Cascade drive: a unified deep learning framework for multi-featured detection and control in autonomous electric vehicles on unstructured roadways by Kushal Kumar Raju, B. Prahal Bhagavath, M. K. Nallakaruppan, Rajesh Kumar Dhanaraj, Soufiane Ben Othman, Obaid Ali

“…Performance metrics are exceptional with measures of 97.26% accuracy for lane detection using DeepLabv3+, 0.92 mAP for object detection with YOLOv5, and 0.83 mAP for pothole detection using YOLOv7. …”
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More Accurate Constraints for Self-Supervised Learning in Remote Sensing Images-Based Object Detection by Shangdong Zheng, Zebin Wu, Yang Xu, Qian Liu, Zhihui Wei

“…However, most existing methods suffer from guaranteeing the quality of the generated SSL pseudoannotations, and the constructed auxiliary tasks are not detection-oriented, which is difficult to enhance the feature representations that are beneficial for object detection. …”
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MODAMS: design of a multimodal object-detection based augmentation model for satellite image sets by Rahul Malik, Rachit Garg, Korhan Cengiz, Nikola Ivković, Adnan Akhunzada

“…This is followed by a context-specific classification layer that assists in identification of detected object types. The identified objects are analyzed via a cascaded dual Generative Adversarial Network (cdGAN), which estimates an object-level importance metric, which is used to evaluate its importance probability levels. …”
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A Novel Dynamic Context Branch Attention Network for Detecting Small Objects in Remote Sensing Images by Huazhong Jin, Yizhuo Song, Ting Bai, Kaimin Sun, Yepei Chen

“…Extensive experiments conducted on four public remote sensing datasets demonstrate that the DCBANet achieves impressive mAP@0.5 scores of 80.79% on DOTA, 89.17% on NWPU VHR-10, 80.27% on SIMD, and a remarkable 42.4% mAP@0.5:0.95 on the specialized small object benchmark AI-TOD. These results surpass RetinaNet, YOLOF, FCOS, Faster R-CNN, Dynamic R-CNN, SKNet, and Cascade R-CNN, highlighting its effectiveness in detecting small objects in remote sensing images. …”
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A Comparative Study of Multiple Object Detection Using Haar-Like Feature Selection and Local Binary Patterns in Several Platforms by Souhail Guennouni, Ali Ahaitouf, Anass Mansouri

“…In this work we present a developed application for multiple objects detection based on OpenCV libraries. The complexity-related aspects that were considered in the object detection using cascade classifier are described. …”
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HSF-DETR: A Special Vehicle Detection Algorithm Based on Hypergraph Spatial Features and Bipolar Attention by Kaipeng Wang, Guanglin He, Xinmin Li

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A Feature-Driven Inception Dilated Network for Infrared Image Super-Resolution Reconstruction by Jiaxin Huang, Huicong Wang, Yuhan Li, Shijian Liu

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Advanced Persistent Threat Kill Chain for Cyber-Physical Power Systems by Alfan Presekal, Alexandru Stefanov, Vetrivel Subramaniam Rajkumar, Ioannis Semertzis, Peter Palensky

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Advanced Self-Driving Vehicle Model for Complex Road Navigation Using Integrated Image Processing and Sensor Fusion by Kalapraveen Bagadi, Naveen Kumar Vaegae, Visalakshi Annepu, Khaled Rabie, Shafiq Ahmad, Thokozani Shongwe

“…The model integrates state-of-the-art image processing techniques with advanced sensor fusion, utilizing EfficientDet D0 and Haar Cascade object detection models to identify obstacles, road signs, and traffic signals accurately. …”
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The Face and number plate recognition for car anti-theft by Quoc Bao Truong, Tan-Loc Tran, Thanh Tan-Kiet Nguyen, Huu Cuong Nguyen

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The Face and number plate recognition for car anti-theft by Quoc Bao Truong, Tan-Loc Tran, Thanh Tan-Kiet Nguyen, Huu Cuong Nguyen

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Detect material volume by fusing heterogeneous camera target detection and depth estimation information by Wei Tian, Xuecong Cheng, Yipeng Zhang, Huazhi Lin

“…First, the improved DeepLabV3+ is used to detect the edge of the material pile in the monocular camera target detection, and the CREStereo cascade network is used in the binocular camera to calculate the depth map; then, SIFT is combined with FLANN to map the edge of the material pile into the depth map and separate the depth of the material pile; finally, the three-dimensional coordinates of each point in the material pile are calculated, and the volume is calculated using the microelement method. …”
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Advanced High Switching-Frequency Cascaded H-Bridge Multilevel Inverter Based Shunt Active Filter for PV Generation: A Case Study by Nabil Karania, Mohamad Alaaeddin Alali, Stefano Di Gennaro, Jean Pierre Barbot

“…This article presents a compact structure ofshunt active photovoltaic filter based on a cascaded H-bridge multilevel inverter (SAF-PV/CHB-MLI) to eliminate electrical perturbations caused by nonlinear loads and to generate MPPT of PV generators. …”
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Proteomic insights into biology of bipolar disorder: implications for health complexity and mortality by Paola Rampelotto Ziani, Marco Antônio de Bastiani, Pietra Paiva Alves, Pedro Henrique da Rosa, Tainá Schons, Giovana Mezzomo, Ellen Scotton, Flávio Kapczinski, Adriane R. Rosa

“…Abstract Objective: The present study has the following objectives: 1) identify differentially expressed proteins and pathways in blood samples of bipolar disorder (BD) compared to healthy controls (HC) by employing high-throughput proteomics and bioinformatics; and 2) characterize disease-related molecular signatures through in-depth analysis of the differentially expressed proteins and pathways. …”
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An embedded intelligence engine for driver drowsiness detection by Shirisha Vadlamudi, Ali Ahmadinia

“…The TensorFlow model is trained on images captured from the video with the help of object detection using cascade classifier. In order to have a better accuracy, an Inception v3 architecture is used in pre‐training the model with the image dataset. …”
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Outlier detection method based on K-means by Liu Daojun, Liu Shuai, Zhang Yusong, Ou Sicheng

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Automating attendance management in human resources: A design science approach using computer vision and facial recognition by Bao-Thien Nguyen-Tat, Minh-Quoc Bui, Vuong M. Ngo

“…Haar Cascade is a cost-effective and user-friendly machine learning-based algorithm for detecting objects in images and videos. …”
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Detecting the left atrial appendage in CT localizers using deep learning by Aydin Demircioğlu, Denise Bos, Anton S. Quinsten, Lale Umutlu, Oliver Bruder, Michael Forsting, Kai Nassenstein

“…Four commonly used deep networks (VariFocalNet, Cascade-R-CNN, Task-aligned One-stage Object Detection Network, YOLO v11) were trained to predict the LAA boundaries on a cohort of 1253 localizers, collected retrospectively from a single center. …”
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Global Feature Focusing and Information Enhancement Network for Occluded Pedestrian Detection by ZHENG Kaikui, JI Kangyou, LI Jun, LI Qiming

“…ObjectivePedestrian detection is a crucial task in computer vision, especially in applications like autonomous driving, robot navigation, and intelligent surveillance. …”
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NID-DETR: A novel model for accurate target detection in dark environments by Qingyuan Pan, Qiang Liu, Wei Huang

“…Finally, in the target detection output layer, we adopt strategies to reduce concatenation operations and optimize small object detection heads to decrease the model parameter count and improve precision. …”
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