Cart
Create Account
Sign In
Showing 1451 - 1500 of 1951
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Talker-Independent Speaker Separation In Reverberant Conditions
Speaker separation refers to the task of separating a mixture signal comprising two or more speakers. Impressive advances have been made recently in deep learning based talker-independent speaker separation. But such advances are achieved in anechoic cond
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Robust And Computationally-Efficient Anomaly Detection Using Powers-Of-Two Networks
Robust and computationally efficient anomaly detection in videos is a problem in video surveillance systems. We propose a technique to increase robustness and reduce computational complexity in a Convolutional Neural Network (CNN) based anomaly detector t
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
A Dataset For Measuring Reading Levels In India At Scale
One out of four children in India are leaving grade eight without basic reading skills. Measuring the reading levels in a vast country like India poses significant hurdles. Recent advances in machine learning opens up the possibility of automating this ta
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Recent studies have highlighted adversarial examples as ubiquitous threats to the deep neural network (DNN) based speech recognition systems. In this work, we present a U-Net based attention model, U-Net$_{At}$, to enhance adversarial speech signals. Spec
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Anomaly Detection With Training Data In Hyperspectral Imagery
In this paper, we investigate the anomaly detection problem for multi-pixel targets in hyperspectral imagery when training data are available. We derive the generalized likelihood ratio test and obtain its analytical expressions of the probability of fals
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Classifying Anomalies For Network Security
Detecting and classifying anomalous behaviors in computer networks remains a formidable challenge. This work outlines a machine learning technique that uses deep neural networks to detect and classify a variety of network attacks. Our approach is based on
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Resilient To Byzantine Attacks Finite-Sum Optimization Over Networks
This contribution deals with distributed finite-sum optimization for learning over networks in the presence of malicious Byzantine attacks. To cope with such attacks, resilient approaches so far combine stochastic gradient descent (SGD) with different rob
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
A Comparative Study Of Western And Chinese Classical Music Based On Soundscape Models
Whether literally or suggestively, the concept of soundscape is alluded in both modern and ancient music. In this study, we examine whether we can analyze and compare Western and Chinese classical music based on soundscape models. We addressed this questi
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Pitch Estimation Via Self-Supervision
We present a method to estimate the fundamental frequency in monophonic audio, often referred to as pitch estimation. In contrast to existing methods, our neural network can be fully trained only on unlabeled data, using self-supervision. A tiny amount of
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Load Management With Predictions Of Solar Energy Production For Cloud Data Centers
Power supply of big infrastructures is today a tremendous operational cost for providers and the expected growth of Internet traffic and services will lead to a further expansion of the computing and networking infrastructures and this, in its turn, raise
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Enhanced Method Of Audio Coding Using Cnn-Based Spectral Recovery With Adaptive Structure
A process of spectral recovery can enhance the performance of transform-based audio coding by transmitting only a portion of spectral data and recovering the missing spectral data in the decoder. This study proposes an enhanced method of audio coding base
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Urtis: A Small 3D Imaging Sonar Sensor For Robotic Applications
State-of-the-art autonomous vehicles mainly rely on optical sensors to perceive their environment. However, the performance of these sensors worsens dramatically in environments where airborne particles are present. Sonar sensors rely on acoustic waves wh
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Near Capacity Rcqd Constellations For Papr Reduction Of Ofdm Systems
We investigate an optimized blind SeLected Mapping (SLM) algorithm to reduce the Peak-to-Average Power Ratio (PAPR) for Orthogonal Frequency Division Multiplexing (OFDM) systems with Signal Space Diversity (SSD). Several phase sequences based on two Rotat
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
A Semi-Supervised Rank Tracking Algorithm For On-Line Unmixing Of Hyperspectral Images
This paper addresses the problem of rank tracking in real time hyperspectral image unmixing methods. Based on the On-line Alternating Direction Method of Multipliers (ADMM), we propose a new hyperspectral unmixing approach that integrates prior informatio
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Compressive Adaptive Bilateral Filtering
We propose a fast algorithm for an adaptive variant of the classical bilateral filter, where the range kernel is allowed to vary from pixel to pixel. Several fast and accurate algorithms have been proposed for bilateral filtering, but they assume that the
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Clock Synchronization Over Networks Using Sawtooth Models
Clock synchronization and ranging over a wireless network with low communication overhead is a challenging goal with tremendous impact. In this paper, we study the use of time-to-digital converters in wireless sensors, which provides clock synchronization
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Generating Empathetic Responses By Looking Ahead The User’S Sentiment
An important aspect of human conversation difficult for machines is conversing with empathy, which is to understand the user's emotion and respond appropriately. Recent neural conversation models that attempted to generate empathetic responses either focu
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Robust Pricing Mechanism For Resource Sustainability Under Privacy Constraint In Competitive Online Learning Multi-Agent Systems
We consider the problem of resource congestion control for competing online learning agents under privacy and security constraints. Based on the non-cooperative game as the model for agents' interaction and the noisy online mirror ascent as the model for
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Time Reversal Based Robust Gesture Recognition Using Wifi
Gesture recognition using wireless sensing opened a plethora of applications in the field of human-computer interaction. However, most existing works are not robust without requiring wearables or tedious training/calibration. In this work, we propose WiGR
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Improving Prosody With Linguistic And Bert Derived Features In Multi-Speaker Based Mandarin Chinese Neural Tts
Recent advances of neural TTS have made ?human parity? synthesized speech possible when a large amount of studio-quality training data from a voice talent is available. However, with only limited, casual recordings from an ordinary speaker, human-like TTS
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
On Regularization Parameter For L0-Sparse Covariance Fitting Based Doa Estimation
In sparse DOA estimation methods, the regularization parameter is generally empirically tuned. In this paper, we provide a statistical method allowing to estimate an admissible interval where it must be chosen. This work is conducted in the case of an Uni
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Optimal Transport Based Change Point Detection And Time Series Segment Clustering
Two common problems in time series analysis are the decomposition of the data stream into disjoint segments, each of which is in some sense ?homogeneous? - a problem that is also referred to as Change Point Detection (CPD) - and the grouping of similar no
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Using Intelligent Reflecting Surfaces For Rank Improvement In Mimo Communications
An intelligent reflecting surface (IRS), consisting of reconfigurable metamaterials, can be used to partially control the radio environment and thereby bring new features to wireless communications. Previous works on IRS have particularly studied the rang
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Retinal Vessel Segmentation Via A Semantics And Multi-Scale Aggregation Network
Precise segmentation of retinal vessels is crucial for a computer-aided diagnosis system of retinal fundus images. However, this task remains challenging due to large variations in scales and poor segmentation of capillary vessels. In this paper, we propo
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Constrained Spectral Clustering For Dynamic Community Detection
Networks are useful representations of many systems with interacting entities, such as social, biological and physical systems. Characterizing the meso-scale organization, i.e. the community structure, is an important problem in network science. Community
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Sound Texture Synthesis Using Ri Spectrograms
This article introduces a new parametric synthesis method for sound textures based on existing works in visual and sound texture synthesis. Starting from a base sound signal, an optimization process is performed until the cross-correlations between the fe
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Fully Pipelined Iteration Unrolled Decoders The Road To Tb/S Turbo Decoding
Turbo codes are a well-known code class used for example in the LTE mobile communications standard. They provide built-in rate flexibility and a low-complexity and fast encoding. However, the serial nature of their decoding algorithm makes high-throughput
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Learning To Detect Keyword Parts And Whole By Smoothed Max Pooling
We propose smoothed max pooling loss and its application to keyword spotting systems. The proposed approach jointly trains an encoder (to detect keyword parts) and a decoder (to detect whole keyword) in a semi-supervised manner. The proposed new loss func
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Joint Coding And Modulation In The Ultra-Short Blocklength Regime For Bernoulli-Gaussian Impulsive Noise Channels Using Autoencoders
This paper develops a joint coding and modulation scheme for end-to-end communication system design using an autoencoder architecture in the ultra-short blocklength regime. Unlike the classical approach of separately designing error correction codes and m
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Leveraging Unpaired Text Data For Training End-To-End Speech-To-Intent Systems
Training an end-to-end (E2E) neural network speech-to-intent (S2I) system that directly extracts intents from speech requires large amounts of intent-labeled speech data, which is time consuming and expensive to collect. Initializing the S2I model with an
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Active Learning With Unsupervised Ensembles Of Classifiers
The present work introduces a simple scheme for active classification of data using unsupervised ensembles of classifiers. Uncertainty sampling, with different uncertainty measures, is evaluated for data selection, while an online expectation maximization
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Maximum Likelihood Multi-Speaker Direction Of Arrival Estimation Utilizing A Weighted Histogram
In this contribution, a novel maximum likelihood (ML) based direction of arrival (DOA) estimator for concurrent speakers in a noisy reverberant environment is presented. The DOA estimation task is formulated in the short-time Fourier transform (STFT) in t
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Optimal Joint Channel Estimation And Data Detection By L1-Norm Pca For Streetscape Iot
We prove, for the first time in the literature of communication theory and machine learning, the equivalence of joint maximum-likelihood (ML) optimal channel estimation and data detection (JOCEDD) to the problem of finding the $L_1$-norm principal compone
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Quickest Detection Of Growing Dynamic Anomalies In Networks
The problem of quickest growing dynamic anomaly detection in sensor networks is studied. Initially, the observations at the sensors, which are sampled sequentially by the decision maker, are generated according to a pre-change distribution. At some unknow
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Mt-Gcn For Multi-Label Audio Tagging With Noisy Labels
Multi-label audio tagging is the task of predicting the types of sounds occurring in an audio clip. Recently, large-scale audio datasets such as Google's AudioSet, have allowed researchers to use deep learning techniques for this task but this comes at th
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Small-Footprint Keyword Spotting On Raw Audio Data With Sinc-Convolutions
Keyword Spotting (KWS) enables speech-based user interaction on smart devices. Always-on and battery-powered application scenarios for smart devices put constraints on hardware resources and power consumption, while also demanding high accuracy as well as
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Far-Field Location Guided Target Speech Extraction Using End-To-End Speech Recognition Objectives
Target speech extraction is a specific case of source separation where an auxiliary information like the location or some pre-saved anchor speech examples of the target speaker is used to resolve the permutation ambiguity. Traditionally such systems are o
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
A Single-Rf Architecture For Multiuser Massive Mimo Via Reflecting Surfaces
In this work, we propose a new single-RF MIMO architecture which enjoys high scalability and energy-efficiency. The transmitter in this proposal consists of a single RF illuminator radiating towards a reflecting surface. Each element on the reflecting sur
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Speech-To-Singing Conversion In An Encoder-Decoder Framework
In this paper our goal is to convert a set of spoken lines into sung ones. Unlike previous signal processing based methods, we take a learning based approach to the problem. This allows us to automatically model various aspects of this transformation, thu
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Sparse Low-Redundancy Linear Array With Uniform Sum Co-Array
Sparse arrays can resolve vastly more scatterers than the number of sensors, in tasks such as coherent source localization. This entails significant cost reductions compared to conventional arrays with uniformly spaced elements. In this paper, we introduc
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Sdtcn: Similarity Driven Transmission Computing Network For Image Dehazing
Transmission similarity is an important feature which can greatly increase the capability of convolutional neural network (CNN) to fit transmission map. However, it is not sufficiently utilized in existing algorithms. In this paper, we propose a novel lig
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
One-Bit Compressed Sensing Using Generative Models
In this paper, we address the classical problem of one-bit compressed sensing. We present a deep learning based reconstruction algorithm that relies on a generative model. The generator which is a neural network, learns a mapping from a low dimensional sp
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Two-Element Biomimetic Antenna Array Design And Performance
Arrays of closely-spaced antennas with mutual coupling have been considered recently with analogies to the hearing mechanism in small insects that exhibit excellent direction finding capabilities. We develop a model for a two-element array system that inc
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Adaptive Region Aggregation Network: Unsupervised Domain Adaptation With Adversarial Training For Ecg Delineation
Electrocardiogram (ECG) delineation, which provides clinically useful information for the diagnosis of cardiovascular disease, is an essential task in automated ECG analysis. The discrepancies among ECG signals from different datasets, namely domain shift
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Multi-Microphone Complex Spectral Mapping For Speech Dereverberation
This study proposes a multi-microphone complex spectral mapping approach for speech dereverberation on a fixed array geometry. In the proposed approach, a deep neural network (DNN) is trained to predict the real and imaginary (RI) components of direct sou
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Mmse-Based Channel Estimation For Hybrid Beamforming Massive Mimo With Correlated Channels
In this paper, we study the channel estimation problem in microwave correlated massive multiple-input-multiple-output systems with reduced number of radio-frequency chains. We exploit the knowledge of the transmit and receive correlation between the anten
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Matching Pursuit Based Dynamic Phase-Amplitude Coupling Measure
Long-distance neuronal communication in the brain is enabled by the interactions across various oscillatory frequencies. One interaction that is gaining importance during cognitive brain functions is phase amplitude coupling (PAC), where the phase of a sl
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Improving Convergent Cross Mapping For Causal Discovery With Gaussian Processes
Convergent cross mapping (CCM) is designed for causal discovery between coupled time series for which Granger's method for detecting causality is shown to be unreliable. The theoretical foundation of CCM is based on state space reconstruction, and therefo