Understandings of the three-dimensional social behaviors of freely moving large-size mammals are valuable for both agriculture and life science, yet challenging due to occlusions in close interactions. Although existing animal pose estimation methods cap
Pretrain, finetune ANY AI model of ANY size on multiple GPUs, TPUs with zero code changes. - Lightning-AI/pytorch-lightning
With all the successfully localized patches, we take their minimum bounding rectangle Bt(rt)k as the initialization of tracked object location. As a class-specific proposal, Bt(rt)k can be further refined based on the objectness, as in Faster- RCNN [30]. We use such a ...
[25]. Model training and evaluation were accomplished using PyTorch deep learning library, while all graph convolutions were accomplished via PyTorch Geometric [20,54]. Ablation experiments were performed by removing graph convolution modules and attention modules with multilayer perceptron (MLP) layers ...
PyTorch (> = 1.11.0 ) is required. We run the experiments on Python 3.11.7. The datasets ana- lysed during the current study are available in the following repositories: · Bacteria: https://github.com/AWebZen/Funct ionalPrediction5000species...
PyTorch (> = 1.11.0 ) is required. We run the experiments on Python 3.11.7. The datasets ana- lysed during the current study are available in the following repositories: · Bacteria: https://github.com/AWebZen/Funct ionalPrediction5000species...
Then, we conduct our experiment in a running environment of CUDA version 10.2, Pytorch version 1.6.0, and Python version 3.7.6. We also selected a high-performance workstation with an AMD 5950x CPU, 64-GB memory, and a GTX 3090 GPU (referred to as environment W) to test the ...
Pretrain, finetune ANY AI model of ANY size on multiple GPUs, TPUs with zero code changes. - Lightning-AI/pytorch-lightning
Results of the EASE with the settings of Support Vector Regression (SVR) and Bayesian Linear Ridge Regression (BLRR) are reported in previous study [7]. (2) CNN-LSTM [4] combines CNN ensembles and LSTM ensembles over 10 runs and obtained the best result in their experiment. (3) LSTM-...
According to the experimental results in Figure 7, the two-stage target detection algorithms are R-CNN and Faster R-CNN. In the process of target detection, candidate frames need to be generated, target classification and location regression, respectively, resulting in a large number of redundant...