Results 131 to 140 of about 4,346 (236)

An Efficient Implementation of the Fast Product Multi-Sensor Labeled Multi-Bernoulli Filter

In Random Finite Set based multi-sensor multi-object tracking, the NP-hard measurement-to-track assignment problem is a key challenge. One approach to address this challenge involves executing computationally simpler single-sensor updates based on a ...
Scheible, Alexander, Buchholz, Michael, Dietmayer, Klaus, Hermann, Charlotte   +3 more
core   +1 more source

From Strain to Pressure: Atomically Resolved Mechanisms of Stress Dissipation in Emissive, Elastically Deformable Molecular Crystals Under Ambient and High Pressure

Advanced Optical Materials, Volume 14, Issue 21, 5 June 2026.
Molecular crystals must withstand both isotropic and anisotropic stress to function in flexible optoelectronics and high‐pressure devices. In situ high‐pressure single‐crystal X‐ray diffraction coupled with DFT‐D computations reveal how an emissive molecular crystal with interdigitated packing bends elastically at ambient‐pressure and remains ...
Arif H. Dar, Vikram C. Joshi, Alexandra Longcake, Tamador Alkhidir, Ayat Al Nimer, Praveen B. Managutti, Shamraiz H. Talib, Jaime Viegas, Michael R. Probert, Changquan C. Sun, Sharmarke Mohamed   +10 more
wiley   +1 more source

Multi-Object Tracking Using Labeled Multi-Bernoulli Random Finite Sets

, 2014
In this paper, we propose the labeled multi-Bernoulli filter which explicitly estimates target tracks and provides a more accurate approximation of the multi-object Bayes update than the multi-Bernoulli filter.
Vo, Ba Tuong, Vo, Ba-Ngu, Reuter, S., Dietmayer, K.   +3 more
core  

Joint underwater target detection and tracking with the Bernoulli filter using an acoustic vector sensor

, 2016
In this paper, we study the problem of joint underwater target detection and tracking using an acoustic vector sensor (AVS). For this challenging problem, first a realistic frequency domain simulation is set up.
Guldogan, Mehmet B., Gunes, Ahmet
core   +1 more source

AutomataGPT: Transformer‐Based Forecasting and Ruleset Inference for Two‐Dimensional Cellular Automata

Advanced Science, Volume 13, Issue 33, 15 June 2026.
We introduce AutomataGPT, a generative pretrained transformer (GPT) trained on synthetic spatiotemporal data from 2D cellular automata to learn symbolic rules. Demonstrating strong performance on both forward and inverse tasks, AutomataGPT establishes a scalable, domain‐agnostic framework for interpretable modeling, paving the way for future ...
Jaime A. Berkovich, Noah S. David, Markus J. Buehler   +2 more
wiley   +1 more source

INB3P: A Multi‐Modal and Interpretable Co‐Attention Framework Integrating Property‐Aware Explanations and Memory‐Bank Contrastive Fusion for Blood–Brain Barrier Penetrating Peptide Discovery

Advanced Science, Volume 13, Issue 34, 19 June 2026.
INB3P is a multimodal framework for blood–brain barrier‐penetrating peptide prediction under extreme data scarcity and class imbalance. By combining physicochemical‐guided augmentation, sequence–structure co‐attention, and imbalance‐aware optimization, it improves predictive performance and interpretability.
Jingwei Lv, Qianyang Wu, Jian Liu, Binlu Yang, Yuanhao Li, Junlin Xu, Yajie Meng, Leyi Wei, Zilong Zhang, Quan Zou, Xiulai Li, Feifei Cui   +11 more
wiley   +1 more source

Integrating Radiomics and Computational Pathology to Predict Early Recurrence of Pancreatic Ductal Adenocarcinoma and Uncover Its Biological Basis in Tumor Microenvironment

Advanced Science, Volume 13, Issue 32, 9 June 2026.
Accurate prediction of early recurrence in pancreatic ductal adenocarcinoma is vital for optimizing treatment. A novel, integrated radiomics‐pathology machine learning model successfully forecasts recurrence risks by analyzing preoperative CT images and computational pathology.
Sihang Cheng, Fuze Cong, Shenbo Zhang, Rui Lv, Wenjia Zhang, Xinyi Ke, Juncheng Wu, Zhonghe Zhao, Kui Zhao, Di Dong, Ruofan Zhang, Zhengyu Jin, Max Seidensticker, Zhiwei Wang, Huanwen Wu, Xianlin Han, Nan Hong, Huadan Xue   +17 more
wiley   +1 more source

DOA Tracking Based on Unscented Transform Multi-Bernoulli Filter in Impulse Noise Environment. [PDF]

Sensors (Basel), 2019
Wu SY, Zhao J, Dong XD, Xue QT, Cai RH.
europepmc   +1 more source

MGDP: Mastering a Generalized Depth Perception Model for Quadruped Locomotion

Advanced Science, Volume 13, Issue 34, 19 June 2026.
ABSTRACT Perception‐based Deep Reinforcement Learning (DRL) controllers demonstrate impressive performance on challenging terrains. However, existing controllers still face core limitations, struggling to achieve both terrain generality and platform transferability, and are constrained by high computational overhead and sensitivity to sensor noise.
Yinzhao Dong, Ji Ma, Yidan Lu, Jiahui Zhang, Wanyue Li, Yeke Chen, Teng Zhang, Xuechao Chen, Zhangguo Yu, Peng Lu   +9 more
wiley   +1 more source

Adaptive Target Birth Intensity Multi-Bernoulli Filter with Noise-Based Threshold. [PDF]

Sensors (Basel), 2019
Hu X, Ji H, Liu L.
europepmc   +1 more source