Running machine learning experiments can be time consuming and just the compute costs can get expensive. Tracking experiments in an organized way helps with all of these core issues. Weights and Biases (wandb) is a simple tool that helps individuals to track their experiments — I talked to sev...
Experiments on challenging sequences demonstrate that the proposed tracker performs favourably against the state-of-the-art methods.doi:10.1049/el.2015.2360Wang, BaoxianBeijing Institute of TechnologyWang, ShuigenLiu, XunYang, JinglinIETElectronics Letters...
None of our label-free experiments would have been successful without employing machine learning for motion analysis. Background subtraction has been a common process to detect intrusive objects in scene analysis of a surveillance system. We succeeded at introducing the computer vision technique to the...
Animal models play an important role in the scientific investigation of brain mechanisms involved in cognition, learning, and other behavioral functions1,2,3,4,5,6. Animal behavioral studies require the administration of experiments, video recording of the experiments, and parameter quantity analysis ...
imgaug: Image augmentation for machine learning experiments solt: Image Streaming over lightweight data transformations Deep Learning Deformable Convolutional Networks RNNexp Grad-CAM: Gradient-weighted Class Activation Mapping Class Imbalance Imbalanced Dataset Sampler [pytorch] Iterable dataset resampling in Py...
Experiments are presented in Section 5, while conclusions are given in Section 6. Access through your organization Check access to the full text by signing in through your organization. Access through your organization Section snippets System introduction The main sensor used in this paper is ...
The main contribution of this study was the concurrent application of EEG and eye tracking techniques during n-back tasks as part of the methodology for addressing the problem of mental workload classification through machine learning algorithms. The experiments involved 15 university st...
tracking. Besides these contributions, we also introduce a new dictionary learning algorithm with a locally constrained sparse representation, called K-Selection. Based on a set of comprehensive experiments, our algorithm has demonstrated better performance than alternatives reported in the recent literature...
💀 - Processing experiments around skeleton tracking with Kinect kinectdrawstarter-kitskeleton-tracking UpdatedFeb 22, 2017 Processing fbdp1202/pyukf_kinect_body_tracking Star24 improve performance of skeleton data from kinect v2 body tracking sdk using unscented kalman filter ...
DeepLabStream enables closed-loop behavioral experiments using deep learning-based markerless, real-time posture detection ArticleOpen access29 January 2021 SLEAP: A deep learning system for multi-animal pose tracking ArticleOpen access Automatic mapping of multiplexed social receptive fields by deep learni...