Deep learning provides the opportunity to improve upon conflicting reports considering the relationship between the Amazon river's fish and dolphin abundance and reduced canopy cover as a result of deforestation. Current methods of fish and dolphin a...
Chromatic dispersion is a common problem to degrade the system resolution in optical coherence tomography (OCT). This study is to develop a deep learning network for automated dispersion compensation (ADC-Net) in OCT. The ADC-Net is based on a redesi...
The radio properties of hard (2-8keV) X-ray selected sources are explored by combining a single 50ks XMM-Newton pointing with the ultra-deep and homogeneous Phoenix radio (1.4GHz) survey (Hopkins et al. 2003). A total of 43 sources are detected abo...
Deep reinforcement learning (DRL) is capable of learning high-performing policies on a variety of complex high-dimensional tasks, ranging from video games to robotic manipulation. However, standard DRL methods often suffer from poor sample efficiency...
Skull stripping is usually the first step for most brain analysisprocess in magnetic resonance images. A lot of deep learn-ing neural network based methods have been developed toachieve higher accuracy. Since the 3D deep learning modelssuffer from hi...
In this paper, a deep neural network based ensemble method is experimented for automatic identification of skin disease from dermoscopic images. The developed algorithm is applied on the task3 of the ISIC 2018 challenge dataset (Skin Lesion Analysis...
I've been diving deeper and deeper into the golden path and it feels really special to have such design where the things are in your plain sight ALL the time but you just don't have the knowledge, I l...
We report on our ongoing project of finding Active Galactic Nuclei (AGN) that go into deep X-ray flux states detected by Swift. Swift is performing an extensive study on the flux and spectral variability of AGN using Guest Investigator and team fill-...
Lung cancer is the leading cause of cancer-related death worldwide, and early diagnosis is critical to improving patient outcomes. To diagnose cancer, a highly trained pulmonologist must navigate a flexible bronchoscope deep into the branched structu...
Lung cancer is the leading cause of cancer-related death worldwide, and early diagnosis is critical to improving patient outcomes. To diagnose cancer, a highly trained pulmonologist must navigate a flexible bronchoscope deep into the branched structu...
This paper presents the summary report on our DFGC 2022 competition. The DeepFake is rapidly evolving, and realistic face-swaps are becoming more deceptive and difficult to detect. On the contrary, methods for detecting DeepFakes are also improving....
The ratio of the nucleon $F_2$ structure functions, $F_2^n/F_2^p$, is determined by the MARATHON experiment from measurements of deep inelastic scattering of electrons from $^3$H and $^3$He nuclei. The experiment was performed in the Hall A Facility...
This paper introduces DeepParliament, a legal domain Benchmark Dataset that gathers bill documents and metadata and performs various bill status classification tasks. The proposed dataset text covers a broad range of bills from 1986 to the present an...
Survival risk stratification is an important step in clinical decision making for breast cancer management. We propose a novel deep learning approach for this purpose by integrating histopathological imaging, genetic and clinical data. It employs vis...
Logo detection from images has many applications, particularly for brand recognition and intellectual property protection. Most existing studies for logo recognition and detection are based on small-scale datasets which are not comprehensive enough w...
We present the main results from our 940 ksec observation of the Chandra Deep Field South (CDFS), using the source catalog described in an accompanying paper (Giacconi et al. 2001). We extend the measurement of source number counts to 5.5e-17 erg/c...
We present deep observations of the nearby T-type brown dwarf binary $ε$ Indi Bab in radio with the Australia Telescope Compact Array and in X-rays with the Chandra X-ray Observatory. Despite long integration times, the binary (composed of T1 and...
In the context of addressing the Robot Air Hockey Challenge 2023, we investigate the applicability of model-based deep reinforcement learning to acquire a policy capable of autonomously playing air hockey. Our agents learn solely from sparse rewards...
This study presents a novel deep learning approach aimed at enhancing stochastic Gust Load Alleviation (GLA) specifically for compliant wings. The approach incorporates the concept of smooth wing camber variation, where the camber of the wing's chord...
We analyze helioseismic waves near the solar equator in the presence of magnetic fields deep within the solar radiative zone. We find that reasonable magnetic fields can significantly alter the shapes of the wave profiles for helioseismic g-modes....