相关论文: A machine learning approach to estimate mid-infrar…

The MIRI Si:As IBC detector arrays extend the heritage technology from the Spitzer IRAC arrays to a 1024 x 1024 pixel format. We provide a short discussion of the principles of operation, design, and performance of the individual MIRI…

Perfect alignment in chosen beam sectors at both transmit- and receive-nodes is required for beamforming in mmWave bands. Current 802.11ad WiFi and emerging 5G cellular standards spend up to several milliseconds exploring different sector…

MUSE, a 2nd generation VLT instrument, will become the world's largest integral field spectrograph. It will be an AO assisted instrument which, in a single exposure, covers the wavelength range from 465 to 930 nm with an average resolution…

In wireless communication systems, the use of multiple antennas at both the transmitter and receiver is a widely known method for improving both reliability and data rates, as it increases the former through transmit or receive diversity…

Analyzing high resolution whole slide images (WSIs) with regard to information across multiple scales poses a significant challenge in digital pathology. Multi-instance learning (MIL) is a common solution for working with high resolution…

This paper examines, compares and plots optical, near- and mid-infrared (MIR) photometric data for 605 planetary nebulae (PNe) in the Large Magellanic Cloud (LMC). With the aid of multi-wavelength surveys such as the Spitzer legacy…

We present a mid-infrared analysis of 35 quasars with spectroscopic redshifts selected from the Spitzer Wide-area InfraRed Extragalactic Survey (SWIRE). We discuss their optical and mid-infrared (MIR) colors, and show that these quasars…

With the launch of the {\em Wide-field Infrared Survey Explorer} ({\em WISE}), a new era of detecting planetary debris and brown dwarfs around white dwarfs (WDs) has begun with the {\em WISE} InfraRed Excesses around Degenerates (WIRED)…

Transfer learning from large-scale pre-trained models has become essential for many computer vision tasks. Recent studies have shown that datasets like ImageNet are weakly labeled since images with multiple object classes present are…

This study presents a novel machine learning-based (ML) framework that utilizes the ConvLSTM-1D model to hindcast or forecast wave heights at coastal locations using a nonuniform array of wind observations. This approach was applied to Lake…

In this paper, we consider the channel estimation problem in Millimeter wave (mmWave) wireless systems with large antenna arrays. By exploiting the inherent sparse nature of the mmWave channel, we develop a novel rate-adaptive channel…

We describe the data reduction algorithms for the Multiband Imaging Photometer for Spitzer (MIPS) instrument. These algorithms were based on extensive preflight testing and modeling of the Si:As (24 micron) and Ge:Ga (70 and 160 micron)…

We present a semi-amortized variational inference framework designed for computationally feasible uncertainty quantification in 2D full-waveform inversion to explore the multimodal posterior distribution without dimensionality reduction.…

Shortwave-infrared(SWIR) spectral information, ranging from 1 {\mu}m to 2.5{\mu}m, overcomes the limitations of traditional color cameras in acquiring scene information. However, conventional SWIR hyperspectral imaging systems face…

The Medium-Resolution Spectrometer (MRS) provides one of the four operating modes of the Mid-Infrared Instrument (MIRI) on board the James Webb Space Telescope (JWST). The MRS is an integral field spectrometer, measuring the spatial and…

The unsupervised 3D object detection is to accurately detect objects in unstructured environments with no explicit supervisory signals. This task, given sparse LiDAR point clouds, often results in compromised performance for detecting…

Efficient inference for wide output layers (WOLs) is an essential yet challenging task in large scale machine learning. Most approaches reduce this problem to approximate maximum inner product search (MIPS), which relies heavily on the…

Inverse medium scattering is an ill-posed, nonlinear wave-based imaging problem arising in medical imaging, remote sensing, and non-destructive testing. Machine learning (ML) methods offer increased inference speed and flexibility in…

We use a dense, complete redshift survey, the Smithsonian Hectospec Lensing Survey (SHELS), covering a 4 square degree region of a deep imaging survey, the Deep Lens Survey (DLS), to study the optical spectral properties of Wide-field…

Climate change poses an extreme threat to biodiversity, making it imperative to efficiently model the geographical range of different species. The availability of large-scale remote sensing images and environmental data has facilitated the…