Machine learning (ML) approaches are a collection of algorithms that attempt to extract patterns from data and to associate such patterns with discrete classes of samples in the data—e.g., given a ...

This package implements the genome scan and genome-wide association studies using deep neural networks (i.e, Multi-Layer Perceptron (MLP), Convolutional Neural Network (CNN)). DeepGenomeScan offers ...

This paper explores the integration of Artificial Intelligence (AI) large language models to empower the Python programming course for junior undergraduate students in the electronic information ...

Abstract: Enabling the capability of accurate and reliable pre-cision landing for multirotor using deep reinforcement learning is presented in this paper. A realistic quadrotor landing environ-ment ...

If you find our work useful in your research, please consider citing: @article{qi2017pointnetplusplus, title={PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space}, ...

InfoWorld’s 2023 Bossie Awards recognize the year’s leading open source tools for software development, data management, analytics, AI, and machine learning. When the leaves fall, the sky turns gray, ...

This project demonstrates the implementation of real-time facial emotion recognition using the `deepface` library and OpenCV. The objective is to capture live video from a webcam, identify faces ...

Abstract: Low size, weight, and power (SWaP) fixed-wing UAVs are used in many applications, including search and rescue, surveillance, and tracking. To carry out these operations efficiently, there is ...

DeepImageJ is a user-friendly solution that enables the generic use of pre-trained deep learning models for biomedical image analysis in ImageJ. The deepImageJ environment gives access to the largest ...

VAR models analyse and predict multivariate time series data, unlike univariate autoregressive models. These models are particularly useful in fields such as economics and weather forecasting. Vector ...