… , deep learning has been reinvigorated and performed many results in agricultural applications.
The popular image datasets for deep learning … a verified annotated dataset of UAV …

… This dataset is described in … art datasets, Section V is devoted to a comparative study between
the results of classical machine learning and deep learning algorithms on FallAllD dataset …

… Additional Dataset Contributions: A subset of contributed data not selected by the CUBDL
organizers for evaluation of Task 1 are included in the open dataset [16] published with this …

… 3.1 Deep learning for segmentation In this section, we present our deep learning approach
… ARs and TCs, using the curated ClimateNet dataset. We model this problem as a semantic …

… deep learning (DL)-enabled signal demodulation methods and establish the first open dataset
… prototype platform for measuring real modulation dataset. Then, based on the measured …

… dataset for training machine learning models to statically detect malicious Windows portable
executable files. The dataset … A recent example of end-to-end deep learning for malware …

… size, transfer learning (9) is a commonly used deep learning … a different but related task in
deep learning. Due to the lack of … learning has become a popular method in deep learning, …

… We consider 5 deep learning approaches to the problem and evaluate their performance;
(1) Binary classification using “Disc” (2) Multiclass classification using “DClass” (3) A binary …

… various machine learning methods (eg, BoVWs, spatial pyramid match kernels) for the
classification of the UCM and BCS dataset. In the context of deep learning, the deep CNNs used …

… in research activity on deep learning [21]. The goal of the fastMRI dataset is to provide a first
step towards enabling similar breakthroughs in the machine-learning-based reconstruction …