Multiple Instance Learning With Instance-Level Positive-Unlabeled Learning in Anomaly Detection by Ryosuke Matsuo, Shinya Yasuda, Hiroshi Yoshida

Subjects: “…Anomaly detection…”
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Data Augmentation With Flickering Backgrounds and Instances for Instance Segmentation by Kisu Lee, Jungeun Kim, Ha Young Kim

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Tomato ripeness detection and fruit segmentation based on instance segmentation by Jinfan Wei, Yu Sun, Yu Sun, Lan Luo, Lingyun Ni, Mengchao Chen, Minghui You, Minghui You, Ye Mu, Ye Mu, He Gong, He Gong

“…The method showcases its superiority in tomato maturity detection and fruit segmentation, thus providing an effective approach to achieving precise picking.…”
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Segmenting Brain Tumor Detection Instances in Medical Imaging with YOLOv8 by Md Javeed Khan, Mohammed Raahil Ahmed, Mohammed Abdul Aziz Taha, Ruhiat Sultana

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Detecting infrared UAVs on edge devices through lightweight instance segmentation. by YuZhi Chen, HaoYue Sun, Liang Tian, Ye Yang, ShenYang Wang, TianYou Wang

“…<h4>Motivation</h4>Infrared unmanned aerial vehicle (UAV) detection for surveillance applications faces three conflicting requirements: accurate detection of pixel-level thermal signatures, real-time processing capabilities, and deployment feasibility on resource-constrained edge devices. …”
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Incoherent Region-Aware Occlusion Instance Synthesis for Grape Amodal Detection by Yihan Wang, Shide Xiao, Xiangyin Meng

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Using Variational Autoencoders for Out of Distribution Detection in Histological Multiple Instance Learning by Francisco Javier Saez-Maldonado, Luz Garcia, Lee A. D. Cooper, Jeffery A. Goldstein, Rafael Molina, Aggelos K. Katsaggelos

Subjects: “…Out-of-distribution detection…”
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Monocular 3D object detection with thermodynamic loss and decoupled instance depth by Gang Liu, Xiaoxiao Xie, Qingchen Yu

“…The proposed method is called the monocular 3D object detection network with thermodynamic loss and decoupled instance depth (TDN). …”
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Pretraining instance segmentation models with bounding box annotations by Cathaoir Agnew, Eoin M. Grua, Pepijn Van de Ven, Patrick Denny, Ciarán Eising, Anthony Scanlan

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SHAP-Instance Weighted and Anchor Explainable AI: Enhancing XGBoost for Financial Fraud Detection by Putthiporn Thanathamathee, Siriporn Sawangarreerak, Siripinyo Chantamunee, Dinna Nina Mohd Nizam

Subjects: “…fraud detection…”
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Real-Time Power System Event Detection: A Novel Instance Selection Approach by Gabriel Intriago, Yu Zhang

“…This study presents a novel adaptation of the Hoeffding Adaptive Tree (HAT) classifier with an instance selection algorithm that detects and identifies cyber and non-cyber contingencies in real time to enhance the situational awareness of cyber-physical power systems (CPPS). …”
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Dam Crack Instance Segmentation Algorithm Based on Improved YOLOv8 by Shuaisen Ma, Mingyue Xu, Weiwu Feng

Subjects: “…Dam crack detection…”
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Distinguishing Difficulty Imbalances in Strawberry Ripeness Instances in a Complex Farmland Environment by Yang Gan, Xuefeng Ren, Huan Liu, Yongming Chen, Ping Lin

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A Self-Paced Multiple Instance Learning Framework for Weakly Supervised Video Anomaly Detection by Ping He, Huibin Li, Miaolin Han

Subjects: “…weakly supervised video anomaly detection…”
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PW-BALFC, a clinical dataset for detection and instance segmentation of bronchoalveolar lavage fluid cell by Xin Shi, Qing Huang, Teng Xu, Hongwen Mei, Tingwei Quan, Xiuli Wang, Yinghan Shi, Ye Hu, Zhimei Duan, Fei Xie, Sifan Li, Lixin Xie, Kaifei Wang

“…However, there is a lack of public clinical BALF cell datasets for the detection of different cell types and a lack of pixel-level annotations for cytomorphology analysis. …”
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Two‐stage video anomaly detection based on dual‐stream networks and multi‐instance learning by Dejun Zhang, Wenbo Fang, Yuhang Liu, Zirong Lyu, Chen Xiong, Zhan Wang

“…Abstract To promptly detect abnormal events in surveillance videos, this article designs a video anomaly detection method based on multiple instance learning. …”
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AFQSeg: An Adaptive Feature Quantization Network for Instance-Level Surface Crack Segmentation by Shaoliang Fang, Lu Lu, Zhu Lin, Zhanyu Yang, Shaosheng Wang

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Deep learning-based image classification of sea turtles using object detection and instance segmentation models. by Jong-Won Baek, Jung-Il Kim, Chang-Bae Kim

“…This study compared the performance of two state-of-the-art DL methods namely; the object detection model (YOLOv5) and instance segmentation model (YOLOv5-seg), to detect and classify sea turtles. …”
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DepressionMIGNN: A Multiple-Instance Learning-Based Depression Detection Model with Graph Neural Networks by Shiwen Zhao, Yunze Zhang, Yikai Su, Kaifeng Su, Jiemin Liu, Tao Wang, Shiqi Yu

“…To address depression detection as a chronic long-term disorder reflected by temporal behavioral patterns, we propose a novel framework that segments videos into utterance-level instances using GRU for contextual representation, and then constructs graphs where utterance embeddings serve as nodes connected through dual relationships capturing both chronological development and intermittent relevant information. …”
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SIGKD: A Structured Instance Graph Distillation Method for Efficient Object Detection in Remote Sensing Images by Fangzhou Liu, Wenzhe Zhao, Haoxiang Qi, Guangyao Zhou

“…In the realm of remote sensing image object detection compression distillation, establishing an efficient method for instance feature knowledge transfer between teacher and student models holds paramount importance. …”
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