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DEFENSE ARTIFICIAL NEURAL NETWORKS FROM ADVERSARIAL ATTACKS BY USING DEEP LEARNING CLASSIFICATION TECHNIQUES

Kanika Bansal, K Bansal, A Haider, Mandeep Jit Alobaidy, Mehran Singh, Rosdiadee Behjati, Nor Nordin, Abdullah Fadzilah, Natasha Angeloska-Galevska, Mohammed Awad, Eldar Boltachev, Massimo Buscema, Enzo Grossi, Antonia Creswell, Tom White, Vincent Dumoulin, Kai Arulkumaran, Biswa Sengupta, Anil Bharath, Roza Dastres, Mohsen Soori, Sandra Drozdz, Akash Goel, Matthew Mcgarr, Joel Katz, Paul Ritvo, Gabriella Mattina, Venkat Bhat, Calvin Diep, Karim Ladha, Anastasios Giannaros, Aristeidis Karras, Leonidas Theodorakopoulos, Christos Karras, Panagiotis Kranias, Nikolaos Schizas, Gerasimos Kaloger-Atos, Dimitrios Tsolis, Pol Grau, Jurado, Xinyue Liang, Alireza Javid, Saikat Chatterjee, Kyounggon Kim, Jun Seok Kim, Seonghoon Jeong, Jo-Hee Park, Huy Kang, Kim, Andrej Krenker, Janez Bester, Andrej Kos, Priyanka Sonali B Maind, Wankar, Fauzia Mitali S Mhatre, Mugdha Siddiqui, Paramjit Dongre, Thakur, Yazdan Movahedi, Michel Cukier, Ilir Gashi, Lisa Ulrika O Stlund, Yvonne Kidd, Neneh Wengstrom, Rowa-Dewar, Tianhang Kui Ren, Zhan Zheng, Xue Qin, Liu, Jurgen Schmidhuber, Igor Sherstov, Lyana Chetvergova, Yi Wang, Mahmoud Amin, Jian Fu, Heba Moussa, Yan Xu, Lili Mou, Ge Li, Yunchuan Chen, Hao Peng, Zhi Jin, Neha Yadav, Syed Anas Ansar, Pawan Chaurasia   +84 more
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Artificial neural networks and deep learning

American Journal of Orthodontics and Dentofacial Orthopedics
This chapter provides a comprehensive overview of Artificial Neural Networks (ANNs) and Deep Learning (DL), tracing their historical development, fundamental principles, and advanced architectures. Beginning with the foundational concepts of ANNs, including neuron structures, activation functions, and learning processes, the discussion extends to deep ...
Melvin Geubbelmans, Axel-Jan Rousseau, Tomasz Burzykowski, Dirk Valkenborg   +3 more
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Deep Learning and Artificial Neural Networks

2020
Artificial neural networks is an important tool used in artificial intelligence and machine learning or deep learning. An example of their applications is to image recognition.
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Artificial Neural Networks and Deep Learning in the Visual Arts: a review

Neural Computing and Applications, 2021
In this article, we perform an exhaustive analysis of the use of Artificial Neural Networks and Deep Learning in the Visual Arts. We begin by introducing changes in Artificial Intelligence over the years and examine in depth the latest work carried out in prediction, classification, evaluation, generation, and identification through Artificial Neural ...
Iria Santos, Luz Castro, Nereida Rodriguez-Fernandez, Álvaro Torrente-Patiño, Adrián Carballal   +4 more
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Eyelid basal cell carcinoma classification using shallow and deep learning artificial neural networks

Evolving Systems, 2021
Results of exhaustive application of neural network pattern recognition and classification of cases suffering from eyelid basal cell carcinoma are reported. Recognition and classification were based on shallow and deep learning methods; namely, multi-layer error backpropagation and convolution neural networks were utilized.
Adam Adamopoulos, Evaggelos Georgios Chatzopoulos, George Anastassopoulos, Efstathios Detorakis   +3 more
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Chlorella Algae Image Analysis Using Artificial Neural Network and Deep Learning

2017
Generally, solutions and results to a problem in image processing involve a lot of trail and testing with huge set of sample images. Chlorella is a single-cell, freshwater green algae, and it consists of green plant pigments, chlorophyll, vitamins, minerals, and protein, fiber, and omega fatty acids. The size of the chlorella cells are 10–30 μm. Due to
S. Lakshmi, R. Sivakumar
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Artificial Neural Networks and Deep Learning in Solid Organ Transplantation

Transplantation
Artificial neural networks are now used across many fields, from medicine to chatbots. However, they are often complicated and give “black-box” predictions. To better understand these models, we outline some of the terminology, provide example applications in solid organ transplantation, and offer recommendations for those interested in starting to use
Byron H. Smith, Aleksandar Denic
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