“Image-Spectral” fusion monitoring of peanut leaf spot disease level based on deep learning by Yongda Lin, Jiangtao Tan, Hong Li, Xi Li, Jianguo Wang, Tingting Chen, Lei Zhang

“…To address these limitations, this study proposes a robust multi-source feature fusion model for peanut leaf spot detection, integrating ResNet101 for RGB image feature extraction and an improved 1D-CNN for hyperspectral feature extraction. …”
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Domain Diversification Progressive Cross-Domain Weakly-Supervised Real-time Object Detection by LI Chengyan, ZHENG Qisen, WANG Hao

“…A real-time object detector matching the cross-domain framework is constructed based on SSD algorithm to realize real-time object detection under weakly supervised conditions. …”
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Football sports video tracking and detection technology based on YOLOv5 and DeepSORT by Bin Wang

“…The detection performance under target overlap and uneven lighting and shadows exceeded 90%, and the difference between the algorithm and other algorithms was at least greater than 2%. …”
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Potential Use of a New Energy Vision (NEV) Camera for Diagnostic Support of Carpal Tunnel Syndrome: Development of a Decision-Making Algorithm to Differentiate Carpal Tunnel-Affect... by Dror Robinson, Mohammad Khatib, Mohammad Eissa, Mustafa Yassin

“…This study evaluates the New Energy Vision (NEV) camera, an RGB-based multispectral imaging tool, to detect CTS through skin texture and color analysis, developing a machine learning algorithm to distinguish CTS-affected hands from controls. …”
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Non-Destructive Detection of Pesticide-Treated Baby Leaf Lettuce During Production and Post-Harvest Storage Using Visible and Near-Infrared Spectroscopy by Dimitrios S. Kasampalis, Pavlos I. Tsouvaltzis, Anastasios S. Siomos

“…The genetic algorithm (GA) and the variable importance in projection (VIP) scores identified eleven distinct regions and nine specific wavelengths that exhibited the most significant effect in the detection models, with most of them in the near-infrared region of the electromagnetic spectrum. …”
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MSRP-TODNet: a multi-scale reinforced region wise analyser for tiny object detection by Thulasi Bikku, K. P. N. V. Satya Sree, Srinivasarao Thota, Malligunta Kiran Kumar, P. Shanmugasundaram

“…Deep Learning (DL) techniques generate feature maps to enhance detection, but conventional methods suffer from high computational costs. …”
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HAD-YOLO: An Accurate and Effective Weed Detection Model Based on Improved YOLOV5 Network by Long Deng, Zhonghua Miao, Xueguan Zhao, Shuo Yang, Yuanyuan Gao, Changyuan Zhai, Chunjiang Zhao

“…With the purpose of improving the model’s capacity to extract features and making it more lightweight, this algorithm employs the HGNetV2 as its backbone network. …”
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MED-AGNeT: An attention-guided network of customized augmentation of samples based on conditional diffusion for textile defect detection by Jun Liu, Haolin Li, Hao Liu, Jiuzhen Liang

“…An attention-guided network (AGNet) is a network that utilizes attention to guide information across different scales. Its feature extraction module employs a dual-branch information residual unit (DIRU) as a substitute for the conventional convolution block, which combines the feature extraction capabilities of global pooling and max pooling, reducing the number of parameters while also achieving a certain improvement in detection results. …”
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Machine Learning Aided Resilient Spectrum Surveillance for Cognitive Tactical Wireless Networks: Design and Proof-of-Concept by Eli Garlick, Nourhan Hesham, MD. Zoheb Hassan, Imtiaz Ahmed, Anas Chaaban, MD. Jahangir Hossain

“…The uniqueness of <inline-formula> <tex-math notation="LaTeX">$\textsf {MARSS}$ </tex-math></inline-formula> is its ability to detect hidden and unknown interference signals in multiple frequency bands without using any prior labels, thanks to its superior feature extraction capability. …”
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DBSANet: A Dual-Branch Semantic Aggregation Network Integrating CNNs and Transformers for Landslide Detection in Remote Sensing Images by Yankui Li, Wu Zhu, Jing Wu, Ruixuan Zhang, Xueyong Xu, Ye Zhou

“…Deep learning-based semantic segmentation algorithms have proven effective in landslide detection. …”
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A Laser-Based SLAM Algorithm of the Unmanned Surface Vehicle for Accurate Localization and Mapping in an Inland Waterway Scenario by Yang Wang, Chao Liu, Jiahe Liu, Jinzhe Wang, Jianbin Liu, Kai Zheng, Rencheng Zheng

“…Subsequently, a generalized iterative closest point (GICP) algorithm incorporating rejection sampling is integrated to enhance the accuracy of point cloud matching, involving a two-phase filtering process to select key feature points for matching. …”
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Terrain and individual tree vertical structure-based approach for point clouds co-registration by UAV and Backpack LiDAR by Tingwei Zhang, Xin Shen, Lin Cao

“…Second, individual tree positions were extracted from each platform’s LiDAR dataset and employed as key feature points for matching. Third, a similarity function was constructed to evaluate the most geometrically consistent point correspondences across platforms, which were subsequently refined through an Iterative Closest Point (ICP) algorithm. …”
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Development of Self-Powered Energy-Harvesting Electronic Module and Signal-Processing Framework for Wearable Healthcare Applications by Jegan Rajendran, Nimi Wilson Sukumari, P. Subha Hency Jose, Manikandan Rajendran, Manob Jyoti Saikia

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Comparison of SVM, K-NN, RF, CART, and GNB Algorithms for Water Bodies Detection Using Sentinel-2 Level-2a Imagery in Nakhon Pathom, Thailand by Ni Putu Nita Nathalia, Gede Andra Rizqy Wijaya, Kadek Yota Ernanda Aryanto, Ni Putu Novita Puspa Dewi, Putu Hendra Saputra, Ni Putu Karisma Dewi, Mellisa Damayanti, Kadek Losinanda Prawira

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A Hybrid Deep Learning–Based Feature Selection Approach for Supporting Early Detection of Long-Term Behavioral Outcomes in Survivors of Cancer: Cross-Sectional Study by Tracy Huang, Chun-Kit Ngan, Yin Ting Cheung, Madelyn Marcotte, Benjamin Cabrera

“…MethodsWe devised a hybrid deep learning–based feature selection approach to support early detection of negative long-term behavioral outcomes in survivors of cancer. …”
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X-FuseRLSTM: A Cross-Domain Explainable Intrusion Detection Framework in IoT Using the Attention-Guided Dual-Path Feature Fusion and Residual LSTM by Adel Alabbadi, Fuad Bajaber

“…For cross-domain intrusion detection, this paper proposes a novel algorithm, X-FuseRLSTM, a dual-path feature fusion framework that is attention guided and coupled with a residual LSTM architecture. …”
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Enhanced early detection of dysarthric speech disabilities using stacking ensemble deep learning model by Jagat Chaitanya Prabhala, Ravi Ragoju, Venkatanareshbabu Kuppili, Christophe Chesneau

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Analysis of the Relationship Between Scale Invariant Feature Transform Keypoint Properties and Their Invariance to Geometrical Transformation Applied to Cone-Beam Computed Tomograp... by Diletta Pennati, Leonardo Bocchi

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Early detection of gray mold on eggplant leaves using hyperspectral imaging technique by FENG Lei, ZHANG De-rong, CHEN Shuang-shuang, FENG Bin, XIE Chuan-qi, CHEN Youyuan, HE Yong

“…Successive projections algorithm (SPA) was executed on 24 feature variables, 13 feature variables in which were extracted as the input of the least square support vector machines (LS-SVM) model, and the accurate rate of the model was 97.5%. …”
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A hybrid deep learning-based intrusion detection system for EV and UAV charging stations by Rosebell Paul, Mercy Paul Selvan

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