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Two-Minute Deep Learning-Powered Brain Quantitative Mapping: Accelerating Clinical Imaging With Synthetic Magnetic Resonance Imaging.

JMIR Med Inform
Liu Y, Yin H, Zheng Z, Liu W, Zhang T, Cai L, Niu H, Lv H, Yang Z, Wang Z, Ren P.   +10 more
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Deep Learning (DL) Oriented Forensic Analysis

Advances in Multidisciplinary and scientific Research Journal Publication, 2022
Cyber-attacks are now more prevalent than ever before in all aspects of our daily lives. As a result of this circumstance, both individuals and organizations are fighting cybercrime on a regular basis. Furthermore, today's hackers have advanced a step further and are capable of employing complex cyber-attack strategies, exacerbating the problem.
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qULM-DL: Quantitative Ultrasound Localization Microscopy via Deep Learning

2020 IEEE International Ultrasonics Symposium (IUS), 2020
Ultrasound localization microscopy (ULM) has been developed in recent years to significantly improve the spatial resolution of ultrasound imaging by localizing the microbubbles (MBs) flowing in microvasculature. Nevertheless, challenges remain in ULM. In our previous work (IEEE Trans. Med.
Tianyang Zhou, Mengyang Lu, Yi Yang, Qiong He, Jianwen Luo, Xin Liu   +5 more
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Auto-DL: A Platform to Generate Deep Learning Models

2021
Deep Learning (DL) model building is a tedious and taxing process. The number of prerequisites is high and a lot of time is invested. Hence, there is a scope of Automation. Code to build DL models follows a standard structure, broadly classified into four categories (Imports, Data Input, Model Creation, and Evaluation).
Aditya Srivastava, Tanvi Shinde, Raj Joshi, Sameer Ahmed Ansari, Nupur Giri   +4 more
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Malware Detection using Deep Learning (DL)

Journal of Advanced Research in Applied Sciences and Engineering Technology
The attack that occurred recently involved the utilization of malicious software, commonly referred to as malware, along with advanced techniques such as machine learning, specifically deep learning, code transformation, and polymorphism. This makes it harder for cyber experts to detect malware using traditional analysis methods.
Chowdhury Sajadul Islam, Madihah Mohd Saudi, Nur Hafiza Zakaria, Muji Setiyo   +3 more
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Smote-DL: A Deep Learning Based Plant Disease Detection Method

2021 6th International Conference for Convergence in Technology (I2CT), 2021
In the due course of time, computer vision, machine learning and deep learning has been widely used to detect disease in the plant leaf. Most works done in this area focuses upon coming up with accurate models but does not focus on the false predictions which could be a serious cause.
Subham Divakar, Abhishek Bhattacharjee, Rojalina Priyadarshini   +2 more
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