes. …”
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An MCMC Approach to Bayesian Image Analysis in Fourier Space by Konstantinos Bakas, John Kornak, Hernando Ombao

“…Bayesian image analysis methods are commonly applied to solve image analysis problems such as noise reduction, feature enhancement, and object detection. A primary limitation of these methods is their computational cost due to the complex joint interdependencies between pixels, which limits the efficiency of performing posterior sampling through Markov chain Monte Carlo (MCMC). …”
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A Multitask CNN for Near-Infrared Probe: Enhanced Real-Time Breast Cancer Imaging by Maryam Momtahen, Farid Golnaraghi

“…This multitasking approach leverages the robust feature extraction capabilities of CNNs to perform complex tasks simultaneously, thereby improving the model’s efficiency and accuracy. …”
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From Image to Sequence: Exploring Vision Transformers for Optical Coherence Tomography Classification by Amirali Arbab, Aref Habibi, Hossein Rabbani, Mahnoosh Tajmirriahi

“…Results: While our model achieves an accuracy of 99.80% on the OCT2017 dataset, its standout feature is its parameter efficiency–requiring only 6.9 million parameters, significantly fewer than larger, more complex models such as Xception and OpticNet-71. …”
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A Review of Artificial Intelligence Applications in Predicting Faults in Electrical Machines by Mathew Habyarimana, Abayomi A. Adebiyi

“…The operational efficiency of many industrial processes is greatly affected by condition monitoring, which has become more and more important in the detection and forecast of electrical machine failures. …”
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A Collaborative Auto-Diversified Optimization Scheme  by Besma Hezili, Hichem Talbi

“…For re-diversification, CADOS utilizes both CMA-ES, known for its efficiency in complex fitness landscapes, and the Auto-Enhanced Population Diversity (AEPD) technique. …”
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