Machine learning models are provided experiences in the form of training data, and are tuned to produce accurate predictions for the training data by an optimization algorithm. The main goal of the models are to be able to generalize their learned expertise, and deliver correct predictions for ...
In recent years, agriculture has become a major field of application and transfer for AI. The paper gives an overview of the topic, focusing agricultural p
3.3 Evolution of deep learning models and applications The evolution of deep learning models started during the late 1990s with the introduction of convolutional neural networks. Since then, deep neural networks have been improved with several theoretical and practical upgrades. In what follows, we dis...
NVIDIA TAO is a low-code AI toolkit built on TensorFlow and PyTorch, which simplifies and accelerates the model training process by abstracting away the complexity of AI models and the deep learning framework. With TAO, users can select one of 100+ pre-trained vision AI models from NGC and ...
overcomplex for a given training set but, at the same time, introducing mechanisms that prevent the algorithm from over-fitting. There are various ways to increase generalization ability of DL models (and avoid over-fitting), for example by means of regularization mechanisms (Kukacka et al.2017...
$ tao deploy detectnet_v2--helpusage: detectnet_v2[-h][--gpu_index GPU_INDEX][--log_file LOG_FILE]{evaluate,gen_trt_engine,inference}... Transfer Learning Toolkit optional arguments: -h,--helpshow thishelpmessage andexit--gpu_indexGPU_INDEX The index of the GPU to be used.--log_fil...
Active learning:Active learning in Intel Geti software enables users to start building computer vision models with as few as 10-20 images and iterate on those models with the help of domain experts. The algorithm selects samples from the dataset that help the model learn quickly...
With the rise of Deep Learning approaches in computer vision applications, significant strides have been made towards vehicular autonomy. Research activity in autonomous drone navigation has increased rapidly in the past five years, and drones are moving fast towards the ultimate goal of near-complete...
Moreover, due to its deep-learning-based algorithm architecture, YOLO series of object detection algorithms possess a better robustness, which lays a solid foundation for their wide application. Figure 1. The object detection mechanism of the YOLO series algorithms. Based on their excellent ...
Bridging Theory and Algorithm for Domain Adaptation [ICML2019] [Pytorch] On Learning Invariant Representation for Domain Adaptation [ICML2019] [code] Unsupervised Domain Adaptation Based on Source-guided Discrepancy [AAAI2019] Learning Bounds for Domain Adaptation [NIPS2007] Analysis of Representations for...