Zobrazeno 1 - 10
of 2 453
pro vyhledávání: '"P. Seifi"'
Autor:
Gonzalez-Franco, Mar, Abdlkarim, Diar, Bhatia, Arpit, Macgregor, Stuart, Fotso-Puepi, Jason Alexander, Gonzalez, Eric J, Seifi, Hasti, Di Luca, Massimiliano, Ahuja, Karan
Virtual, Mixed, and Augmented Reality (XR) technologies hold immense potential for transforming productivity beyond PC. Therefore there is a critical need for improved text input solutions for XR. However, achieving efficient text input in these envi
Externí odkaz:
http://arxiv.org/abs/2406.09579
Mid-air ultrasound haptic technology offers a myriad of temporal and spatial parameters for contactless haptic design. Yet, predicting how these parameters interact to render an ultrasound signal is difficult before testing them on a mid-air ultrasou
Externí odkaz:
http://arxiv.org/abs/2405.02808
Mid-air ultrasound technology offers new design opportunities for contactless tactile patterns (i.e., Tactons) in user applications. Yet, few guidelines exist for making ultrasound Tactons easy to distinguish for users. In this paper, we investigated
Externí odkaz:
http://arxiv.org/abs/2405.02800
Mid-air ultrasound haptic technology can enhance user interaction and immersion in extended reality (XR) applications through contactless touch feedback. Yet, existing design tools for mid-air haptics primarily support creating tactile sensations (i.
Externí odkaz:
http://arxiv.org/abs/2404.19275
Multimodal emotion recognition in conversation (MERC) and multimodal emotion-cause pair extraction (MECPE) has recently garnered significant attention. Emotions are the expression of affect or feelings; responses to specific events, thoughts, or situ
Externí odkaz:
http://arxiv.org/abs/2404.00403
Alzheimer's disease is a progressive neurodegenerative disorder that primarily affects cognitive functions such as memory, thinking, and behavior. In this disease, there is a critical phase, mild cognitive impairment, that is really important to be d
Externí odkaz:
http://arxiv.org/abs/2403.15443
Semantic Segmentation is one of the most challenging vision tasks, usually requiring large amounts of training data with expensive pixel level annotations. With the success of foundation models and especially vision-language models, recent works atte
Externí odkaz:
http://arxiv.org/abs/2403.09307
Autor:
Makvandi, Armin, Kavian, Yousef Seifi
In this paper, a machine learning-based decentralized time division multiple access (TDMA) algorithm for visible light communication (VLC) Internet of Things (IoT) networks is proposed. The proposed algorithm is based on Q-learning, a reinforcement l
Externí odkaz:
http://arxiv.org/abs/2311.14078
The mechanism of selectivity in ion channels is still an open question in biology. According to recent proposals, it seems that the selectivity filter of the ion channel, which plays a key role in the channel's function, may show quantum coherence, w
Externí odkaz:
http://arxiv.org/abs/2311.10222
Out-of-Distribution (OOD) detection is a crucial problem for the safe deployment of machine learning models identifying samples that fall outside of the training distribution, i.e. in-distribution data (ID). Most OOD works focus on the classification
Externí odkaz:
http://arxiv.org/abs/2310.01942