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RAWPED is a dataset for detection of pedestrians in the context of railways. The dataset is labeled box-wise. 26000 Images Object recognition and classification 2020 [70] [71] Tugce Toprak, Burak Belenlioglu, Burak Aydın, Cuneyt Guzelis, M. Alper Selver OSDaR23 OSDaR23 is a multi-sensory dataset for detection of objects in the context of railways.
The CIFAR-10 dataset (Canadian Institute For Advanced Research) is a collection of images that are commonly used to train machine learning and computer vision algorithms. It is one of the most widely used datasets for machine learning research. [1] [2] The CIFAR-10 dataset contains 60,000 32x32 color images in 10 different classes. [3]
The datasets are classified, based on the licenses, as Open data and Non-Open data. The datasets from various governmental-bodies are presented in List of open government data sites. The datasets are ported on open data portals. They are made available for searching, depositing and accessing through interfaces like Open API. The datasets are ...
In 2021, ImageNet-1k was updated by annotating faces appearing in the 997 non-person categories. They found training models on the dataset with these faces blurred caused minimal loss in performance. [31] ImageNetV2 was a new dataset containing three test sets with 10,000 each, constructed by the same methodology as the original ImageNet. [32]
Image credits: micmac2869 Dogs can start acting like cats because they are highly impressionable. If the pooch has spent more time around felines than their own species, there’s a high chance ...
"I [thought to myself], ‘Oh, no, this is not going to happen today,’ ” Linda Rosa recalled of the incident
Cats on the other hand, well, that's a different story. Amir Anwary is a veterinarian that is very active on social media. He posts lots of helpful tips and information about pets, but he also has ...
A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]