Seminar

Meeting ID: 972 6774 1607 Abstract: The robotics industry has manufactured multiple successful robots that are deployed in various domains and have been playing a significant role in the modern economy. […]

Meeting ID: 957 7820 8166 Password: 631839 Speaker: Mr. Weibin KOU Department of Electrical and Electronic Engineering, The University of Hong Kong Abstract: In this seminar, I will present the […]

Abstract: Enormous amounts of data are generated by billions of edge devices in mobile networks. Distributed data analytics can support a broad range of mobile applications, from edge AI to […]

Abstract: Although considerable progress has been obtained in neural network quantization for efficient inference, existing methods are not scalable to heterogeneous devices as one dedicated model needs to be trained, […]

Meeting ID: 958 6149 4641 Password: 505358 Abstract: Recent advances in medical image segmentation models combine convolution with the attention mechanism which provides an effective approach to formulate long-term dependencies. […]

Meeting ID: 990 0206 5927 Password: 585304 Abstract: The instrumental variable pseudolinear Kalman filter (IV-PLKF) algorithm, used for 3D angle-of-arrival (AOA) target tracking, has been proven to be more robust […]

Abstract Manual annotation of 3D point clouds is notoriously labor-intensive, prompting the need for automated solutions. Existing automated annotation methods, however, are typically complex and may neglect the crucial inter-object […]

Meeting ID: 892 6022 4678 Password: n9QxYg Abstract In recent years, attention-based models, particularly those employing the transformer structure, have exhibited exceptional performance in tasks such as natural language processing, […]

Abstract Recently deep learning methods have gained groundbreaking success in many areas, including autonomous driving and 3D object detection. Powerful neural networks are proposed and yield human-comparable ability after being […]

Abstract Combinatorial optimization problems are prevalent in various fields, but obtaining exact solutions remains challenging due to the combinatorial explosion with increasing problem size. Special-purpose hardware such as Ising machines, […]

Microneedles (MNs) are an emerging platform for transdermal applications including drug delivery, insulin delivery, vaccination, biosensing, disease diagnosis, and cosmeceutical industry. Their advantages lie in their easy-to-use, pain-free, minimally invasive, […]

Abstract AI models significantly impact our daily lives, but their high performance brings the challenge of model complexity. Deploying these models on edge devices poses additional challenges, including power consumption, […]

Abstract The past decade of escalated development in deep learning (DL) has achieved unprecedented success in engineering fields. In particular, deep neural networks (DNNs) via deep learning have achieved remarkable […]

Abstract Light scattering is a fundamental optical process that accounts for many optical phenomena and applications. This process comes from the interaction between light and scattering particles, or scatters. It […]

Abstract In the past decades, with the rapidly increasing data, AI technology, including neural network (NN) shows more and more powerful ability. However, the development of electronic hardware meets a […]

Abstract: Blood analysis is an indispensable clinical tool for human health and diseases. Specifically, the overarching challenge in characterization of blood, notably immune cells, is to identify the cellular phenotypes […]

Abstract: Financial portfolio management (PM) is a very important topic in computational finance, with its primary objective of achieving higher returns while reducing investment risks through dynamically allocating capital to […]

Abstract Layered two-dimensional (2D) materials interact primarily via van der Waals bonding, which has created new opportunities for heterostructures that are not constrained by epitaxial lattice matching requirements. However, since […]

Abstract Despite the long and crucial role of traditional solid-state physics for current silicon-based technologies, next-generation neuromorphic, non-volatile memory, and energy devices that are key components in the era of […]

Abstract The need to shuttle data between processing and memory units has been a key performance bottleneck for conventional hardware implementations of artificial neural networks. Analog in-memory computing (AIMC) emerges […]