Many studies on deep learning-based speech enhancement (SE) utilizing the computational auditory scene analysis method typically employs ideal binary mask or ratio to reconstruct enhanced signal. However, many SE applications in real scenarios demand a desirable balance between denoising capability and cost. In this study, first, an improvement over attain more superior performance is proposed ...

Inclusion of low-resolution data in macromolecular crystallography requires a model for the bulk solvent. Previous methods have used a binary mask to accomplish this, which has proven to be very effective, but the mask is discontinuous at the solute-solvent boundary (i.e. the mask value jumps from zero to one) and is not differentiable with respect to atomic parameters. Here, two algorithms are...

Context. We present the results of the first laboratory experiment of checkerboard shaped pupil binary mask coronagraphs using visible light, in the context of the R&D activities for future mid-infrared space missions such as the 3.5 m SPICA telescope. Aims. The primary aim of this work is to demonstrate the coronagraphic performance of checkerboard masks down to a 10 −6 peak-to-peak contrast, ...

Starting with values {f 0 j }j∈Z assigned to the integers, a binary subdivision scheme defines recursively values {fk j }j∈Z, respectively assigned to the binary points {2−kj}j∈Z. The purpose of subdivision analysis is to study the convergence of such processes and to establish the existence of a limit function on R and its smoothness class. A general treatment of uniform subdivision can be fou...

A pixel-wise accurate and interactive video segmentation technique is proposed in this paper to generate a binary mask of moving objects optimized for MPEG-4 object-based video coding. The initial object mask is tracked temporally, and three regions are classified as background region, object region, and uncertain region where the pixel is within a certain distance from the tracked object bound...

Speech separation is a well-known problem, especially when there only one sound mixture available. Estimating the Ideal Binary Mask (IBM) solution to this problem. Recent research has focused on supervised classification approach. The challenge of extracting features from sources critical for method. been accomplished by using variety feature extraction models. majority them, however, are conce...

Speech separation algorithms are faced with a difficult task of producing high degree of separation without containing unwanted artifacts. The time-frequency (T-F) masking technique applies a real-valued (or binary) mask on top of the signal’s spectrum to filter out unwanted components. The practical difficulty lies in the mask estimation. Often, using efficient masks engineered for separation ...

F w n [1], we presented simulations to illustrate the characeristics of the proposed binary mask optimization algoithm. However, an error was made in the aerial image alculation. In addition, the range of the point-spread unction was overly truncated. We would like to correct hese errors and modify the previous simulations in this rratum. The correct simulations are illustrated as folows. The d...

We present noise robust automatic speech recognition (ASR) using sparseness-based underdetermined blind source separation (BSS) technique. As a representative underdetermined BSS method, we utilized time-frequency masking in this paper. Although time-frequency masking is able to separate target speech from interferences effectively, one should consider two problems. One is that masking does not...

We address the problem of instance-level semantic segmentation, which aims at jointly detecting, segmenting and classifying every individual object in an image. In this context, existing methods typically propose candidate objects, usually as bounding boxes, and directly predict a binary mask within each such proposal. As a consequence, they cannot recover from errors in the object candidate ge...