AI for Robots, Visional Intelligence, Behavioral Intelligence, Soft Robotics, etc.
Brain-Computer Interface, Affective Intelligence, Animal Computing, etc.
Sensory Intelligence, AI for Healthcare, Deep Analysis, etc.
This study addresses the challenge of performing visual localization in demanding conditions such as nighttime scenarios, adverse weather, and seasonal changes. Many prior studies tend to overlook unobserved keypoints during the matching process. Therefore, dense Read more…
Early diagnosis of Alzheimer’s disease is crucial to stall the deterioration of brain function, but conventional diagnostic methods require complicated analytical procedures or inflict acute pain on the patient. Then, label-free Surface-enhanced Raman spectroscopy (SERS) Read more…
For stroke survivors, diminished hand functions limit their ability to perform Activities of Daily Living (ADLs). To help stroke survivors perform rehabilitation exercises, soft robotic gloves have been utilized to assist them in actively practicing Read more…
Despite the prevalence of robotic manipulation tasks in various real-world applications of different requirements and needs, there has been a lack of focus on enhancing the adaptability of robotic grasping systems. Most of the current Read more…
We report a substrate-less nanomesh receptor that is coupled with an unsupervised meta-learning framework and can provide user-independent, data-efficient recognition of different hand tasks. The nanomesh, which is made from biocompatible materials and can be Read more…
This study addresses an image-matching problem in challenging cases, such as large scene variations or textureless scenes. To gain robustness to such situations, most previous studies have attempted to encode the global contexts of a Read more…
We propose a novel view path-planning method based on an online Multi-View Stereo (MVS) system. This method aims to incrementally construct the target three-dimensional (3D) model in real time. View paths are continually planned based Read more…
A universal and rapid bacteria detection method in diverse target media is imperative for food safety analysis and diagnosis of infectious diseases. Surface-enhanced Raman spectroscopy (SERS) shows prospective as a potentially practical method to rapidly Read more…
Learning from human feedback using event related electroencephalography (EEG) signals has attracted extensive attention recently owing to their intuitive communication ability by decoding user intentions. However, this approach requires users to perform specified tasks and Read more…
Soft wearable robotic gloves based on tendon-sheath mechanism are widely developed for assisting people with a loss of hand mobility. For these robots, knowing the fingertip forces applied to deformable objects is crucial in successfully Read more…
We develop a wearable ear-EEG acquisition tool and directly compared its performance with a conventional 32-channel scalp-EEG setup in a multi-class speech imagery classification task. Our system uses Riemannian tangent space projection of EEG covariance Read more…
While data-driven approaches could model complex sensor patterns, the required amount of labeled data increases exponentially as the number of contact points or the number of sensor subelements increase. We propose a novel deep learning Read more…
We propose a new Riemannian-based deep learning network to generate more discriminative features for electroencephalogram (EEG) classification. Our key innovation lies in learning the Riemannian barycenter for each class within a Riemannian geometric space. The Read more…
Despite recent advances in the field of explainable artificial intelligence systems, a concrete quantitative measure for evaluating the usability of such systems is nonexistent. Ensuring the success of an explanatory interface in interacting with users Read more…
Visual information plays an essential role in enhancing neural activity during mental practices. This study therefore hypothesized that applying immersive virtual reality headsets, with their ability to provide rich immersion and illusion by presenting egocentrically Read more…
We develop an ultra-sensitive skin-like sensor that discovers previously undetectable signals far from the joint, assisted by a deep neural network that deciphers patterns within the signals. By utilizing a single sensor capable of extracting Read more…
Depression is a complicated mental illness that varies in symptoms and needs the cooperation of patients. We propose a novel data-driven attempt to diagnose Major Depression Disorder (MDD) based on clinical questionnaire. It includes deep Read more…
Soft wearable hand robots with tendon-sheath mechanisms are being actively developed to assist people with lost hand mobility. For these robots, accurately estimating fingertip forces leads to successful object grasping. An approach can utilize information Read more…
