arXiv subjects

Qi Yao

Publications and source records attributed to Qi Yao.

At least 37 records · Page 2Linked to original sources

arXiv2023

Weakly Supervised Detection of Baby Cry

Detection of baby cries is an important part of baby monitoring and health care. Almost all existing methods use supervised SVM, CNN, or their varieties. In this work, we propose to use weakly supervised anomaly detection to detect a baby cry. In this weak supervision, we only need weak annotation if there is a cry in an audio file. We design a data mining technique using the pre-trained VGGish feature extractor and an anomaly detection network on long untrimmed audio files. The obtained datasets are used to train a simple CNN feature network for cry/non-cry classification. This CNN is then used as a feature extractor in an anomaly detection framework to achieve better cry detection performance.

cs.CV↗

arXiv2023

Interplay between moment-dependent and field-driven unidirectional magnetoresistance in CoFeB/InSb/CdTe heterostructures

Magnetoresistance effects are crucial for understanding the charge/spin transport as well as propelling the advancement of spintronic applications. Here we report the coexistence of magnetic moment-dependent (MD) and magnetic field-driven (FD) unidirectional magnetoresistance (UMR) effects in CoFeB/InSb/CdTe heterostructures. The strong spin-orbital coupling of InSb and the matched impedance at the CoFeB/InSb interface warrant a distinct MD-UMR effect at room temperature, while the interaction between the in-plane magnetic field and the Rashba effect at the InSb/CdTe interface induces the marked FD-UMR signal that dominates the high-field region. Moreover, owning to the different spin transport mechanisms, these two types of nonreciprocal charge transport show opposite polarities with respect to the magnetic field direction, which further enable an effective phase modulation of the angular-dependent magnetoresistance. Besides, the demonstrations of both the tunable UMR response and two-terminal spin-orbit torque-driven magnetization switching validate our CoFeB/InSb/CdTe system as a suitable integrated building block for multifunctional spintronic device design.

physics.app-ph↗

arXiv2023

Controlling Character Motions without Observable Driving Source

How to generate diverse, life-like, and unlimited long head/body sequences without any driving source? We argue that this under-investigated research problem is non-trivial at all, and has unique technical challenges behind it. Without semantic constraints from the driving sources, using the standard autoregressive model to generate infinitely long sequences would easily result in 1) out-of-distribution (OOD) issue due to the accumulated error, 2) insufficient diversity to produce natural and life-like motion sequences and 3) undesired periodic patterns along the time. To tackle the above challenges, we propose a systematic framework that marries the benefits of VQ-VAE and a novel token-level control policy trained with reinforcement learning using carefully designed reward functions. A high-level prior model can be easily injected on top to generate unlimited long and diverse sequences. Although we focus on no driving sources now, our framework can be generalized for controlled synthesis with explicit driving sources. Through comprehensive evaluations, we conclude that our proposed framework can address all the above-mentioned challenges and outperform other strong baselines very significantly.

cs.AI↗

arXiv2023

Integrated Artificial Neural Network with Trainable Activation Function Enabled by Topological Insulator-based Spin-Orbit Torque Devices

Non-volatile memristors offer a salient platform for artificial neural network (ANN), but the integration of different function blocks into one hardware system remains challenging. Here we demonstrate the implementation of brain-like synaptic (SOT-S) and neuronal (SOT-N) functions in the Bi2Te3/CrTe2 heterostructure-based spin-orbit torque (SOT) device. The SOT-S unit exhibits highly linear (linearity error < 4.19%) and symmetrical long-term potentiation/depression process, resulting in better performance compared to other memristor synapses. Meanwhile, the Sigmoid-shape transition curve inherited in the SOT-N cell replaces the software-based activation function block, hence reducing the system complexity. On this basis, we employ a serial-connected, voltage-mode sensing ANN architecture to enhance the vector-matrix multiplication signal strength with low reading error of 0.61%. Furthermore, the trainable activation function of SOT-N enables the integrated SOT-ANN to execute the Batch Normalization algorithm and activation operation within one clock cycle, which bring about improved on/off-chip training performance close to the ideal baseline.

cond-mat.mes-hall↗

arXiv2023

Overlooked Video Classification in Weakly Supervised Video Anomaly Detection

Current weakly supervised video anomaly detection algorithms mostly use multiple instance learning (MIL) or their varieties. Almost all recent approaches focus on how to select the correct snippets for training to improve the performance. They overlook or do not realize the power of video classification in boosting the performance of anomaly detection. In this paper, we study explicitly the power of video classification supervision using a BERT or LSTM. With this BERT or LSTM, CNN features of all snippets of a video can be aggregated into a single feature which can be used for video classification. This simple yet powerful video classification supervision, combined into the MIL framework, brings extraordinary performance improvement on all three major video anomaly detection datasets. Particularly it improves the mean average precision (mAP) on the XD-Violence from SOTA 78.84\% to new 82.10\%. The source code is available at https://github.com/wjtan99/BERT_Anomaly_Video_Classification.

cs.CV↗

arXiv2023

Record-high Mobility and Extreme Magnetoresistance on Kagome-lattice in Compensated Semimetal Ni3In2S2

The kagome-lattice crystal hosts various intriguing properties including the frustrated magnetism, charge order, topological state, superconductivity and correlated phenomena. To achieve high-performance kagome-lattice compounds for electronic and spintronic applications, careful tuning of the band structure would be desired. Here, the electronic structures of kagome-lattice crystal Ni3In2S2 were investigated by transport measurements, angle-resolved photoemission spectroscopy as well as ab initio calculations. The transport measurements reveal Ni3In2S2 as a compensated semimetal with record-high carrier mobility (~8683 cm2 V-1 S-1 and 7356 cm2 V-1 S-1 for holes and electrons) and extreme magnetoresistance (15518% at 2 K and 13 T) among kagome-lattice materials. These extraordinary properties are well explained by its band structure with indirect gap, small electron/hole pockets and large bandwidth of the 3d electrons of Ni on the kagome lattice. This work demonstrates that the crystal field and doping serve as the key tuning knobs to optimize the transport properties in kagome-lattice crystals. Our work provides material basis and optimization routes for kagome-lattice semimetals as electronics and spintronics applications.

cond-mat.mtrl-sci↗

arXiv2022

Level-spectra Statistics in Planar Fractal Tight-Binding Models

In this communication, we study the level-spectra statistics when a noninteracting electron gas is confined in \textit{Sierpiński Carpet} (\textit{SC}) lattices. These \textit{SC} lattices are constructed under two representative patterns of the $self$ and $gene$ patterns, and classified into two subclass lattices by the area-perimeter scaling law. By the singularly continuous spectra and critical traits using two level-statistic tools\iffalse the nearest spacing distribution and alternative gap-ratio distribution\fi, we ascertain that both obey the critical phase due to broken translation symmetry and the long-range order of scaling symmetry. The Wigner-like conjecture is confirmed numerically since both belong to the Gaussian orthogonal ensemble. An analogy was observed in a quasiperiodic lattice~\cite{Zhong1998Level}. In addition, this critical phase isolates the crucial behavior near the metal-insulator transition edge in Anderson model. The lattice topology of the self-similarity feature can induce level clustering behavior.

cond-mat.mes-hall↗

arXiv2022

Ballistic transport of a polariton ring condensate with spin precession

It is now routine to make Bose-Einstein condensates of polaritons with long enough lifetime and low enough disorder to travel ballistically for hundreds of microns in quasi-one-dimensional (1D) wires. We present observations of a polariton condensate injected at one point in a quasi-1D ring, with a well-defined initial velocity and direction. A clear precession of the circular polarization is seen, which arises from an effective spin-orbit coupling term in the Hamiltonian. Our theoretical model accurately predicts the experimentally observed behavior, and shows that "zitterbewegung" behavior plays a role in the motion of the polaritons.

cond-mat.quant-gas↗

arXiv2022

Wafer-scale epitaxial growth of the thickness-controllable van der Waals ferromagnet CrTe2 for reliable magnetic memory applications

To harness the intriguing properties of two-dimensional van der Waals (vdW) ferromagnets (FMs) for versatile applications, the key challenge lies in the reliable material synthesis for scalable device production. Here, we demonstrate the epitaxial growth of single-crystalline 1T-CrTe2 thin films on 2-inch sapphire substrates. Benefiting from the uniform surface energy of the dangling bond-free Al2O3(0001) surface, the layer-by-layer vdW growth mode is observed right from the initial growth stage, which warrants precise control of the sample thickness and atomically smooth surface morphology across the entire wafer. Moreover, the presence of the Coulomb interaction at the CrTe2/Al2O3 interface serves as an effective tuning parameter to tailor the anomalous Hall response, and the structural optimization of the CrTe2-based spin-orbit torque device leads to a substantial switching power reduction by 54%. Our results may lay out a general framework for the design of energy-efficient spintronics based on configurable vdW FMs.

cond-mat.mtrl-sci↗

arXiv2022

Two-Stage COVID19 Classification Using BERT Features

We propose an automatic COVID1-19 diagnosis framework from lung CT-scan slice images using double BERT feature extraction. In the first BERT feature extraction, A 3D-CNN is first used to extract CNN internal feature maps. Instead of using the global average pooling, a late BERT temporal pooing is used to aggregate the temporal information in these feature maps, followed by a classification layer. This 3D-CNN-BERT classification network is first trained on sampled fixed number of slice images from every original CT scan volume. In the second stage, the 3D-CNN-BERT embedding features are extracted on all slice images of every CT scan volume, and these features are averaged into a fixed number of segments. Then another BERT network is used to aggregate these multiple features into a single feature followed by another classification layer. The classification results of both stages are combined to generate final outputs. On the validation dataset, we achieve macro F1 score of 0.9164.

eess.IV↗

arXiv2022

Mass and Expansion of Asymptotically Conical Kähler Metrics

We prove an expansion theorem on scalar-flat asymptotically conical Kähler metrics. Consider an AC Kähler manifold with asymptotic to a Ricci-flat Kähler metric cone with complex dimension n. Assuming the weak decay conditions required for the mass to be well-defined, then each scalar-flat AC Kähler metric admits an expansion that the main term is given by the standard Kähler metric of the metric cone and the leading error term is of O(r^{2-2n}) with coefficient only depending on the ADM mass and its dimension. Besides, the mass formula by Hein-LeBrun also can be proved in our setting. As an application, a new version of the positive mass theorem will be discussed in the cases of the resolutions of the Ricci-flat Kähler cones.

math.DG↗

arXiv2022

Electronic properties and quantum transports in functionalized graphene Sierpinski carpet fractals

Recent progress in controllable functionalization of graphene surfaces enables the experimental realization of complex functionalized graphene nanostructures, such as Sierpinski carpet (SC) fractals. Herein, we model the SC fractals formed by hydrogen and fluorine functionalized patterns on graphene surfaces, namely, H-SC and F-SC, respectively. We then reveal their electronic properties and quantum transport features. From calculated results of the total and local density of state, we find that states in H-SC and F-SC have two characteristics: (i) low-energy states inside about |E/t|<1 (with t as the near-neighbor hopping) are localized inside free graphene regions due to the insulating properties of functionalized graphene regions, and (ii) high-energy states in F-SC have two special energy ranges including -2.3<E/t<-1.9 with localized holes only inside free graphene areas and 3<E/t<3.7 with localized electrons only inside fluorinated graphene areas. The two characteristics are further verified by the real-space distributions of normalized probability density. We analyze the fractal dimension of their quantum conductance spectra and find that conductance fluctuations in these structures follow the Hausdorff dimension. We calculate their optical conductivity and find that several additional conductivity peaks appear in high energy ranges due to the adsorbed H or F atoms.

cond-mat.mes-hall↗

arXiv2022

YOLO5Face: Why Reinventing a Face Detector

Tremendous progress has been made on face detection in recent years using convolutional neural networks. While many face detectors use designs designated for detecting faces, we treat face detection as a generic object detection task. We implement a face detector based on the YOLOv5 object detector and call it YOLO5Face. We make a few key modifications to the YOLOv5 and optimize it for face detection. These modifications include adding a five-point landmark regression head, using a stem block at the input of the backbone, using smaller-size kernels in the SPP, and adding a P6 output in the PAN block. We design detectors of different model sizes, from an extra-large model to achieve the best performance to a super small model for real-time detection on an embedded or mobile device. Experiment results on the WiderFace dataset show that on VGA images, our face detectors can achieve state-of-the-art performance in almost all the Easy, Medium, and Hard subsets, exceeding the more complex designated face detectors. The code is available at \url{https://github.com/deepcam-cn/yolov5-face}

cs.CV↗

arXiv2021

Tailoring Magnetic Exchange Interactions in Ferromagnet-Intercalated MnBi2Te4 Superlattices

The intrinsic magnetic topological insulator MnBi2Te4 (MBT) has provided a platform for the successful realization of exotic quantum phenomena. To broaden the horizons of MBT-based material systems, we intercalate ferromagnetic MnTe layers to construct the [(MBT)(MnTe)m]N superlattices by molecular beam epitaxy. The effective incorporation of ferromagnetic spacers mediates the anti-ferromagnetic interlayer coupling among the MBT layers through the exchange spring effect at the MBT/MnTe hetero-interfaces. Moreover, the precise control of the MnTe thickness enables the modulation of relative strengths among the constituent magnetic orders, leading to tunable magnetoelectric responses, while the superlattice periodicity serves as an additional tuning parameter to tailor the spin configurations of the synthesized multi-layers. Our results demonstrate the advantages of superlattice engineering for optimizing the magnetic interactions in MBT-family systems, and the ferromagnet-intercalated strategy opens up new avenues in magnetic topological insulator structural design and spintronic applications.

cond-mat.mtrl-sci↗

arXiv2021

Balanced Masked and Standard Face Recognition

We present the improved network architecture, data augmentation, and training strategies for the Webface track and Insightface/Glint360K track of the masked face recognition challenge of ICCV2021. One of the key goals is to have a balanced performance of masked and standard face recognition. In order to prevent the overfitting for the masked face recognition, we control the total number of masked faces by not more than 10\% of the total face recognition in the training dataset. We propose a few key changes to the face recognition network including a new stem unit, drop block, face detection and alignment using YOLO5Face, feature concatenation, a cycle cosine learning rate, etc. With this strategy, we achieve good and balanced performance for both masked and standard face recognition.

cs.CV↗

arXiv2021

A Dataset and System for Real-Time Gun Detection in Surveillance Video Using Deep Learning

Gun violence is a severe problem in the world, particularly in the United States. Deep learning methods have been studied to detect guns in surveillance video cameras or smart IP cameras and to send a real-time alert to security personals. One problem for the development of gun detection algorithms is the lack of large public datasets. In this work, we first publish a dataset with 51K annotated gun images for gun detection and other 51K cropped gun chip images for gun classification we collect from a few different sources. To our knowledge, this is the largest dataset for the study of gun detection. This dataset can be downloaded at www.linksprite.com/gun-detection-datasets. We present a gun detection system using a smart IP camera as an embedded edge device, and a cloud server as a manager for device, data, alert, and to further reduce the false positive rate. We study to find solutions for gun detection in an embedded device, and for gun classification on the edge device and the cloud server. This edge/cloud framework makes the deployment of gun detection in the real world possible.

cs.CV↗

arXiv2021

Thickness-Driven Quantum Anomalous Hall Phase Transition in Magnetic Topological Insulator Thin Films

The quantized version of anomalous Hall effect realized in magnetic topological insulators (MTIs) has great potential for the development of topological quantum physics and low-power electronic/spintronic applications. To enable dissipationless chiral edge conduction at zero magnetic field, effective exchange field arisen from the aligned magnetic dopants needs to be large enough to yield specific spin sub-band configurations. Here we report the thickness-tailored quantum anomalous Hall (QAH) effect in Cr-doped (Bi,Sb)2Te3 thin films by tuning the system across the two-dimensional (2D) limit. In addition to the Chern number-related metal-to-insulator QAH phase transition, we also demonstrate that the induced hybridization gap plays an indispensable role in determining the ground magnetic state of the MTIs, namely the spontaneous magnetization owning to considerable Van Vleck spin susceptibility guarantees the zero-field QAH state with unitary scaling law in thick samples, while the quantization of the Hall conductance can only be achieved with the assistance of external magnetic fields in ultra-thin films. The modulation of topology and magnetism through structural engineering may provide a useful guidance for the pursuit of QAH-based new phase diagrams and functionalities.

cond-mat.mes-hall↗

arXiv2021

Electron-plasmon interaction induced plasmonic-polaron band replication in epitaxial perovskite SrIrO$_3$ films

Electron-boson interaction is fundamental to a thorough understanding of various exotic properties emerging in many-body physics. In photoemission spectroscopy, photoelectron emission due to photon absorption would trigger diverse collective excitations in solids, including the emergence of phonons, magnons, electron-hole pairs, and plasmons, which naturally provides a reliable pathway to study electron-boson couplings. While fingerprints of electron-phonon/-magnon interactions in this state-of-the-art technique have been well investigated, much less is known about electron-plasmon coupling, and direct observation of the band renormalization solely due to electron-plasmon interactions is extremely challenging. Here by utilizing integrated oxide molecular-beam epitaxy and angle-resolved photoemission spectroscopy, we discover the long sought-after pure electron-plasmon coupling-induced low-lying plasmonic-polaron replica bands in epitaxial semimetallic SrIrO$_3$ films, in which the characteristic low carrier concentration and narrow bandwidth combine to provide a unique platform where the electron-plasmon interaction can be investigated kinematically in photoemission spectroscopy. This finding enriches the forms of electron band normalization on collective modes in solids and demonstrates that, to obtain a complete understanding of the quasiparticle dynamics in 5d electron systems, the electron-plasmon interaction should be considered on equal footing with the acknowledged electron-electron interaction and spin-orbit coupling.

cond-mat.str-el↗