Sensor-based technologies are playing a key role in making artificial intelligence (AI) possible in various fields. LiDAR is one of the most promising sensor-based technology, used in autonomous vehicles or self-driving cars and became essential for such autonomous machines to get aware of its surroundings and drive properly without any collision risks. Autonomous vehicles already use various sensors and LiDAR is one of them that helps to detect the objects in-depth. So, right here we will discuss LiDAR technology, how it works, and why it is important for autonomous vehicles or self-driving cars. LIDAR stands for Light Detection and Ranging is a kind of remote sensing technology using the light in the form of a pulsed laser to measure ranges (variable distances) to the Earth.

AI Business Directory is a list of key companies (including startups and big corporations) worldwide with products, services, and applications in the fields related to the Artificial Intelligence (AI). A registered user can submit a listing and maintain it for your own business. The listing service is free. Typical AI fields include, but not limited to: Machine Learning (ML), Deep Learning, Cognitive Computing, Natural Language Processing (NLP), Computer Vision, Pattern Recognition, Autonomous Agents and Multi-Agent Systems, Automated Planning and Scheduling, Robotics, Predictive Analytics, etc. Typical AI applications include, but not limited to: Smart Agriculture, Healthcare, Manufacturing, Smart Cities, Smart Grids, Smart Mobility, Smart Lighting, Smart Buildings, Smart Home, Autonomous Vehicles, Supply Chain and Logistics, Cybersecurity, etc.

Anolytics offers a low-cost annotation service for machine learning and artificial intelligence model developments. It is providing the precisely annotated data in the form of text, images and videos using the various annotation techniques while ensuring the accuracy and quality. It is specialized in Image Annotation, Video Annotation and Text Annotation with best accuracy. Anolytics is providing all leading types of data annotation service used as a data training in machine learning and deep learning. It offers Bounding Boxes, Semantic Segmentation, 3D Point Cloud Annotation for fields like healthcare, autonomous driving or drone falying, retail, security surveillance and agriculture.

The new Create ML app just announced at WWDC 2019, is an incredibly easy way to train your own personalized machine learning models. All that's required is dragging a folder containing your training data into the tool and Create ML does the rest of the heavy lifting. So how do we prepare our data? When doing image or sound classification we just need to organize the data into folders, but if we want to do object detection the task becomes a bit more complicated. With object detection, we need to specify some additional information.

IBM developer Nicholas Bourdakos recently created a new Code Pattern that lets just about anyone develop and train an AI model to recognize objects using computer vision. Bourdakos' Code Pattern, called "Create a real-time object detection app using Watson Machine Learning," relies on a tool called Cloud Annotations. It's basically a blueprint for training an AI model to recognize whatever objects you train it on, with a tool that makes labeling your data dead simple. I saw someone doing emoji classification and I thought it would be a cool project to work on with Cloud Annotations and real-time object detection. Using Cloud Annotations and the Code Pattern is relatively simple. In this code pattern, you'll build an iOS app that lets you use your own custom-trained models to detect objects.