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DEEPSIGN: A DEEP-LEARNING ARCHITECTURE FOR SIGN LANGUAGE
(2018-11-13)
Sign languages are used by deaf people for communication. In sign languages, humans use hand gestures, body, facial expressions and movements to convey meaning. Humans can easily learn and understand sign languages, but ...
TOWARDS END-TO-END SEMI-SUPERVISED DEEP LEARNING FOR DRUG DISCOVERY
(2018-11-26)
Observing the recent progress in Deep Learning, the employment of AI is surging to accelerate drug discovery and cut R&D costs in the last few years. However, the success of deep learning is attributed to large-scale clean ...
CELL SEGMENTATION IN CANCER HISTOPATHOLOGY IMAGES USING CONVOLUTIONAL NEURAL NETWORKS
(2016-12-07)
Cancer, the second most dreadful disease causing large scale deaths in humans is characterized by uncontrolled growth of cells in the human body and the ability of those cells to migrate from the original site and spread ...
Deep Reinforcement Learning-based Portfolio Management
(2019-05-16)
Machine Learning is at the forefront of every field today. The subfields of Machine Learning called Reinforcement Learning and Deep Learning, when combined have given rise to advanced algorithms which have been successful ...
ULTRA-CONTEXT: MAXIMIZING THE CONTEXT FOR BETTER IMAGE CAPTION GENERATION
(2019-05-07)
Several combinations of visual and semantic attention have been geared towards developing better image captioning architectures.
In this work we introduce a novel combination of word-level semantic context with image ...
FROM TEXT CLASSIFICATION TO IMAGE CLUSTERING, PROBLEMS LESS OPTIMIZED
(2018-06-11)
Machine Learning is thriving. Every industry is using its techniques in some way to improve their efficiency and revenue. However, the focus on research is not divided equally between all of the different areas and problems ...
COMPREHENSIVE STUDY OF GENERATIVE METHODS ON DRUG DISCOVERY
(2019-12-09)
Observing the recent success of the deep learning (DL) technology in multiple life-changing application areas, e.g., autonomous driving, image/video search and discovery, natural language processing, etc., many new ...
Deep Representation Learning for Clustering and Domain Adaptation
(2019-12-05)
Representation learning is a fundamental task in the area of machine learning which can significantly influence the performance of the algorithms used in various applications. The main goal of this task is to capture the ...
LOW-DOSE CT IMAGE DENOISING USING DEEP LEARNING METHODS
(2021-05-07)
Low-dose computed tomography (LDCT) has raised highly attention since the counterpart, full-dose computed tomography (FDCT), brings potential ionizing radiation influence to patients. However, LDCT still suffers from several ...
Deep Learning Based Multi-Label Classification for Surgical Tool Presence Detection in Laparoscopic Videos
(2017-08-07)
Laparoscopic surgery, Modern surgery, where the surgery is performed far away from the patient by inserting small incisions on the patient's body and the surgery is performed with a help of a video recorder and through ...