Semantically-Enhanced Feature Extraction with CLIP and Transformer Networks for Driver Fatigue Detection by Zhen Gao, Xiaowen Chen, Jingning Xu, Rongjie Yu, Heng Zhang, Jinqiu Yang

Subjects: “…fatigue detection…”
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A Cascaded Defect Detection Algorithm for Track Components by LIN Jun, KANG Gaoqiang, TU Zhenwei, XU Yanghan, YUE Wei, XIONG Qunfang

Subjects: “…defect detection…”
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Food Waste Detection in Canteen Plates Using YOLOv11 by João Ferreira, Paulino Cerqueira, Jorge Ribeiro

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Correction: Optimizing Mask R-CNN for enhanced quinoa panicle detection and segmentation in precision agriculture by Manal El Akrouchi, Manal El Akrouchi, Manal Mhada, Dachena Romain Gracia, Malcolm J. Hawkesford, Bruno Gérard

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An improved multi-object instance segmentation based on deep learning by Nawaf Alshdaifat, Mohd Azam Osman, Abdullah Zawawi Talib

“… Given the recent breakthroughs in recent years, Deep learning (DL) networks have attracted growing interest and attention by researchers and scholars alike due to its importance in detecting and instance segmentation of objects in an image. …”
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Real-Time Instance Segmentation Models for Identification of Vehicle Parts by Abdulmalik Aldawsari, Syed Adnan Yusuf, Riad Souissi, Muhammad AL-Qurishi

“…The YOLACT-based part localization and segmentation method outperformed other real-time instance mechanisms with an mAP of 66.5. For the workshop repair dataset, SipMask++ reported better accuracy for object detection with a mAP of 57.0, with outcomes for APIoU=.50 and APIoU=.75 reporting 72.0 and 67.0, respectively, whereas YOLACT was observed to be a better performer for APs with 44.0 and 2.6 for object detection and segmentation categories, respectively.…”
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A recent survey on instance-dependent positive and unlabeled learning by Chen Gong, Muhammad Imran Zulfiqar, Chuang Zhang, Shahid Mahmood, Jian Yang

“…This setting has practical importance in many real-world applications such as medical diagnosis, outlier detection, object detection, etc. In this survey, we first present the preliminary knowledge of PU learning, and then review the representative instance-dependent PU learning settings and methods. …”
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SPBA-Net point cloud object detection with sparse attention and box aligning by Haojie Sha, Qingrui Gao, Hao Zeng, Kai Li, Wang Li, Xuande Zhang, Xiaohui Wang

Subjects: “…3D object detection…”
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Image-Level Anti-Personnel Landmine Detection Using Deep Learning in Long-Wave Infrared Images by Jun-Hyung Kim, Goo-Rak Kwon

“…This study proposes a simple deep learning-based framework for image-level anti-personnel landmine detection in long-wave infrared imagery. To address challenges posed by the limited size of the available dataset and the small spatial size of anti-personnel landmines within images, we integrate two key techniques: transfer learning using pre-trained vision foundation models, and attention-based multiple instance learning to derive discriminative image features. …”
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Optimal-Transport-Based Positive and Unlabeled Learning Method for Windshear Detection by Jie Zhang, Pak-Wai Chan, Michael Kwok-Po Ng

Subjects: “…light detection and ranging…”
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Updating “BePLi Dataset v1: Beach Plastic Litter Dataset version 1, for instance segmentation of beach plastic litter” with 13 object classesSeanoe by Mitsuko Hidaka, Koshiro Murakami, Shintaro Kawahara, Yujin Nakagawa, Daisuke Sugiyama, Shin’ichiro Kako, Daisuke Matsuoka

“…The BePLi Dataset v2 allows users to develop an instance segmentation and object detection method detecting macro beach plastic litter individually and at the pixel level. …”
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Cucumber Leaf Segmentation Based on Bilayer Convolutional Network by Tingting Qian, Yangxin Liu, Shenglian Lu, Linyi Li, Xiuguo Zheng, Qingqing Ju, Yiyang Li, Chun Xie, Guo Li

Subjects: “…dense target detection…”
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Automated Detection, Localization, and Severity Assessment of Proximal Dental Caries from Bitewing Radiographs Using Deep Learning by Mashail Alsolamy, Farrukh Nadeem, Amr Ahmed Azhari, Walaa Magdy Ahmed

“…We analyzed 1354 BRs annotated by a consultant of restorative dentistry to delineate the pertinent categories, concentrating on the detection and localization of caries tasks. A pre-trained YOLOv11-based instance segmentation model was employed, allocating 80% of the dataset for training, 10% for validation, and the remaining portion for evaluating the model on unseen data. …”
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Instance segmentation and automated pig posture recognition for smart health management by Md Nasim Reza, Md Sazzadul Kabir, Md Asrakul Haque, Hongbin Jin, Hyunjin Kyoung, Young Kyoung Choi, Gookhwan Kim, Sun-Ok Chung

“…The objective of this study was to recognize and detect pig posture using a masked-based instance segmentation for automated pig monitoring in a closed pig farm environment. …”
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Transformer-Based Person Detection in Paired RGB-T Aerial Images With VTSaR Dataset by Xiangqing Zhang, Yan Feng, Nan Wang, Guohua Lu, Shaohui Mei

Subjects: “…Aerial-based person detection…”
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MSNet: A multispectral-image driven rapeseed canopy instance segmentation network by Yuang Yang, Xiaole Wang, Fugui Zhang, Zhenchao Wu, Yu Wang, Yujie Liu, Xuan Lv, Bowen Luo, Liqing Chen, Yang Yang

“…In addition, comparisons with various RGB-only instance segmentation models show that all the proposed MSNet-HAFB fusion models significantly outperform single-modal models in rapeseed count detection tasks, confirming the potential advantages of multispectral fusion strategies in agricultural target recognition. …”
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Advanced segmentation models for automated capsicum peduncle detection in night-time greenhouse environments by Ayan Paul, Rajendra Machavaram

Subjects: “…Capsicum peduncle detection…”
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E-Commerce Image Enhancement Method Based on Instance Segmentation and Background Replacement by Qiang Gao, Huiping Hu, Wei Liu

“…This paper proposes a novel image enhancement method that integrates instance segmentation, dominant color detection, background replacement, realistic shadow generation, and logo addition into a unified framework, optimized for e-commerce product images. …”
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Weakly supervised multiple-instance active learning for tooth-marked tongue recognition by Feilin Deng, Shangxuan Li, Zizhu Yang, Wu Zhou

“…Current deep learning methods for tooth mark detection require extensive manual labeling and tongue segmentation, which is labor-intensive. …”
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Transfer Learning-Driven Cattle Instance Segmentation Using Deep Learning Models by Rotimi-Williams Bello, Pius A. Owolawi, Etienne A. van Wyk, Chunling Tu

“…Among the emerging applications of artificial intelligence is animal instance segmentation, which has provided a practical means for various researchers to accomplish some aim or execute some order. …”
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