GitHub

Flash LiDAR Vehicle Detection with MATLAB Dataset and Deep Learning Benchmarks

This repository provides code and workflows to test several state-of-the-art vehicle detection deep learning algorithms —including YOLOX, SalsaNext, and RandLA-Net— on a Flash Lidar dataset. The ...
marktechpost

Implementing Deep Q-Learning (DQN) from Scratch Using RLax JAX Haiku and Optax to Train a CartPole Reinforcement Learning Agent

In this tutorial, we implement a reinforcement learning agent using RLax, a research-oriented library developed by Google DeepMind for building reinforcement learning algorithms with JAX. We combine ...
Scientific Research Publishing

Deep Learning-Based Multi-Class Classification of Retinal Diseases from OCT Images Using Transfer Learning ()

1 Amazon Web Services, Seattle, USA. 2 Rajiv Gandhi University of Knowledge Technologies, Nuzvid, India. Optical Coherence Tomography (OCT) is a non-invasive imaging modality widely employed for ...
Hosted on MSN

DenseNet Architecture Explained | Beginner’s Deep Learning Tutorial

Learn about DenseNet, one of the most powerful deep learning architectures, in this beginner-friendly tutorial. Understand its structure, advantages, and how it’s used in real-world AI applications.
Science Daily

Deep learning revolutionizes cytoskeleton research

A research team has developed a groundbreaking deep learning-based method for analyzing the cytoskeleton -- the structural framework inside cells -- more accurately and efficiently than ever before.
IEEE

Improved Deep Learning-Based Microwave Inversion With Experimental Training Data

Abstract: Deep learning-based inversion methods show great promise. The most common way to develop deep learning inversion techniques is to use synthetic (i.e., computationally-generated) data for ...
IEEE

Nanobot-Assisted Pollination for Sustainable Agriculture: A Review of Image Classification and Deep Learning Techniques With YOLO, SLAM, and MATLAB

Abstract: The global decrease in native pollinators poses a substantial challenge to agricultural production and food security, particularly in malnutrition prone countries. There is a huge potential ...