62 research outputs found
Advanced DSP Techniques for High-Capacity and Energy-Efficient Optical Fiber Communications
The rapid proliferation of the Internet has been driving communication networks closer and closer to their limits, while available bandwidth is disappearing due to an ever-increasing network load. Over the past decade, optical fiber communication technology has increased per fiber data rate from 10 Tb/s to exceeding 10 Pb/s. The major explosion came after the maturity of coherent detection and advanced digital signal processing (DSP). DSP has played a critical role in accommodating channel impairments mitigation, enabling advanced modulation formats for spectral efficiency transmission and realizing flexible bandwidth. This book aims to explore novel, advanced DSP techniques to enable multi-Tb/s/channel optical transmission to address pressing bandwidth and power-efficiency demands. It provides state-of-the-art advances and future perspectives of DSP as well
Make the U in UDA Matter: Invariant Consistency Learning for Unsupervised Domain Adaptation
Domain Adaptation (DA) is always challenged by the spurious correlation
between domain-invariant features (e.g., class identity) and domain-specific
features (e.g., environment) that does not generalize to the target domain.
Unfortunately, even enriched with additional unsupervised target domains,
existing Unsupervised DA (UDA) methods still suffer from it. This is because
the source domain supervision only considers the target domain samples as
auxiliary data (e.g., by pseudo-labeling), yet the inherent distribution in the
target domain -- where the valuable de-correlation clues hide -- is
disregarded. We propose to make the U in UDA matter by giving equal status to
the two domains. Specifically, we learn an invariant classifier whose
prediction is simultaneously consistent with the labels in the source domain
and clusters in the target domain, hence the spurious correlation inconsistent
in the target domain is removed. We dub our approach "Invariant CONsistency
learning" (ICON). Extensive experiments show that ICON achieves the
state-of-the-art performance on the classic UDA benchmarks: Office-Home and
VisDA-2017, and outperforms all the conventional methods on the challenging
WILDS 2.0 benchmark. Codes are in https://github.com/yue-zhongqi/ICON.Comment: Accepted by NeurIPS 202
Interventional few-shot learning
Ministry of Education, Singapore under its Academic Research Funding Tier 1 and 2; Alibaba Innovative Research (AIR) programm
Novel Insights into Orbital Angular Momentum Beams: From Fundamentals, Devices to Applications
It is well-known by now that the angular momentum carried by elementary particles can be categorized as spin angular momentum (SAM) and orbital angular momentum (OAM). In the early 1900s, Poynting recognized that a particle, such as a photon, can carry SAM, which has only two possible states, i.e., clockwise and anticlockwise circular polarization states. However, only fairly recently, in 1992, Allen et al. discovered that photons with helical phase fronts can carry OAM, which has infinite orthogonal states. In the past two decades, the OAM-carrying beam, due to its unique features, has gained increasing interest from many different research communities, including physics, chemistry, and engineering. Its twisted phase front and intensity distribution have enabled a variety of applications, such as micromanipulation, laser beam machining, nonlinear matter interactions, imaging, sensing, quantum cryptography and classical communications. This book aims to explore novel insights of OAM beams. It focuses on state-of-the-art advances in fundamental theories, devices and applications, as well as future perspectives of OAM beams
Invariant Feature Regularization for Fair Face Recognition
Fair face recognition is all about learning invariant feature that
generalizes to unseen faces in any demographic group. Unfortunately, face
datasets inevitably capture the imbalanced demographic attributes that are
ubiquitous in real-world observations, and the model learns biased feature that
generalizes poorly in the minority group. We point out that the bias arises due
to the confounding demographic attributes, which mislead the model to capture
the spurious demographic-specific feature. The confounding effect can only be
removed by causal intervention, which requires the confounder annotations.
However, such annotations can be prohibitively expensive due to the diversity
of the demographic attributes. To tackle this, we propose to generate diverse
data partitions iteratively in an unsupervised fashion. Each data partition
acts as a self-annotated confounder, enabling our Invariant Feature
Regularization (INV-REG) to deconfound. INV-REG is orthogonal to existing
methods, and combining INV-REG with two strong baselines (Arcface and CIFP)
leads to new state-of-the-art that improves face recognition on a variety of
demographic groups. Code is available at
https://github.com/PanasonicConnect/InvReg.Comment: Accepted by International Conference on Computer Vision (ICCV) 202
Exogenous brassinosteroids alleviate calcium deficiency-induced tip-burn by maintaining cell wall structural stability and higher photosynthesis in mini Chinese Cabbage
Tip-burn has seriously affected the yield, quality and commodity value of mini Chinese cabbage. Calcium (Ca2+) deficiency is the main cause of tip-burn. In order to investigate whether exogenous brassinosteroids (BRs) can alleviate tip-burn induced by calcium (Ca2+) deficiency and its mechanism, in this study, Ca2+ deficiency in nutrient solution was used to induced tip-burn, and then distilled water and BRs were sprayed on leaves to observe the tip-burn incidence of mini Chinese cabbage. The tip-burn incidence and disease index, leaf area, fluorescence parameters (Fv/Fm, NPQ, qP andφPSII) and gas exchange parameters (Tr, Pn, Gs and Ci), pigment contents, cell wall components, mesophyll cell ultrastructure and the expression of genes related to chlorophyll degradation were measured. The results showed that exogenous BRs reduced the tip-burn incidence rate and disease index of mini Chinese cabbage, and the tip-burn incidence rate reached the highest on the ninth day after treatment. Exogenous BRs increased the contents of cellulose, hemifiber, water-soluble pectin in Ca2+ deficiency treated leaves, maintaining the stability of cell wall structure. In addition, BRs increased photosynthetic rate by increasing the activities of Ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco) and fructose 1,6-bisphosphatase (FBPase) related to Calvin cycle, maintaining relatively complete chloroplast structure and higher chlorophyll content via down-regulating the expression of BrPPH1 and BrPAO1 genes related to chlorophyll degradation. In conclusion, exogenous BRs alleviated calcium deficiency-induced tip-burn by maintaining cell wall structural stability and higher photosynthesis
Action recognition using machine learning techniques for robots
Recent advancement in the processing capabilities of mobile chips has opened up the
possibility of developing domestic companion robots with small form factors. The most
intuitive way to interact with such robot is through human action, especially hand
gesture. In this project, a robust static and dynamic gesture detector is built to achieve
real-time performance on a mobile processor. The proposed framework features a novel
hand hypotheses generator based on color and edge, a hand detector using Convolutional
Neural Network (CNN), a static gesture recognizer based on skin contour analysis, and a
hypotheses-tracking system based on Kalman Filter for increased performance and
consistency. The resulting system is robust to viewpoint, ambient lighting, and rotation,
capable of producing accurate results in various real-life settings.
Index Terms: Hand Gesture Recognition, Hand Detection, Hand Tracking,
Convolutional Neural NetworkBachelor of Engineerin
Eccentric settlements of a rigid foundation on a consolidating layer
The paper examines the eccentric settlement of a rigid foundation located at the surface of a poroelastic layer saturated with a compressible pore fluid. The base of the rigid foundation is circular and flat. The poroelastic layer rests in bonded contact with an impermeable, rigid subbase and the surface of the layer is considered to be either permeable or impermeable. The paper develops the integral equations governing the eccentric settlement of the rigid foundation associated with the consolidation process of the saturated poroelastic layer. The numerical results presented in the paper illustrate the time-dependent behavior of the rigid foundation by taking into account the effects of the relative layer thickness, eccentricity, drainage conditions, and the compressibility of the pore fluid.link_to_subscribed_fulltex
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