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Developed at Google Research, HyperTransformer decouples the task space and individual task complexity to generate all model weights in just one pass — while also offering support for unlabeled sample ingestion.
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featured
Developed at Google Research, HyperTransformer decouples the task space and individual task complexity to generate all model weights in just one pass — while also offering support for unlabeled sample ingestion.
Featured
FaceBit aims to be low-cost, energy-efficient, and easy-to-integrate hardware with rich sensing functionalities– monitors physiological signals
Featured
Hardware and software engineers will be the lifeblood of tomorrow's connected world. Academia is working hard to ensure a steady supply, in part by adapting engineering education to train the next generation of IoT innovators.
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Understanding industrial vision systems by examining their components, imaging fundamentals, AI integration since 2020, and how to choose the right solution for every application.
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TAGGED WITH computer vision
EPFL researchers are developing AI models that could one day enable vision prosthetics able to restore meaningful, object-level sight for the blind.
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Understanding industrial vision systems by examining their components, imaging fundamentals, AI integration since 2020, and how to choose the right solution for every application.
The AI-powered tool could inform the design of better sensors and cameras for robots or autonomous vehicles.
Latest Posts
Developed at Google Research, HyperTransformer decouples the task space and individual task complexity to generate all model weights in just one pass — while also offering support for unlabeled sample ingestion.
FaceBit aims to be low-cost, energy-efficient, and easy-to-integrate hardware with rich sensing functionalities– monitors physiological signals
Hardware and software engineers will be the lifeblood of tomorrow's connected world. Academia is working hard to ensure a steady supply, in part by adapting engineering education to train the next generation of IoT innovators.
3 minutes read
Designed to dramatically reduce the amount of training data needed for an image recognition system, this one-shot approach "inspired by nativism" takes a leaf from humans' ability to intuit and abstract.
ML can be deployed on Embedded Sensors to unleash the full power of Industry 4.0.
Advances in software allow a customized car to perform controlled, autonomous drifting to enhance active safety and to give drivers the skills of professional racers.
With the help of new technologies, artificial intelligence, and digital monitoring, more healthcare will be provided in patients’ homes.
3 minutes read
BottleFit framework applied DNN models in image classification achieves 77.1% data compression with up to 0.6% accuracy loss on the ImageNet dataset.
In this article, we look at two tinyML projects for education. We show how Backyard Brains uses low-cost experiment kits to make neuroscience education more accessible. We also introduce our readers to a specialisation offered by Harvard & Google to help students learn tinyML like never before.
Considered obsolete since the introduction of vision transformers, ConvNeXt proves there's life in convolution yet — outperforming its rivals by adopting some of their own tricks.
A holistic open-source framework to improve the performance of multiple modalities and outperform the existing single-modality algorithms.
#6 of our 'Voice of Innovation' fireside chat series: Robotics and AI reporter Rachel Gordon speaks to IoT networking savant Wienke Giezeman.
Soon, internet users will be able to meet each other in cyberspace as animated 3D avatars. Researchers at ETH Zurich have developed new algorithms for creating virtual humans much more easily.
4 minutes read
MotionCam-3D by Photoneo enables 3D scanning & handling of objects that are moving on an overhead conveyor without interruption. The camera provides high-quality 3D data even while the objects are moving, swinging, or slightly rotating.
ETH researchers led by Marco Hutter developed a new control approach that enables a legged robot, called ANYmal, to move quickly and robustly over difficult terrain. Thanks to machine learning, the robot can combine its visual perception of the environment with its sense of touch for the first time.
3 minutes read
