Multi-target neural circuit reconstruction and enhancement in spinal cord injury by Lingyun Cao, Siyun Chen, Shuping Wang, Ya Zheng, Dongsheng Xu

Subjects: “…multi-targets…”
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A virtual rail train path recognition method based on binocular stereo vision by ZENG Junwei, GENG Li, LU Chenyang, REN Lihui

Subjects: “…virtual rail train…”
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Multi-Target Vehicle Tracking Algorithm Based on Improved DeepSORT by Dudu Guo, Zhuzhou Li, Hongbo Shuai, Fei Zhou

“…In this paper, we address the issues of insufficient accuracy and frequent identity switching in the multi-target tracking algorithm DeepSORT by proposing two improvement strategies. …”
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SDGTrack: A Multi-Target Tracking Method for Pigs in Multiple Farming Scenarios by Tao Liu, Dengfei Jie, Junwei Zhuang, Dehui Zhang, Jincheng He

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Multi‐target cognitive electronic reconnaissance for unmanned aerial vehicles based on scene reconstruction by Yun Zhang, Shixun You, Yunbin Yan, Qiaofeng Ou, Jie Liu, Ling Chen, Xiang Zhu

“…Abstract Model‐free deep reinforcement learning (DRL) is regarded as an effective approach for multi‐target cognitive electronic reconnaissance (MCER) missions. …”
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Multi-target digital material design via a conditional denoising diffusion probability model by Wei Yue, Yuan Gao, Zhenliang Pan, Fanping Sui, Liwei Lin

“…Abstract Multi-target digital material design has been challenging due to the expansive design space and instability of traditional methods in satisfying multiple objectives. …”
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Research on detection and tracking methods of unmanned ship water targets based on light vision by LIU Yibo, QIU Xinyu, WANG Tianhao, GAOYAN Xiusong, WANG Yintao

“…In order to achieve accurate multi-target tracking, combined with self-trained model weights and Sort algorithm, continuous tracking of targets and accurate annotation of center point trajectories are successfully implemented. …”
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A Novel and Efficient Multi-Target Backdoor Attack for Deep Learning-Based Wireless Signal Classifiers by Nayan Moni Baishya, B. R. Manoj, Snehashish Karmakar

“…Our attack method is practically realizable and does not require access to the target model’s training data or architecture, which is a less explored area in DL-based wireless systems. …”
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Multi-Targeted Textual Backdoor Attack: Model-Specific Misrecognition via Trigger Position and Word Choice by Taehwa Lee, Soojin Lee, Hyun Kwon

“…These attacks involve training a target model with samples that include specific triggers, causing the model to misclassify these triggered samples while still correctly classifying regular samples. …”
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Transferable machine learning model for multi-target nanoscale simulations in hydrogen-carbon system from crystal to amorphous by Weiqi Chen, Zhiyue Xu, Kang Wang, Lei Gao, Aisheng Song, Tianbao Ma

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Research on Multi-Target Detection and Tracking of Intelligent Vehicles in Complex Traffic Environments Based on Deep Learning Theory by Xuewen Chen, Shilong Yan, Chenxi Xia

“…The VERI-776 vehicle re-identification dataset and MARKET1501 pedestrian re-identification dataset were used to train the proposed ReID model, and multi-target tracking performance comparison experiments were conducted on the MOT16 dataset. …”
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YED-Net: Yoga Exercise Dynamics Monitoring with YOLOv11-ECA-Enhanced Detection and DeepSORT Tracking by Youyu Zhou, Shu Dong, Hao Sheng, Wei Ke

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Finding a New Balance Point: Intelligent Optimization of Multi-Target Cognitive Electronic Reconnaissance Strategy for Unmanned Aerial Vehicles by Yun Zhang, Shixun You, Yunbin Yan, Qiaofeng Ou, Xiang Zhu

“…To address the lack of an effective strategy for Unmanned Aerial Vehicles (UAVs) to perform Multi-Target Reconnaissance (MTR) against netted radar system, a reconnaissance pseudo-target is shaped and used to guide the UAV to quickly approach a key reconnaissance area. …”
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Machine Vision-Based Real-Time Monitoring of Bridge Incremental Launching Method by Haibo Xie, Qianyu Liao, Lei Liao, Yanghang Qiu

“…The method designs a kind of cross target, and realizes efficient detection, recognition, and tracking of multiple targets during the dynamic process of beam incremental launching by training a YOLOv5 target detection model and a DeepSORT multi-target tracking model. …”
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Flavonoids in atopic dermatitis: mechanisms, delivery innovations, and translational strategies by Dongdong Li, Dongdong Li, Yusheng Han, Jingjing Zhou, Jing Chen, Hong Liang Tey, Hong Liang Tey, Hong Liang Tey, Timothy T. Y. Tan, Timothy T. Y. Tan

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Research on lidar target detection for metro scene by PAN Wenbo, LI Cheng, YUAN Xiwen, LONG Teng, ZENG Xiang, XIE Guotao

“…Then, the forward limit of train passage was constructed based on the extracted rail track position in real time. …”
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Multi-fidelity graph neural networks for predicting toluene/water partition coefficients by Thomas Nevolianis, Jan G. Rittig, Alexander Mitsos, Kai Leonhard

“…We explore the transfer learning, feature-augmented learning, and multi-target learning approaches in combination with graph neural networks, validating them on two external datasets: one with molecules similar to training data (EXT-Zamora) and one with more challenging molecules (EXT-SAMPL9). …”
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AlzhCPI: A knowledge base for predicting chemical-protein interactions towards Alzheimer's disease. by Jiansong Fang, Ling Wang, Yecheng Li, Wenwen Lian, Xiaocong Pang, Hong Wang, Dongsheng Yuan, Qi Wang, Ai-Lin Liu, Guan-Hua Du

“…To confront AD, scientists are searching for multi-target-directed ligands (MTDLs) to delay disease progression. …”
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Multi-Underwater Target Interception Strategy Based on Deep Reinforcement Learning by Wenhao GAN, Yunfei PENG, Lei QIAO

“…Training results show rapid convergence and high success rates of the proposed interception strategies. …”
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EEG-fMRI neurofeedback versus motor imagery after stroke, a randomized controlled trial by Simon Butet, Mathis Fleury, Quentin Duché, Elise Bannier, Giulia Lioi, Lou Scotto di Covella, Emilie Lévêque-Le Bars, Anatole Lécuyer, Pierre Maurel, Isabelle Bonan

“…A comparison was conducted between the efficacy of NF versus motor imagery (MI) training without feedback. We hypothesized that employing a bimodal EEG-fMRI based NF training approach would ensure precise targeting, and incorporating progressive multi-target feedback would provide a more effective mean to enhance plasticity. …”
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