Tourniaire, Paul Ilie, Marius Hofman, Paul Ayache, Nicholas Delingette, Hervé
Since the standardization of Whole Slide Images (WSIs) digitization, the use of deep learning methods for the analysis of histological images has shown much potential. However, the sheer size of WSIs is a real challenge, as they are often up to 100,000 pixels wide and high at the highest resolution, and therefore cannot be processed directly by any...
Liu, Lucas Jing Ortiz-Soriano, Victor Neyra, Javier A. Chen, Jin
Published in
ACM-BCB ... ... : the ... ACM Conference on Bioinformatics, Computational Biology and Biomedicine. ACM Conference on Bioinformatics, Computational Biology and Biomedicine
With the rapid accumulation of electronic health record (EHR) data, deep learning (DL) models have exhibited promising performance on patient risk prediction. Recent advances have also demonstrated the effectiveness of knowledge graphs (KG) in providing valuable prior knowledge for further improving DL model performance. However, it is still unclea...
Shen, Guojiang Yu, Kaifeng Zhang, Meiyu Kong, Xiangjie
Published in
PeerJ Computer Science
Traffic flow prediction is the foundation of many applications in smart cities, and the granular precision of traffic flow prediction has to be enhanced with refined applications. However, most of the existing researches cannot meet these requirements. In this paper, we propose a spatial-temporal attention based fusion network (ST-AFN), for lane-le...
Ma, Tengfei
Remote Electrical Tilt optimization is an effective method to obtain the optimal Key Performance Indicators (KPIs) by remotely controlling the base station antenna’s vertical tilt. To improve the KPIs aims to improve antennas’ cooperation effect since KPIs measure the quality of cooperation between the antenna to be optimized and its neighbor anten...
Wei, Wen Poirion, Emilie Bodini, Benedetta Tonietto, Matteo Durrleman, Stanley Colliot, Olivier Stankoff, Bruno Ayache, Nicholas
Multiple sclerosis (MS) is a demyelinating and inflammatory disease of the central nervous system (CNS). The de-myelination process can be repaired by the generation of a new sheath of myelin around the axon, a process termed remyelination. In MS patients, the demyelination-remyelination cycles are highly dynamic. Over the years, magnetic resonance...
Tomy, Abhishek (author)
A human driver can gauge the intention and signals given by other road users indicative of their future behaviour. The intentions and signals are identified by looking at the cues originating from vulnerable road users or their surroundings (hand signals, head orientation, posture, traffic signals, distance to curb, etc.). Taking all these cues int...
Derwin Suhartono Gema, Aryo Pradipta Winton, Suhendro David, Theodorus Fanany, Mohamad Ivan Arymurthy, Aniati Murni
Published in
Journal of Big Data
Argumentation mining is a research field which focuses on sentences in type of argumentation. Argumentative sentences are often used in daily communication and have important role in each decision or conclusion making process. The research objective is to do observation in deep learning utilization combined with attention mechanism for argument ann...
Das, Srijan
This thesis targets recognition of human actions in videos. Action recognition is a complicated task in the field of computer vision due to its high complex challenges. With the emergence of deep learning and large scale datasets from internet sources, substantial improvements have been made in video understanding. For instance, state-of-the-art 3D...
Nourani, Esmaeil Reshadat, Vahideh
Published in
Journal of theoretical biology
Extracting biological relations from biomedical literature can deliver personalized treatment to individual patients based on their genomic profiles. In this paper, we present a novel sentence-level attention-based deep neural network to predict the semantic relationship between medical entities. We utilize a transfer learning based paradigm which ...
Isunza Navarro, Abgeiba Yaroslava
Just-In-Time Software Defect Prediction (JIT-DP) focuses on predicting errors in software at change-level with the objective of helping developers identify defects while the development process is still ongoing, and improving the quality of software applications. This work studies deep learning techniques by applying attention mechanisms that have ...