The in-sensor adaptation strategy widens the range for image perception under different illumination conditions to simplify the complexity of hardware and algorithms.
Be the first to know.
Get our artificial intelligence weekly email digest.
Tagged with
artificial intelligence
ORGANIZATIONS. SHAPING THE INDUSTRY.
The Next Byte
Entertainment
The Next Byte Podcast is hosted by two young engineers - Daniel and Farbod - who select the most interesting tech/engineering cont...
165 Posts
High Tech Campus Eindhoven
High Tech
High Tech Campus Eindhoven is Europe's smartest square km and has the ultim...
49 Posts
ETH Zurich
University for science and technology
Freedom and individual responsibility, entrepreneurial spirit and open-min...
43 Posts
Carnegie Mellon University
University
A private, global research university, Carnegie Mellon stands among the wor...
24 Posts
Latest Posts
Sounds provide important information about how well a machine is running. ETH researchers have now developed a new machine learning method that automatically detects whether a machine is "healthy" or requires maintenance.
4 minutes read
Designed to address the OOD data false prediction by adaptively synthesizing virtual outliers that can maintain the model’s decision boundary during training.
Designed to address the exploding computational demands of deep neural networks, physical neural networks (PNNs) branch out from electronics into optics and even mechanics to boost performance and efficiency.
Designed for use in the human body for everything from drug delivery to less-invasive biopsies, these tiny microrobots operate under the control of a deep-learning system trained with no modelling or prior environmental knowledge.
Over the last decade, deep neural networks have emerged as the solution to several AI complex applications from speech recognition and object detection to autonomous vehicular systems.
Using a now public-access dataset, a research team has created a robotics control system which can generalize to unseen related tasks — allowing robots to interpret natural-language commands and video demonstrations.
Intelligent Automation (IA) is a set of technologies and methods for automating the work of white-collar professionals and knowledge workers. Here, we present a framework for explaining its power in terms of four main capabilities—Vision, Execution, Language, and Thinking & Learning—and how they can enable business transformations, with people and business goals at the center.
With research suggesting feral pigeons do as much as $1.1 billion in damage in the US alone, a project which pairs a commercial drone with machine learning to scare them away — without injury — could prove key to their control.
A team of experts in artificial intelligence and animal ecology have put forth a new, cross-disciplinary approach intended to enhance research on wildlife species and make more effective use of the vast amounts of data now being collected thanks to new technology.
4 minutes read
Attention: Don’t presume human or model-generated labels to be the growth truth for machine learning deployment in autonomous vehicular systems.
The proposed AI system has an accuracy between 70% and 80% that can be employed as a second referral mechanism for cardiovascular examination.
A system developed by Grégoire Courtine and Jocelyne Bloch now enables patients with a complete spinal cord injury to stand, walk and even perform recreational activities like swimming, cycling and canoeing.
4 minutes read
5 Questions to Ask Before Getting Started with Data Annotation: What is data annotation? Why is it essential? What are common label types for models? How do AI-powered data annotation tools help with the computer vision labeling process? What’s the best way to get started?
4 minutes read
By reconfiguring neural networks in artificial intelligence (AI) devices, a multi-institute team that included Penn State researchers facilitated AI systems to continually learn and adapt new data and tasks in ways that were not possible or practical before.
4 minutes read
