We define and study error detection and correction tasks that are useful for 3D reconstruction of neurons from electron microscopic imagery, and for image segmentation more generally. Both tasks take as input the raw image and a binary mask representing a candidate object. For the error detection task, the desired output is a map of split and merge errors in the object. For the error correction...

Despite considerable effort, monaural (single-microphone) algorithms capable of increasing the intelligibility of speech in noise have remained elusive. Successful development of such an algorithm is especially important for hearing-impaired (HI) listeners, given their particular difficulty in noisy backgrounds. In the current study, an algorithm based on binary masking was developed to separat...

In this paper, we propose a mask estimation method for a computational auditory scene analysis (CASA) based speech recognition front-end using speech obtained from two microphones. The proposed mask estimation method incorporates the observation that the mask information should be correlated over contiguous analysis time frames and adjacent frequency channels. To this end, two different hidden ...

In order to simplify the optical setup and the encryption process, a diffractive-imaging-based optical encryption system using a single diffraction pattern is proposed. A predesigned binary mask is placed before the plaintext in the encryption process, and three randomly distributed phase only masks are placed in the optical path. Only one diffraction pattern needs to be recorded as ciphertext ...

A new two-stage blind source separation (BSS) for convolutive mixtures of speech is proposed, in which a Single-Input MultipleOutput (SIMO)-model-based ICA and binary mask processing are combined. SIMO-model-based ICA can separate the mixed signals, not into monaural source signals but into SIMO-model-based signals from independent sources as they are at the microphones. Thus, the separated sig...

The thin ideal has been identified as playing a central role in female body dissatisfaction. However, research into idealization of thinness in young women tends to focus on quantitative measures that can mask the complexity of attitudes and experiences. This article describes a series of focus groups with 41 females aged 16-26 and explores the multifaceted relationship young women have with th...

This paper describes comparison and analysis of state-of-theart lossless image compression algorithms for light field mask data that are very useful in transmitting and refocusing the light field images. Recently, light field cameras have received wide attention in that they provide 3D information. Also, there has been a wide interest in studying the light field data compression due to a huge l...

In this paper, several binary mask based Depth From Defocus (DFD) algorithms are proposed to improve autofocusing performance and robustness. A binary mask is defined by thresholding image Laplacian to remove unreliable points with low Signal-to-Noise Ratio (SNR). Three different DFD schemes-with/without spatial integration and with/without squaring-are investigated and evaluated, both through ...

This paper proposes an end-to-end deep hashing framework with category mask for fast video retrieval. We train our network in a supervised way by fully exploiting interclass diversity and intra-class identity. Classification loss is optimized to maximize inter-class diversity, while intra-pair is introduced to learn representative intra-class identity. We investigate the binary bits distributio...

We propose a single-beam generation scheme to obtain a bottle-hollow (BH) beam using a binary phase mask and a focusing lens. The resulting BH beam is shown to possess an open bottle-shaped null intensity region, which has two hollow tube-shaped null intensity regions located on two opposite sides of this bottle. It is found that this scheme works identically under incident illumination with ra...