Impact of Adaptive Synthetic on Naïve Bayes Accuracy in Imbalanced Anemia Detection Datasets by Muhammad Khahfi Zuhanda, Lisya Permata, Hartono, Erianto Ongko, Desniarti

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Detection of Violent Scenes in Cartoon Movies Using a Deep Learning Approach by Noreen Fayyaz Khan, Sareer Ul Amin, Zahoor Jan, Changhui Yan

“…This paper addresses the challenge of detecting subtle instances of violence within cartoon movies. …”
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Density-Aware DETR With Dynamic Query for End-to-End Tiny Object Detection by Xianhang Ye, Chang Xu, Haoran Zhu, Fang Xu, Haijian Zhang, Wen Yang

“…End-to-end DEtection TRansformer (DETRs) are leading a new trend in various object detection tasks. …”
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Integrating Pose Features and Cross-Relationship Learning for Human–Object Interaction Detection by Lang Wu, Jie Li, Shuqin Li, Yu Ding, Meng Zhou, Yuntao Shi

“…Background: The main challenge in human–object interaction detection (HOI) is how to accurately reason about ambiguous, complex, and difficult to recognize interactions. …”
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Automatic detection of floating instream large wood in videos using deep learning by J. Aarnink, J. Aarnink, T. Beucler, T. Beucler, M. Vuaridel, V. Ruiz-Villanueva, V. Ruiz-Villanueva

“…This paper presents a novel approach for detecting floating pieces of instream wood in videos. …”
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APPROACH OF PROCESSING, CLASSIFICATION AND DETECTION OF NEW CLASSES AND ANOMALIES IN HETEROGENIOUS AND DIFFERENT STREAMS OF DATA by R. A. Bagutdinov

“…The approach does not classify a new instance of the class as an existing class, but can effectively handle the functional evolution.…”
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Burned area detection based on time-series analysis in a cloud computing environment by J.A. Anaya, W.F. Sione, A.M. Rodriguez-Montellano

“…This error is then inherited by other models, for instance, those used to report Greenhouse Gas Emissions using a “bottom up” approach. …”
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A Novel Approach to Road Safety: Detecting Illegal Overtaking Using Smartphone Cameras and Deep Learning for Vehicle Auditing by Karem Daiane Marcomini, Vitória de Carvalho Brito, Gregori da Cruz Balestra, Vitor Tosetto, Luiz Carlos Duarte, Antonio Roberto Donadon

“…We confirm overtaking events by checking for overlaps between detections from both models. We store confirmed instances and evaluate the information temporally rather than just from individual frames. …”
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Making a Real-Time IoT Network Intrusion-Detection System (INIDS) Using a Realistic BoT–IoT Dataset with Multiple Machine-Learning Classifiers by Jawad Ashraf, Ghulam Musa Raza, Byung-Seo Kim, Abdul Wahid, Hye-Young Kim

“…In our research, we have developed and trained a real-time intrusion-detection system for IoT networks that can detect multiple modern and traditional threats with high accuracy. …”
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Detecting Depression via Tweets on Twitter Utilizing Machine Learning and Neural Network Models by Xinyong Lu

“…This study highlights the potential of utilizing social media data for early depression detection, providing mental health professionals with valuable insights to identify at-risk individuals and implement timely interventions.…”
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Cloud-based database framework of corrosion detecting and grading for temporary steel pipe supports by Ali Akbar, Goeun Choi, James Mugo Njoroge, Soonwook Kwon

“…The proposed multi-detection system utilizes state-of-the-art deep learning architectures, including YOLOv9 for object detection and YOLOv9-seg for instance segmentation. …”
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A Tank Experiment of the Autonomous Detection of Seabed-Contacting Segments for Submarine Pipelaying Operations by Bo Wang, Jie Wang, Chen Zheng, Ye Li, Jian Cao, Yueming Li

“…The results show that our modules can improve the performance of different neural network models for seabed-contacting segment detection. The target detection and instance segmentation performance of the best model is improved through a 6.3% increase in AP and a 3.8% increase in mean intersection over union compared with the baseline model.…”
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Transfer Learning-Based Accurate Detection of Shrub Crown Boundaries Using UAS Imagery by Jiawei Li, Huihui Zhang, David Barnard

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Occlusion-Aware Worker Detection in Masonry Work: Performance Evaluation of YOLOv8 and SAMURAI by Seonjun Yoon, Hyunsoo Kim

“…This study evaluates the performance of You Only Look Once version 8 (YOLOv8) and a SAM-based unified and robust zero-shot visual tracker with motion-aware instance-level memory (SAMURAI) for worker detection in masonry construction environments under varying occlusion conditions. …”
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Automated detection and structuration of building and vegetation changes from LiDAR point clouds by A. Kharroubi, Z. Ballouch, Z. Ballouch, I. Jeddoub, R. Hajji, R. Billen

“…Achieving 100% accuracy for detecting new buildings changes, as validated within the study dataset and methodology. …”
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UAV image analysis for detecting rice seedling gaps and gap effect on grain yield by Sanai Li, Yubin Yang, Jing Zhang, Lloyd T. (Ted) Wilson, Stanley Omar P.B. Samonte, Fugen Dou, Tanumoy Bera, Xin-Gen Zhou, Darlene Sanchez, Jing Wang

“…This study proposes a novel approach utilizing high-resolution UAV images to detect seedling gaps, providing an alternative method to estimate seedling establishment in densely planted crops such as rice. …”
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Improved Asphalt Pavement Crack Detection Model Based on Shuffle Attention and Feature Fusion by Tursun Mamat, Abdukeram Dolkun, Runchang He, Yonghui Zhang, Zulipapar Nigat, Hanchen Du

“…Subsequently, we conduct comparative testing against the results of the original model, analyzing issues such as the oversight of shallow and small cracks, truncation in the recognition of single-instance long cracks, and imprecise detection. We devise an improved detection approach based on YOLOv8. …”
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Automated detection and classification of osteolytic lesions in panoramic radiographs using CNNs and vision transformers by Niels van Nistelrooij, Iman Ghanad, Amir K. Bigdeli, Daniel G. E. Thiem, Constantin von See, Carsten Rendenbach, Ira Maistreli, Tong Xi, Stefaan Bergé, Max Heiland, Shankeeth Vinayahalingam, Robert Gaudin

“…Four model architectures for instance segmentation (Mask R-CNN with a Swin-Tiny or ResNet-50 backbone, Mask DINO, and YOLOv5) were employed with five-fold cross-validation. …”
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FsDAOD: Few-shot domain adaptation object detection for heterogeneous SAR image by Siyuan Zhao, Yong Kang, Hang Yuan, Guan Wang, Hui Wang, Shichao Xiong, Ying Luo

“…It is then asserted that confidence-based sample separation methods can improve detection efficiency by adjusting the model to prioritize the identification of more easily detected objects, but this may lead to incorrect decisions for more challenging instances. …”
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Abnormal Operation Detection of Automated Orchard Irrigation System Actuators by Power Consumption Level by Shahriar Ahmed, Md Nasim Reza, Md Rejaul Karim, Hongbin Jin, Heetae Kim, Sun-Ok Chung

“…For the second solenoid valve in channel 2, with 333 actual instances of normal operation and 60 actual instances of abnormal operation, the model accurately detected 316 normal and 58 abnormal instances. …”
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