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Found 9 papers, 1 papers with code
Exploiting High Quality Tactile Sensors for Simplified Grasping
We further demonstrate that, due to the high performance of the fingertips, a complex adaptive grasping algorithm is not required for grasping of everyday objects.
NeuroHSMD: Neuromorphic Hybrid Spiking Motion Detector
Vertebrate retinas are highly-efficient in processing trivial visual tasks such as detecting moving objects, yet a complex challenges for modern computers.
HSMD: An object motion detection algorithm using a Hybrid Spiking Neural Network Architecture
The detection of moving objects is a trivial task performed by vertebrate retinas, yet a complex computer vision task.
Object recognition for robotics from tactile time series data utilising different neural network architectures
Robots need to exploit high-quality information on grasped objects to interact with the physical environment.
Rough Set Microbiome Characterisation
Microbiota profiles measure the structure of microbial communities in a defined environment (known as microbiomes).
Strawberry Detection Using a Heterogeneous Multi-Processor Platform
Over the last few years, the number of precision farming projects has increased specifically in harvesting robots and many of which have made continued progress from identifying crops to grasping the desired fruit or vegetable.
AdaBoost-CNN: An adaptive boosting algorithm for convolutional neural networks to classify multi-class imbalanced datasets using transfer learning
AdaBoost-CNN is computationally efficient, as evidenced by the fact that the training simulation time of the proposed method is 47. 33 s, which is lower than the training simulation time required for a similar AdaBoost method without transfer learning, i. e. 225. 83 s on the imbalanced dataset.
On-Device Transfer Learning for Personalising Psychological Stress Modelling using a Convolutional Neural Network
Stress is a growing concern in modern society adversely impacting the wider population more than ever before.
NatCSNN: A Convolutional Spiking Neural Network for recognition of objects extracted from natural images
Biological image processing is performed by complex neural networks composed of thousands of neurons interconnected via thousands of synapses, some of which are excitatory and others inhibitory.
