1 day ago · They presented a deep-learning approach, based on a set of convolutional neural networks (trained on simulated data), to classify trajectories by three types of ...

2 days ago · This paper aims to localize and track a single source using TDOA measurements extracted from the acoustic signal recorded by a single receiver. Rather than ...

6 days ago · A review of progress in single particle tracking: From methods to biophysical insights. ... neural networks automate detection for tracking. of submicron ...

3 days ago · Improving the Successful Robotic Grasp Detection Using Convolutional Neural Networks ... Learning Data Association for Multi-Object Tracking using Only ...

3 days ago · Scheffe, “Multi-target tracking using joint probabilistic data association,” in Proc. ... Fox, “PoseCNN: A convolutional neural network for 6D object pose ...

3 days ago · Aimed at this problem, we propose a long short-term memory (LSTM)-aided association-learning sparse reconstruction framework for polarimetric inverse scattering ...

2 days ago · 2020 [3] suggested a deep learning-based CNN technique for respiratory sound classification. The suggested technique includes data pre-processing, CNN training ...

3 days ago · The conference program includes over 40 Special Sessions including Deep Learning for. Graphs, Trustworthy and Explainable Federated Learning: Towards Security ...

6 days ago · Tiny Machine Learning (TinyML) is an emerging technology proposed by the scientific community for developing autonomous and secure devices that can gather, ...

6 days ago · Deep neural networks (NNs) are among the most widely used approach to wind energy forecasting [6], [7], [8], whereas hybrid methods are typically used for solar ...